Physics World

A voting system with a high level of security intrinsically guaranteed by quantum mechanics has been demonstrated by two independent teams – one led by Federico Centrone at the Barcelona Institute of Technology and the other led by Rob Thew at the University of Geneva.

Their systems employ a quantum protocol that was first proposed by Centrone and colleagues in 2022 and uses a system of entangled qubits to ensure every voter has complete anonymity.

A conventional voting system – paper or electronic – could be hacked or corrupted at the counting stage, resulting in a rigged outcome or lack of anonymity. In 2007, Anne Broadbent and Alain Tapp at the University of Montreal proposed a possible solution: an e-voting protocol in which an election is broken into as many rounds as there are voters.

Before anyone casts a vote, Broadbent and Tapp’s system secretly assigns each participant to be the “real” voter in exactly one designated round. In that round, the chosen voter picks a value (either 0 or 1) representing their actual choice.

Secret ballot

In every other round, the system automatically submits a pre-assigned value on the voter’s behalf, engineered so the round’s total has a fixed parity – either always odd or always even. The real voter’s free choice then either flips this total to the opposite parity or leaves it unchanged, and the final odd or even result is recorded. Once every round is complete, each voter will have had their real say – but from the outside, the identity of the real voter in any given round is completely hidden.

Although this scheme is watertight in principle, there is still no guarantee that the e-voting system itself can be fully trusted. In 2022, a team led by Centrone proposed how this loophole could be closed by harnessing entanglement between quantum bits, or qubits.

In the quantum protocol, each voter is assigned a single qubit, prepared as part of one joint entangled state spanning all voters together. When measured, each qubit is randomly either a 0 or 1, But, because of the type of entanglement between the qubits, the total number of 1s across all voters is guaranteed to have the expected parity. Since not even the e-voting system itself can know the outcome of any individual measurement in advance, the protocol removes the need to trust whoever is distributing the values.

Easily adapted

Thew’s team realised that it could create this protocol in the lab. “We had just finished another experiment concerning distributed polarization entanglement and realized we could ‘easily’ adapt our setup to produce the entangled states required for the voting protocol,” says Geneva’s Joey Marcellino.

Both teams used spontaneous parametric down-conversion (SPDC) to create the entangled qubits, which were photons. Here, a laser is fired into a nonlinear crystal, splitting single photons into pairs of lower-energy photons that are entangled in terms of their polarization states.

SPDC is then repeated using the newly-entangled photons, chaining pairs together until reaching the same number of entangled photons as there are voters – albeit a small number in these demonstrations. The result is one single, large entangled state. Each individual photon then passes through a 50/50 beam splitter, is coupled into an optical fibre, and sent to a detector, where its state is measured.

Fidelity and success

In their first experimental tests of the technique, Centrone and colleagues were able to create the entanglement required for the voting protocol at success rate of about 96%. Meanwhile, Thew’s team achieved an 87% success rate.

Commenting on his colleagues’ result, Marcellino says, “This suffices as a proof-of-principle for the protocol and our modified approach, although obviously we would want to improve these numbers significantly for real-world applications”.

For now, the result demonstrates that e-voting systems with quantum-guaranteed security are achievable, using existing technologies including single-photon sources, detectors, and entanglement generation schemes.

“Moreover, in the end the protocol is just a way to anonymously distribute a bit with perfect security,” Marcellino adds. “While this is obviously useful for voting, it could also work as an anonymous message board, or to enable anonymous distributed computation.”

The research is described in Physical Review Letters: Thew and colleagues; Centrone and colleagues.

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As the world of quantum computing grows and researchers work towards scaling up quantum systems, energy consumption is becoming a major concern. Beyond the small scale and high level of control in a laboratory environment, the lasers that power quantum systems result in a large energy cost that may act as a bottleneck for the integration of quantum technology.

Publishing their findings in Optica, researchers have demonstrated that sunlight can be used to generate pairs of entangled photons, providing a more energy efficient alternative to laser-pumped systems. This collaborative project combined theoretical research led by Robert Boyd at the University of Ottawa with technology developed by Hanieh Fattahi’s research group at the Max Plank Institute for the Science of Light in Erlangen, Germany.

Overcoming assumptions

Optical quantum computers use pairs of entangled photons as qubits, with the nonlinear optical processes used to produce them typically relying on lasers. This is largely due to two assumptions: firstly, that high optical coherence is required, meaning that the light waves maintain a steady phase relationship; and secondly, that lasers are the only way to achieve the necessary optical power density for these methods.

Sunlight, while naturally abundant, is largely incoherent and is difficult to collect in concentrations comparable to that of lasers. As such, this natural reservoir of optical input has been largely overlooked as a direct resource for nonlinear optical processes.

The researchers behind this latest study are challenging these assumptions with a new system that uses sunlight to fuel a process called spontaneous parametric down-conversion (SPDC). In this process, a pump beam – usually a laser but replaced here with solar light – interacts with a nonlinear crystal, splitting individual photons into entangled pairs.

Previous work from Boyd’s team demonstrated that incoherent light from an LED can produce photons with entangled polarization states. By achieving entanglement powered by sunlight, this new research further overturns both assumptions about the necessary properties of the optical input.

Harnessing the Sun

To harness the plentiful yet highly dispersed sunlight, Fattahi’s team had to develop a device that focuses sunlight down to a point approximately 2 mm wide, to be coupled to a fibre as thin as a human hair. To achieve this, they used a Fresnel lens and spectral filter to collect sunlight, and a glass cone-shaped concentrator to funnel the light to a point, where it is coupled to the fibre. The fibre then directs the sunlight into the nonlinear crystal to induce SPDC.

Fattahi described the “significant practical challenges” involved with implementing such a system. Along with having to continuously track the Sun, the outdoor nature of the experiment left it vulnerable to both environmental effects and background light. Eventually compensated for by enclosing the system in a tent, the background light was initially offset by students beginning measurements at around 3 a.m. to make the most of the natural darkness.

Overcoming both theoretical and practical concerns, the system was able to successfully produce entangled photons. The states produced violate Bell’s inequality (as the photon correlations cannot be modelled classically) with an S value of 2.54, where S = 2 is the threshold for indication of quantum behaviour, and a 94% fidelity to the target entangled Bell state.

Significantly, when normalized in terms of the spectral bandwidth of the pump, sunlight-powered SPDC demonstrates a photon pair generation rate comparable to that of the laser-pumped process. This method eliminates the need for electrical-to-optical energy conversion, providing a viable path towards increasing energy efficiency.

The future of photon production

The development of quantum technology is vital for the future of secure communication, ultraprecise sensing and high-performance computation. Taking steps to develop a sunlight-driven method of photon pair production will potentially allow scaling of this technology without the major energy cost.

Minimizing energy consumption and system complexity would be a huge benefit for systems operating in demanding conditions, such as polar deserts. This research is particularly striking when considering space-based quantum technology. Sun-synchronous orbits could allow near constant access to a naturally occurring, reliable pump-source.

Fattahi and her team intend to develop a field-deployable version of this system, with a focus on greater integration which should “significantly improve mechanical stability, efficiency and overall practicality”. There is also potential to expand the portion of the solar spectrum used in this experiment. Fattahi described the “exciting possibility” of using different spectral regions to drive multichannel entangled-photon generation, increasing efficiency and capacity.

Research into new, energy-efficient photon production has the potential to remove a major barrier for the integration of quantum technologies and contribute to a brighter future for quantum computing.

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When I went to university, I didn’t know what kind of career I wanted to pursue. I’d originally applied to study geophysics, but after a few weeks realized mineral exploitation wasn’t my thing and quickly switched to maths. Then, at the end of my first year, I had a range of degree options open to me and, whilst I preferred (and was better at) maths, I just didn’t feel it was my best choice for a career.

So I decided to switch again, this time to physics. During my degree, a few friends and I joined the Student Industrial Society (now known as the Bright Future Society). It gave us the chance to visit a range of companies – from micro-breweries and wine importers to TV studios, nuclear-power stations and semiconductor manufacturers. We also went to Llanwern steelworks in South Wales, where a closing session with a British Steel careers advisor really shook me up.

A feisty Yorkshireman, he started off by directly asking each of us what we planned to do after university. We were all put on the spot and our answers, which were embarrassingly unsure, failed to impress him. The advisor firmly suggested that if we didn’t know what our plans were by now, we had better find out before it was too late. For me, it was a wake-up call and when I got back to campus, I went straight to the careers office and started applying for summer student placements.

To my amazement, and despite my lack of experience, I was offered several positions and decided to take a summer job in Malvern at the Royal Signals and Radar Establishment, which is now part of the private defence-technology firm QinetiQ. Somehow, I managed to find something useful to work on and after 12 weeks had done enough to be as included as co-author on a peer-reviewed publication.

Summerlove sensation

After the placement, I continued with my physics degree, but began to feel something about physics wasn’t quite right for me. Whilst I loved the classical side of the subject and the real-world applications, I struggled with the less visible aspects, such as quantum and nuclear. So after a final-year project investigating the aerodynamics of cars – and finding myself more interested in my housemate’s mechanical engineering course – I wondered if I might be better suited to a career in engineering.

On the back of this growing interest, I applied to do a PhD in high-speed aerodynamics at the University of Southampton. My final-year project – coupled with my grounding in physics and the fact that I had a journal publication to my name – must have impressed my future supervisor, who picked me for the project. I had a great time on my PhD, which proved I loved engineering – particularly aerospace.

After four years in research, I realized an academic career wasn’t for me. But my PhD proved handy as it led to me getting a job with a small business called Stewart Hughes Ltd, which built vibration-monitoring equipment for use on mechanical machines. The company was looking for people with an academic background whose presence could help secure US government research funding. It turned out to be a sound strategy, as the firm built up a significant track record in winning high-value government grants.

My advice to you

These days I work a lot with interns and science or engineering students, who often ask me about my career path. As you can see, it wasn’t straightforward – and I believe a lot of people struggle making choices early in their careers. It’s easy to think you need to have everything mapped out in advance, which is rarely how things pan out. With that in mind, here are a few tips if you are starting out on your own career journey.

Doing the rounds

One interesting bit of advice was once given to me on a career session led by a senior human-resources executive who works for a global corporation. The exec told us how he’d been having a golf lesson and was about to hit the ball down the fairway when the coach stopped him and asked where he was aiming. After explaining he was hoping to land the ball on the green, the coach shot back: “Yes…but where exactly on the green?”

Set your goal, do your best to reach it, and don’t worry too much about potential pitfalls.

Obviously the exec said he wanted to get a hole in one, but he was also trying to avoid the bunker and the long grass. The coach went on to explain that golfers should aim at the target and not be distracted by obstacles. Stay focused and the ball will land at or near the target. The exec saw this as the perfect analogy for one’s career: set your goal, do your best to reach it, and don’t worry too much about potential pitfalls.

Now that’s easier said than done – in fact, my career journey has not been the epitome of this advice. There have been bumps and detours along the way, which haven’t necessarily been through lack of focus, but because it took me time to discover what I really wanted to do. To stretch the golf analogy to breaking point, my first green might have not been great, but I’ve certainly had fun making it round the course.

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Sensors designed to record earthquakes can reveal insights into a very different natural hazard – how hurricanes evolve and intensify as they strike land. The surprising connection has been made by researchers in the US, who examined data from seismic sensors installed in Louisiana for studying the interior of the Earth. They found that the sensors, which collected data on pressure fluctuations, provided information about how Hurricane Isaac grew and intensified as it struck and devastated the state in 2012.

Earthquakes and hurricanes are very different in how they form, move and impact the Earth. The parameters governing these natural hazards – and the way that we measure them – are also distinct given that one is a geophysical phenomenon and the other atmospheric.

Hurricanes, which form over warmer tropical and subtropical ocean waters, are rotating systems of cloud and thunderstorms. They consist of a calm, central “eye”, a surrounding layer of tall thunderstorms, and strong winds called the “eyewall”. Spiralling away from the eyewall are bands of clouds and thunderstorms.

Forecasters describe the structure and evolution of hurricanes using three main parameters: track, intensity and the radii of the wind layers around the eye. But when hurricanes strike land, particularly important is the turbulence in the lowermost layer. That’s where momentum, heat and moisture mix between the atmosphere and the ocean or land.

Eyeing up hurricane path and intensity

Measuring the turbulence in this boundary layer is critical both for forecasting wind intensity and for developing and validating weather models. Such data are usually collected using reconnaissance aircraft, ocean buoys and onshore towers and radar. But flying planes into hurricanes is dangerous, while onshore towers are sparse, making data-gathering tricky. Continuous monitoring of a storm’s passage is not easy either.

In the new study, Qing Ji, Ipshita Dey and Eric Dunham from Stanford University processed data from seismic stations in Louisiana that are part of a network of 1700 stations across the US. Equipped with both infrasound sensors and seismometers, these “seismoacoustic” stations are designed to record seismic activity.

The infrasound sensors measure pressure fluctuations at the Earth’s surface, with the seismometers recording the resulting elastic response. But when the hurricane passed through the equipment, the winds were strong enough to leave an additional signal. In fact, the Stanford team found that the data revealed the calm eye and the turbulent eyewall – as well as the circular layers of thunderstorms and winds as the hurricane passed through the sensors.

“The infrasound sensors provide direct measurements of turbulent pressure fluctuations,” says Dunham. “We also used the seismometer data together with data from other atmospheric sensors to calibrate a computer model of hurricane turbulence.” The model provided space-time correlations of pressure fluctuations around the station, while the simulated pressure spectra matched the recorded data at station.

The researchers then calculated the Earth’s elastic response using the simulated pressure field, which aligned with the observed vertical displacement. More importantly, the simulations showed that the relevant parameter for calculating the Earth’s elastic response to pressure fluctuations is the velocity at which those fluctuations are carried downstream — rather than the near-surface wind speed as had been assumed.

Exploiting existing sensor networks

Dunham told Physics World that he hopes the study will draw attention to the potential of seismoacoustic networks for atmospheric sciences. “Perhaps this will lead to deployments of seismometers and infrasound sensors in areas where coverage is currently sparse, like in the southeastern US,” he adds.

Those hopes are echoed by Ji – now based at the University of Texas, Austin – who says there is a growing interest in the use of these “noise” signals for environmental monitoring. As Ji points out, the beauty of seismic stations is that they record data continuously and have a high sampling rate compared to other sensors.

Seismoacoustic stations have already been used to study various environmental and climatic phenomena, such as rising amounts of energy in ocean waves as waters warm and the evolution of tropical storms and accompanying winds. “The atmospheric imprints, however, are less studied partly due to the overall smaller amplitudes and the potentially more complicated nature,” Ji adds.

Dunham also sees an opportunity to add infrasound sensors and barometers, both of which measure atmospheric pressure, to existing seismometers. “Having multiple sensors at a single location opens up new opportunities for studying both the solid Earth and atmosphere,” he says.

The researchers report their findings in Science.

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Particles such as protons and neutrons are more accurately represented as “baryon junctions” than as simple collections of three quarks, say physicists. This finding, which is based on studies of heavy-ion collisions, is at odds with textbook descriptions, but it confirms a longstanding belief among many nuclear physicists that these descriptions are over-simplified.

Like charge and energy, baryon number is conserved in all experimentally observed reactions. This conservation law was first articulated in 1938, long before physicists developed the theory of quantum chromodynamics (QCD) to explain the behaviour of nuclei. It also predates the coinage of the term “quark” by Murray Gell-Mann in 1963.

Initially, theorists working on QCD felt that the simplest way to incorporate baryon number conservation was to assign a baryon number of 1/3 to every quark and -1/3 to every antiquark. As bound states of three quarks, protons and other baryons therefore have a baryon number of +1, antibaryons are -1, and quark-antiquark pairs, or mesons, are 0. However, this association of the baryon number with the quark – known as the valence quark model – is not fundamental to QCD, and as early as the 1970s theorists were already considering alternatives. In 1996, for example, Dmitri Kharzeev of Stony Brook University in New York, US proposed a model in which the baryon number was assigned not to the quarks themselves but to the Y-shaped junction in the gluon field that mediates their interactions.

At high-energy accelerators such as the LHC, collisions are usually modelled in the high-energy “perturbative QCD” regime. Here, quarks can be treated as isolated particles, and the two models are effectively equivalent. Inside a proton or in a quark-gluon plasma, however, quarks are more deeply immersed in the gluon field. This makes perturbative calculations such as those used in the theory of quantum electrodynamics (QED) impossible. “You can’t do these Feynman-like calculations anymore,” explains Anselm Vossen, an experimental nuclear physicist at Duke University in North Carolina, US. “Every diagram you write out has the same importance.” Within this so-called “lattice QCD” regime, the two models’ predictions can differ.

Discrepancies between models

In the new work, the STAR collaboration – which studies particles produced in quark-gluon plasmas generated at Brookhaven National Laboratory’s Relativistic Heavy Ion Collider (RHIC) in New York, US – homed in on these differences. By comparing predictions from the baryon junction model with those from the valence quark model in various scenarios, and matching them against experimental results, they hoped to find evidence to support one model over another.

First, they studied head-on collisions of gold nuclei, plus near-misses that led to the exchange of a virtual photon and the break-up of one nucleus. They found that the proportion of particles scattered varied sharply with the energy of the incoming nuclei, but not as the valence quark model predicted.

“The net baryons scattered decreases as the beam energy increases – that is expected – because the higher the energy the more things will just move straight through without being scattered to a large angle,” explains Chun Yuen Tsang, a STAR project leader who is now at Argonne National Laboratory in Illinois. However, he adds that the rate of decline “is actually slower than the existing valence quark model would have you believe”. A baryon junction should scatter more easily than a valence quark, so the fact that a simulation designed using the latter model underpredicts scattering at high energies points towards the baryon junction model.

A charged result

The researchers also compared fragments produced in collisions with zirconium-96 and rubidium-96 nuclei. Since both particles contain the same number of nucleons, they have the same baryon number. However, the ruthenium-96 nucleus has 44 protons, whereas the zirconium-96 nucleus has only 40, giving them different electric charges.

In a nuclear collision, both charge and baryon number – while being conserved overall – are rearranged among the fragments. The charge is localized to the quarks, so, according to the valence quark model, charge and baryon number should move approximately the same amount. Because the colliding nuclear pairs in this experiment differed only in their charge, the outcomes of collisions could be predicted relatively well across a range of energies. However, these predictions were strongly violated, with baryon number moving much more easily than electric charge. “This is evidence for quarks not being the carriers of both baryon number and electric charge,” Tsang says.

The researchers now wish to study collisions from other experiments. They also hope that the Electron-Ion Collider currently planned to replace RHIC will provide a more precise baryon probe and yield a definitive answer.

Vossen, who was not involved in the research, says that in some sense, its conclusions are “not that surprising”. His own research has examined the so-called “proton spin crisis” precipitated by the discovery that the proton’s spin cannot be explained by the spin of its constituent quarks, while the proton’s mass is much greater than the sum of the quark masses. “It’s part of this general picture that shows that a proton is much more complex than three valence quarks,” he says. Nevertheless, he says the STAR findings are not trivial: “It’s still a very interesting result,” he concludes.

The work is published in Science.

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Fancy some more? Check out our puzzles page.

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Researchers at the Flatiron Institute in New York City have used a new tensor network (TN) scheme to simulate how Ising spin glasses evolve in time. In many cases, their classical method is more accurate than the latest quantum annealers running the same problem. The results scale in two and three dimensions and raise the bar in the ongoing competition between classical and quantum computers for simulating many-particle quantum systems.

Classical versus quantum

Quantum many-particle systems provide a good way of comparing computational techniques because their complexity grows exponentially with the number of particles. In theory, quantum computers hold an advantage rooted in entanglement and superposition. In a classical computer, the spin of a particle (up or down) is encoded in bit that is either zero (down) or one (up), but never both. In a quantum computer, the spin can be encoded in a qubit holding a quantum superposition of up and down. This is a much more natural way to represent what the simulated system is actually doing.

Recently, a team of quantum computing researchers used the D-Wave’s Advantage2 quantum annealer to simulate Ising spin glass dynamics and claimed that classical computers could not match their results. But now, Joseph Tindall and colleagues at the Flatiron Institute have shown that a classical scheme can do just as well -and sometimes better- than the annealer.

In this occasion, the competition involved the simulation of the Ising spin glass model, which describes spins on a lattice pointing in random directions. This disordered state is product of different nearest-neighbor interactions for different pairs of spins. The difficulty of this famous problem grows with the system size, which makes it a good benchmark for comparing classical and quantum performance.

Tensor networks

The tensors used by Tindall and colleagues can be thought of as LEGO pieces. Just as LEGO bricks have knobs and tubes that snap together to build a bigger array, tensors have legs (bond indices) that join through a process called contraction to form networks. In a many-particle simulation, each tensor represents a site along with its physical attributes: for instance, the type of particle it hosts, which could be a spin or an electron. Connected together, the tensors form a network that encodes how those particles interact and how entangled they are. Widening the legs (increasing the bond dimension in technical terms), allows the network to capture the correlations more accurately.

In simple terms, the pattern of connections describes how particles can move or interact, and what Tindall and colleagues built is a tensor network representation of both the Ising spin glass Hamiltonian and wave function. The first specifies the interactions between spins and the second describes the state of spins. Writing quantum states this way has proved enormously useful for accessing large systems, where the sheer number of particles rules out any exact solution.

Tindall’s group used these tensor network ideas to simulate the spin glass model’s dynamics. But there is a catch: as a TN wave function evolves forward in time, entanglement builds up between different parts of the system and the bond indices must widen to keep track of the growing correlations. This increases the computational cost of finding the ground state of the system at different times, making it more difficult and sometimes impossible.

Belief propagation

To compensate for this, the team used a belief propagation (BP) message passing approach to perform the contraction. In this scheme, each tensor receives a compact summary of what the rest of the network “looks like” from its perspective (the effective environment of each tensor). This unlike the conventional approach of accounting for every single contribution exactly. As Tindall points out, their approach can be understood as a mean field approximation on each tensor’s environment since the pieces of information reaching a particular given tensor from each of its neighbours are assumed to be independent.

By implementing this TN–BP approach, their classical implementation could evolve the system to much longer times than conventional TN schemes and manage far enough to reach the regime the quantum annealer operates. Conceptually, passing messages about an effective environment lets the computation to keep pace with the entanglement inherent to the system’s time evolution. The researchers then measured how the spin at one site relates to the spin elsewhere on the lattice (the two-point correlator) at various times and system sizes on two and three-dimensional lattices with cylindrical, diamond and cubic geometries.

Starting with a cylindrical lattice, the team compared the error in the two-point correlator error from the annealer with that from the TN-BP message passing approach. Once the bond dimension was large enough, the classical error was markedly lower error than the quantum counterpart at different annealing. On the diamond lattice, the classical error obtained again came in below the annealer’s, while on the cubic lattice the error was of the same order at a fixed annealing time.

What comes next

This work, which is described in Science, shows how fast classical simulation of quantum physics is advancing and how the on-going competition between classical and quantum computation is driving this progress.  In the future, Tindall and colleagues want to apply the TB-BP to interacting electronic systems such the Hubbard model. Additionally, the group is also extending their scheme to finite temperature problems as well as maintaining their open-source tensor network quantum simulator library.

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Astronomers have found the best evidence yet for a companion star to Betelgeuse, the brightest star in the constellation Orion. Based on data obtained by the SPHERE instrument on the European Southern Observatory’s Very Large Telescope (VLT) in Chile, they say this companion may be responsible for the red supergiant star’s periodic changes in brightness, which have puzzled scientists for decades.

Betelgeuse is a red supergiant star located about 548 light-years away. As the 10th brightest star in the night sky, it is generally visible even in locations with substantial light pollution. However, its brightness varies over a period of roughly 420 days, superimposed on a longer 2200-day modulation.

For decades, astronomers have suspected that some of these variations could be caused by a companion star that modifies the distribution of cosmic dust that Betelgeuse produces and expels. These changes in cosmic dust would, in turn, change the amount of its light that reaches us here on Earth.

A few years ago, two studies (published in The Astrophysical Journal in 2024 and 2025, but available as preprints beforehand) predicted that in December 2024, this companion star would be at its greatest distance (maximum elongation) from Betelgeuse, making it easier to detect. To take advantage of this opportunity, researchers led by Miguel Montargès of the Observatoire de Paris – PSL, France, requested observing time on the VLT. Although the same studies predicted that the companion would not be massive enough to be detectable with current instrumentation, Montargès and colleagues nevertheless hoped to place upper limits on its stellar parameters.

A difficult analysis

The astronomers used the SPHERE instrument on the VLT to image light from the region where the companion was expected to be, followed by advanced post-processing techniques originally developed to search for exoplanets. Betelgeuse’s brightness and large angular size made this analysis difficult, explains Montargès, but he and his colleagues were nevertheless able to gather enough data to identify a “Betelbuddy” with a confidence of 6σ. As Montargès points out, this is better than the previous upper limit of 1.5σ reported by astronomers at NOIRlab in 2025, and above the usual 5σ threshold that constitutes an “observation” or “discovery”.

Despite this, the astronomers say that before they can be certain that they have really detected a companion that it is indeed gravitationally bound to Betelgeuse, they will need to perform additional observations next year. At that point, they will attempt to confirm the companion’s presence by observing it half a period after the initial detection, on the other side of the red supergiant. “We will then continue observing it to get a precise characterization of its orbit (semi-major axis, eccentricity and inclination, among other parameters),” Montargès says. “These will be required to understand the past and future evolution of the system.”

What happens next

As a mature supergiant star, Betelgeuse is expected to undergo a supernova explosion at some point. The presence of a companion star could affect how this process plays out, and even dictate when the eventual explosion occurs. “It is clear to me that this companion detection will now trigger a wave of new studies on the evolutionary status of Betelgeuse,” Montargès says. “Depending on past, present and future interactions between the two stars, the supernova could possibly be advanced or delayed.

“Betelgeuse is a star that has been observed throughout history,” Montargès continues. “It was even depicted in prehistoric paintings, yet we are discovering one of its fundamental characteristics only now.”

And that is not all: “30% of red supergiants in our galaxy show the type of light variations that led to the discovery of Betelgeuse’s companion,” he tells Physics World. “We may have opened a new avenue to find such binary systems, when the primary star is an evolved star like Betelgeuse.”

The new study is detailed in Astronomy and Astrophysics.

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For a chemical reaction to occur, atoms and molecules need to collide. However, not every collision produces a reaction. If the atoms and molecules are not favourably aligned with each other, nothing will happen. The “point of impact” of the colliding entities is also important, and it is hard to control because it requires confining the reactants along precise paths.

A team at the University of Graz, Austria, has now shed fresh light on this question by observing molecular coupling reactions on a single-crystal surface. “For the first time, we have been able to directly observe in real space and with single molecules which collision geometry must be met for a successful reaction,” explains Leonhard Grill, a physicist at Graz who co-led the study with post-doctoral researcher Matthew Timm. “Importantly, our experiment covers all geometric aspects of a reaction, namely, the precise location at which the reactants ‘touch’ each other upon collision, the ‘impact parameter’ (that is, how far the collision is from the reactants’ centre of mass) and the orientation of the reactants.”

Based on these observations, the researchers concluded that reactions only occur within a so-called “cone of reaction” that is defined by the colliding particles contacting at a specific point and a certain angle. This finding could lead to a better understanding of chemical reactions at the atomic scale and, ultimately, to ways of controlling and optimizing them.

Control of impact parameters

Grill and Timm used a scanning tunnelling microscope (STM) to project a molecule of difluorocarbene (CF₂) onto a target radical (BTFyl) anchored to a copper surface. This set-up enabled them to control the impact parameter by launching the CF₂ molecules directly and in a straight line along different atomic rows on the surface. They were also able to control the orientation of the BTFyl target by rotating it around its anchor point.

The researchers observed that reactions mainly occur when the CF₂ approaches the BTFyl target on the same copper row to which the target is bound. This didn’t happen often. In fact, only six of the 79 collisions they observed – corresponding to a narrow range of impact parameters – resulted in a chemical reaction, and reactions did not happen at all when the orientation of the CF₂ and the BTFyl deviated by more than 15 °.

“Controlling the impact parameter was for a long time considered to be the ‘forbidden fruit’ of reaction dynamics because of the technical difficulties to control it,” explains Grill. “The main challenge for us was how to do such experiments with relatively large molecules, which can have many adsorption orientations on the surface.”

A new view of collisions

Grill believes that the study’s findings could change the way we view collisions between reactants. “The new picture we have gleaned concerns not only the impact parameter, so where one reactant has to collide with another, but also the orientation of the involved compounds,” he tells Physics World. “If the reactants become larger and also have various side groups, understanding the cone of reaction might become even more important to understand, control and predict reaction rates.”

The researchers, who detail their work in Science, say they are already studying similar systems to assess whether the behaviour they observed can be generalized. In a related article, Jonas Björk of Linköping University, Sweden, suggests that further measurements could reveal how molecular structure, reactive sites and environment shape reaction pathways, enabling more predictive control of surface chemical transformations. “They could also enable single-molecule studies of how chirality influences chemical reactivity by directly controlling the handedness and orientation of reactants,” he adds.

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Molecularly imprinted polymers (MIPs) are synthetic receptors that can recognize target analytes through tailored binding sites, offering a stable, cost-effective and versatile alternative to natural bioreceptors. In electrochemical sensing, MIPs have attracted growing interest because they can provide high selectivity while enabling rapid, portable and low-cost detection.

This webinar will introduce the fundamentals of molecular imprinting, including binding site design, polymerization strategies, template removal and immobilization on electrode surfaces. It will then compare molecularly imprinted non-conducting polymers (MINPs) and molecularly imprinted conducting polymers (MICPs), focusing on their differences in conductivity, binding-site accessibility, reproducibility, sensitivity and selectivity. Recent advances in MIP-based electrochemical sensors will be discussed across representative applications, along with current limitations and design strategies to improve sensor performance.

The webinar will conclude with perspectives on how conducting polymers, nanomaterials and optimized molecular recognition can guide the development of next-generation selective and sensitive electrochemical sensors.

Wonhyeong Kim is a postdoctoral research associate in the department of materials science and engineering at the University of Arizona. He received his PhD in materials engineering from Auburn University, where his research focused on molecularly imprinted polymers, conducting polymers and electrochemical sensors for selective chemical and biomarker detection. His work has resulted in multiple publications in leading journals and he was the recipient of the 2025 ECS Sensor Division Student Research Award for his contributions to molecularly imprinted polymer-based electrochemical sensors. His research interests include molecular imprinting, conducting polymers, electrochemical sensors and functional materials for selective chemical sensing, with recent work expanding into advanced polymeric materials and nanomaterials for environmental applications.

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Newborn and rapidly growing supermassive black holes could be powering the mysterious “little red dots” that litter the early universe. That is the conclusion of an international team of astronomers who have found the best evidence yet for a new kind of object called a “black-hole star”, which appears to be driving a little red dot that existed just 660 million years after the Big Bang.

“A little red dot is an extraordinary object,” says team leader Rohan Naidu, of the University of Hawaii and MIT. “Somewhere within it lies a black-hole star, surrounded by a good old fashioned galaxy.”

When the James Webb Space Telescope (JWST) began observing the distant universe in the summer of 2022, astronomers were astonished to find lots of little red dots. They are highly luminous as one would expect an active black hole to be, but their spectra are odd, looking more like stars with no X-ray emission.

Some astronomers believe little red dots are dense cocoons of gas incubating a growing black hole at their cores. As the black hole accretes gas from the interior of the cocoon, it radiates energy that is absorbed by the cocoon – making it glow brightly. This is similar to how stars shine, the radiation from their core heating their outer layers. Hence these hypothesized objects are dubbed black-hole stars.

Until now, however there had only been circumstantial evidence for this hypothesis. Part of the problem is that in most cases the light from the little red dots mingles with the light from the unresolved host galaxy, clouding the observations.

Miracle or mirage?

Naidu is co-lead of the Mirage or Miracle (MoM) survey. When pushing to high redshifts (further distances) with the JWST, it can be difficult to discern whether a faint red splotch is really a high-redshift galaxy or a cool star in the foreground masquerading as something from the early universe.

Now, MoM has found a black-hole star shining 100 billion times brighter than any known star, and drastically outshining its host galaxy.

Called MoM-BH*-1, the object is incredibly luminous at longer wavelengths, but below the wavelength corresponding to the Balmer series of hydrogen emission there is no light at all. This sudden drop in luminosity is called the Balmer break and is often seen in young stars.

“In MoM-BH*-1 the Balmer break is three to four times stronger than any we’ve seen ever before,” says Naidu. “This feature alone tells us there is something truly singular afoot, and that this is a new kind of astrophysical object.”

Extremely dense cocoon

Simulations modelling the Balmer break and the object’s luminosity strongly suggest that there is a 100,000 solar mass black hole at the centre of MoM-BH*-1, surrounded by an extremely dense cocoon of gas.

“The physics of how its light is being produced by this dense gas cocoon around this black hole is radically different from what we see around us in the local universe,” says Naidu.

If the object is indeed a black-hole star, a salient question is how did the black hole form? Numerous possibilities have been raised, from the direct gravitational collapse of a gas cloud to the merger of a cluster of massive stars.

Naidu favours an explanation involving a supermassive star – an object that could have formed about 150 million years after the Big Bang when the universe was dense with hydrogen and helium. According to many popular models, these conditions spawned stars thousands of times the mass of the Sun.

Recent outburst

Naidu points to the life cycles of the massive stars in the Milky Way, which top out at a few hundred solar masses. Eta Carinae, for example, had an outburst in the 1840s that made it the second brightest star in the sky for several days. The outburst from this 100-solar-mass star left a cocoon of gas called the Homunculus Nebula. A much larger supermassive star could have had a similar outburst and then collapse to a black hole, thereby creating a black hole star.

“In the past few months I’ve seen so much evidence for this, that at this point, it is the main hypothesis that needs to be proved or disproved because the similarities to supermassive stars are uncanny,” says Naidu.

Indeed, it is possible that every supermassive black hole in the universe could be a relic of the very first giant stars created just after the Big Bang. Over time these objects would steadily erode their gaseous cocoon, eating it  away from the inside-out while radiation from accretion onto the black hole would blow away the remainder of the cocoon. This is supported by a recent discovery by NASA’s Chandra X-ray Observatory of a little red dot that existed 11.8 billion years ago and from which X-rays are starting to peak through holes in its shredded cocoon.

Naidu is suitably awe-struck by the possibilities, describing how “it’s inspiring to be witnessing the birth of supermassive black holes.”

The discovery of MoM-BH*-1 is reported in Nature.

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This episode of the Physics World Weekly podcast explores how the innate curiosity of children can help make quantum mechanics more accessible to the public. My guest is Katia Moskvitch, who co-hosts The Quantum Kid video channel with her 10-year-old son Kai.

As well as interviewing leading lights in quantum science and technology – including Nobel laureates – the duo has toured science labs including CERN. Moskvitch explains how the programme’s child-led approach puts guests at ease and helps them explain difficult concepts to a general audience.

Moskvitch believes that children can be more receptive to counterintuitive quantum concepts than adults and argues that an early familiarity with quantum physics could inspire young people to study science. This, she believes, will provide a foundation for success in the burgeoning quantum sector.

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Most people can perceive different colours in the visible range of the electromagnetic spectrum – at wavelengths between about 400 and 700 nm. However, our eyes cannot see infrared radiation, let alone perceive infrared “colours”. But now a team at China’s Beijing Institute of Technology has created colloidal quantum dot-based light upconverters that convert the infrared to the visible while preserving the spectral notion of colour. These nanostructures can be incorporated into wearable eyeglasses and, more ambitiously, could someday be implanted directly into the retina.

Photoreceptors in mammalian eyes contain light-absorbing pigments consisting of opsins and their covalently linked retinals. Infrared light at wavelengths greater than 700 nm cannot be absorbed by these photoreceptors, so when such light reaches the retina no corresponding electric signal is sent to the brain. Seeing infrared radiation could reveal otherwise invisible features and improve night vision, which relies on infrared light.

In recent years, researchers have made great strides in developing materials that capture photons with lower energies (in the infrared, for example) and re-emit them as photons with higher energies (typically visible or ultraviolet light). This process is known as upconversion, and the emitted light is said to be anti-Stokes shifted. This has led to the development of photoreceptor-binding upconversion nanoparticles that convert infrared light into visible emissions. These have been injected into mouse eyes and have been used to create wearable lenses for humans – with nonlinear upconversion projecting infrared-transformed visible light onto the cornea. While effective, these applications are limited to the narrow near-infrared (NIR) spectral range.

Confined electrons

Now, a team led by Ge Mu and Xin Tang studied a structure made up of semiconducting mercury telluride (HgTe) colloidal quantum dots (CQDs) atop an organic light-emitting diode (OLED). The OLED contains two light-emitting layers, one red-light-emitting and one cyan-light-emitting. Because of the small size of the CQDs, the electrons in them are confined in all three directions. This means that the electrons are restricted to discrete and separate atomic-like energy subbands rather than having access to a continuous band of allowed energies as they would in a bulk material.

When the CQDs absorb photons with infrared wavelengths, spanning the NIR to short-wave infrared regions, they produce excited carriers (electrons and holes) that then travel from their different energy levels into the OLED. This is a seamless process because the OLED is designed so that its electronic bands align with the sub-bands of the HgTe. When either the light intensity or the wavelength of the incident infrared light changes, explains Tang, the excited photocarriers are transported and recombined in the different emissive layers of the OLED thanks to the hole-trapping barriers that were engineered in these layers. The result is infrared-to-visible-light (red and cyan) upconversion.

Semi-transparent wearable eyeglasses

As a proof-of-concept, the researchers integrated their upconverter into lightweight, semi-transparent wearable eyeglasses and found that they can project multispectral infrared light onto the retina without affecting normal vision, so allowing the wearer to see infrared light as well as visible light. Indeed, a wearer can detect infrared light at wavelengths greater than 2 μm with a luminance of over 700 cd m⁻².

Looking ahead, Tang says that the upconverter could be bound to light-sensitive proteins in the retina and so serve as an implantable next-generation retinal bionic photoreceptor. This structure would transform infrared light into visible light emissions that stimulate light-sensitive proteins on retinal neurons to bypass damaged photoreceptor cells and potentially restore visual function across both the visible and infrared.

This full colour upconverter has been a long-term project in my group, Tang tells Physics World. “Starting from an efficient single-colour upconverter, we then successfully demonstrated colour-tuneable OLEDs and Si-/Ge-/CMOS-integrated upconverters. And with our recent progress on the understanding of interfacial carrier transport between quantum dots and colour-tuneable OLEDs, we have now demonstrated this new full-colour upconverter.”

The latest work is detailed in Science Advances.

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The European Space Agency (ESA) is globally recognized for its iconic space missions that push the boundaries of science and technology, whether it’s a rendezvous with a comet, landing a probe on Saturn’s giant moon Titan or mapping the stars of the Milky Way in unprecedented detail. But ESA does so much more than these headline-grabbing scientific and exploratory endeavours.

“Space is no longer solely a playground for curious minds,” says Eric Wille, ESA Head of the Opto-Electronics Section. “It’s really important for our everyday life too.” In fact, modern society relies on space technologies.

Satellite-based environmental monitoring, weather forecasting and global navigation are obvious examples, but there are many other important applications. For instance, the global financial system could not function without atomic clocks aboard satellites time-stamping millions of stock trades and digital payments every second. Similarly, when natural disasters strike, satellite networks become essential lifelines: mapping floods, tracking wildfires and helping with the co-ordination of emergency response efforts on the ground.

Fulfilling all of these roles and ESA’s bold space ambitions – from seeking answers to big questions about the universe to watching over our precious planet – requires a highly dedicated, technically proficient and multi-skilled workforce made up of scientists, engineers and various other professionals.

Diverse and challenging work

When Wille joined ESA as an optical systems engineer in 2009 after completing his PhD in experimental quantum optics, it was the sheer diversity of challenging work that attracted him. “Working in an international space agency, you’re partly a researcher, partly a project manager, partly also someone with ambassadorial skills,” he says. “That mixture is really something which I found at that time very attractive and I still like today, very much.”

Charlotte Pachot also craved a technically challenging role after her master in optics. She found it at Thales Alenia Space in France as a space engineer working on optical instruments. But after a few years, her interactions with ESA staff through joint projects convinced her to join the Agency as an optical engineer. She is now Lead Payload Engineer for the Laser Interferometer Space Antenna (LISA) mission, intended for launch in 2035, which will be the first gravitational wave detector in space.

Both Wille and Pachot have found that the technically challenging work at ESA is particularly satisfying because it has real-world impact. The first 10 years of Wille’s ESA career were largely spent on Athena (Advanced Telescope for High ENergy Astrophysics; now renamed NewAthena), a powerful X-ray observatory set to launch in the late 2030s that will provide fresh eyes on a wide range of hot and energetic processes in the universe.

In this role, Wille and the ESA team collaborated with an industrial consortium led by Dutch measuring instrument supplier cosine to develop a completely new type of optics, called silicon pore optics. Using techniques perfected by the semiconductor industry, cosine bonded and stacked many silicon plates on top of each other. By shaping the plates, a lightweight mirror to focus X-rays was created; in fact, 10 times lighter than the ones flying on current X-ray missions XMM-Newton and the Chandra X-ray Observatory.

Like Athena, LISA will also provide fresh eyes on cosmic events, but through the unique prism of gravitational waves. This will be achieved through a completely new approach involving a triangle of three satellites spaced 2.5 million kilometres apart.

Understandably, LISA calls for a unique optical bench, which Pachot is managing from design to manufacturing and testing. She sees her role as being like that of a conductor of an orchestra: a lot of her time is spent co-ordinating team members and partners, while also helping to solve technical, budget and schedule problems. For Pachot, tackling these daily friction points is part and parcel of working on real-world big science. “The instruments are very complex technically, very challenging, but they are also real pieces of hardware as part of a real project,” she says.

International community

As Wille and Pachot’s stories show, ESA selects talent from different career stages.  The Agency offers several programmes that support students, graduates and experienced professionals in finding the right role for their profile and interests.

For example, university students can benefit from ESA Academy sponsorship, such as participating in hands-on projects or training sessions. They can also join ESA as interns. Graduates can apply to ESA’s Graduate Trainee Programmes where they can gain experience on actual ESA projects and develop technical and professional skills. And for those currently in industry with less than three years’ experience, the Junior Professional Programme allows them to join ESA as staff members for four years and benefit from tailored learning and development opportunities to prepare them for a long-term position.

Whichever pathway they take, once new recruits get started in their first role, an excellent employment package – including competitive salary and pension scheme, hybrid working and flexible hours, and professional development training opportunities – comes as standard.

What sets ESA apart is the multicultural work environment. Team members might come from any of ESA’s 23 Member States and nine further Cooperating States and Associate Members.  And recruits can be based in more than nine locations in seven countries (France, Germany, the Netherlands, Italy, Belgium, Spain and the UK). This makes for a melting pot of cultures.

“There’s a very lively expat community,” says Wille. “At the European Space Research and Technology Centre (ESTEC) and other big sites, it’s like a small Europe.”  This cultural diversity is of course intentional. “The problems we have to solve require teamwork,” says Pachot. “And this is made easier at ESA because we all see problems in a different way depending on our culture.”

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Modern computation ranks among the great technical achievements of the 20th and 21st centuries and touches nearly every area of human activity. Today digital computing uses billions of transistors etched onto semiconducting silicon chips to work as tiny switches that represent binary 0 or 1. The technology underlies personal phones and laptop computers, and extends to supercomputers that perform nearly one quintillion operations per second (10¹⁸ floating point operations per second, or FLOPS) and manipulate up to 100 petabytes of data.

Supercomputers can simulate otherwise intractable problems in science, from climate and weather patterns to protein folding and even black-hole interactions. However, further progress in scientific and general computation is approaching saturation because of fundamental limits, while the explosion in artificial intelligence (AI) based on large language models (LLMs) is clearly showing where computation needs to be improved. Physics is essential for this effort.

Nearing the physical limits

Back in 1965, Intel co-founder Gordon Moore famously predicted that the number of transistors we could fit onto a silicon chip would increase exponentially. He later forecasted that the number would double roughly every two years. Moore’s law has held for decades, albeit at a lower rate since the mid-2010s. More transistors meant increased computing power per chip, as well as faster computing.

That’s because smaller transistors switched between binary states more quickly, and higher transistor densities reduced the distance signals had to travel. These factors made it possible to increase “clock speed” – the frequency at which a computer’s central processing unit (CPU) synchronizes its internal operations – which helps determine computational speed. That frequency grew from tens to hundreds of megahertz in the 1970s–1990s until it reached gigahertz levels.

But by the early 2000s, the increase in clock speed with density of transistors no longer held. Transistors that switched more frequently used more power, generating heat beyond what could easily be dissipated. Essentially, clock frequencies have stagnated at 3–5 GHz.

Within this limitation, the strategy for faster computing has been to design chips for parallel processing. Modern CPUs contain “cores”, which are separate processing units on a chip that independently read and execute instructions. In a CPU with four cores, each operates at the clock rate of 5 GHz, say; but since they operate in parallel, the throughput can approach a fourfold increase.

Another, more specialized form of parallel processing was introduced in graphics processing units (GPUs). While a CPU typically has between four and 32 powerful cores that have been optimized for flexibility in carrying out different tasks, a GPU has hundreds to thousands of simpler cores, designed to deal with many data elements for such tasks as rendering images or multiplying large matrices.

GPUs have become essential for supercomputers, but they also face limits. Trouble is, not all computational tasks can be broken into parallel operations, while adding more transistors to a chip still requires more power and generates yet more heat.

Large scales and rising costs

Supercomputer-level capabilities, however, are needed to support the rising use of LLMs such as ChatGPT, which are trained on huge data-sets and can create content based on natural language. Other LLMs followed, and by 2025 up to a billion individuals, corporations and governments were using AIs globally. This enormous scale of usage is highly demanding of computational and electrical power.

LLMs need two kinds of computation. First there is training computation, which analyses massive amounts of text from books, articles and websites containing trillions of tokens – words or parts of words. The training’s aim is for the model to learn statistical patterns in a given language, and estimate the probabilities for the next token in a given sequence.

Training the largest LLMs can take up to 100,000 GPUs using tens to hundreds of megawatts, comparable to the biggest supercomputers. A few dozen of these centralized installations are estimated to be operating around the world, concentrated in the US and China.

The second type of computation is inference, where an already trained model responds to user prompts. Inference processing needs less computational and electrical power, but runs continuously to serve users. It must also respond with little latency, the time delay between request and response, so inference infrastructure is geographically distributed, not centralized.

Of about 12,000 general data centres operating globally, hundreds to a few thousand now support a large AI cluster for inference, with the number rapidly growing. With this scale of continuous operation, inference is expected to dominate long-term AI energy use.

By 2030, global data centres, driven largely by AI, are expected to consume some 1000 TWh per year, corresponding to an average load of roughly 100 GW. This is a few percent of global electricity use and the resulting waste heat must be removed, requiring millions of gallons of water for some facilities. This heat discharge, along with the necessary additional electricity generation, will have a significant impact on the environment.

That’s provoked reactions to AI infrastructure, both from communities objecting to local data centres and governments concerned about national power grids. Scaling today’s relatively few specialized supercomputers to many large AI centres around the world carries significant costs, not to mention AI’s uncertain societal impact. As AI stretches resources, researchers are keen to rethink the very nature of computation.

Building a better bit

The use of electronic circuits to carry out binary logic, which defines modern computation, was mathematically formalized by the US mathematician Claude Shannon. In 1937 he showed that on/off electrical switches, arranged in what we now call a “logic gate” (based on the true/false logic George Boole invented in the 19th century), can carry out arithmetic as well as logical decision-making.

This approach has been embodied in computers, first using electromechanical relays, then vacuum tubes, followed by discrete transistors, and finally CMOS (complementary metal-oxide-semiconductors) integrated circuits. Each succeeding generation has slashed the energy required for a single binary switching event – for example, from nanojoules for an older discrete transistor to femtojoules for a transistor in a modern CMOS chip.

But this gain has been far outstripped by the rapidly growing volume of computation. Despite improved energy efficiency, our increasingly computerized world demands more electrical energy. Fortunately, there are other, more efficient ways to encode binary information using physical systems that support two stable states: the horizontal or vertical polarization of a photon; the up or down orientation of the spin magnetic moment of an electron; or persistent superconducting currents circulating in opposite directions.

Each approach has its own advantages and drawbacks. Photon-based computing offers high speed and reduced resistive heating; but it is difficult to store photons. Superconducting currents offer high speed, and require low energy per operation. But the energy cost for cryogenic cooling at 4 kelvin, hundreds of watts per one watt of heat removed, diminishes or wipes out the energy advantage.

“Spintronics” technology, however, has been the most successful of the three. Its basic device is the magnetic tunnel junction (MTJ), where a thin insulating barrier separates a “reference” and a “free” magnetic layer. The device’s electrical resistance depends on whether the magnetizations of the layers are parallel or antiparallel.

MTJs exist in hard disk drives and can also serve as read-write units in a magnetoresistive random-access memory (MRAM). To read, a small current is passed through the MTJ, and the resulting voltage shows the state of the bit. To write, a larger current is applied. The fixed layer polarizes the spin of the electrons, which carry angular momentum as they tunnel into the free layer.

This flips that layer’s magnetization, switching the magnetic bit, whose state survives even without power. That’s a key advantage of MRAMs compared to volatile CMOS RAMs, which require power and lose their stored data without it. MRAMs are not yet competitive with CMOS RAMs, but are already used in automotive, aerospace and other applications where their non-volatile nature is essential to reduce power needs and maintain their data under extreme conditions.

Along with this benefit, new possibilities for spintronics are emerging. In 2024 Nuh Gedik at the Massachussetts Institute of Technology (MIT) and colleagues reported that they had rapidly induced magnetism in iron phosphorus trisulfide with light (Nature 636 609). FePS₃ is an antiferromagnet where atomic spins in opposite directions result in little or no net magnetic field. The researchers found that picosecond pulses of terahertz light produced magnetic states that persisted for milliseconds – far longer than any other reported light-induced magnetism (see box below).

Metastable magnetization

Shown here is the experimental set-up that an international team of physicists use to produce a long-lasting, light-driven magnetic state in a material such as iron phosphorus trisulfide (FePS₃), which becomes antiferromagnetic when cooled below about 118 K. They used an intense terahertz-frequency (THz) pulse (orange) to drive low-energy collective excitations, which induce transient changes in optical properties that can be probed with an 800 nm probe pulse (red). Fe²⁺ ions form a hexagonal lattice and their spins arrange ferromagnetically along the zig-zag chain (a-axis) and antiferromagnetically between the adjacent chains (the structure in the circle). The magnetic coupling between the layers is antiferromagnetic together with a small interlayer shear distortion along the a-axis. The THz pulses put the material in a metastable magnetic state that lasts for more than 2.5 milliseconds even after the light source is switched off.

Earlier this year, researchers at Beijing Normal University in China found that light-induced magnetic transitions consume little energy (ACS Nano 20 9051). If magnetic bits become competitive with electrical ones – activated by light or otherwise – they would unite working memory and long-term storage in one computational stage rather than two as we now have. Magnetic bits could also play a role in a bigger change in computer structure. 

Bringing it all together

A novel form of computer architecture could also remove a famous bottleneck in computing that dates back to the influential 1945 proposal by the mathematician John von Neumann for a general computational design. He suggested using separate processing and memory (first put forth in 1837 by Charles Babbage for his mechanical “Analytical Engine”) but added the idea of the stored program.

By holding the instructions for computer operations in memory along with data, a computer program makes computation more flexible but has one big drawback. Data and instructions have to shuttle between processor and memory along the same channel, reducing computing throughput and using more energy than processing – the “von Neumann bottleneck”.

Novel computing: liquids, soft solids and deuterium

At the heart of modern computing technology are ultra-pure silicon wafers. These nearly perfect regular crystalline solids form the substrates for integrated circuits, making it all the more surprising that less ordered materials – such as liquids and soft solids – have their own history in computation.

In 1949, for example, the UK-built Monetary National Income Analogue Computer (MONIAC) simulated the flow of money within a national economy using coloured water moving through transparent tubes under gravity. Water levels representing economic conditions were set by pumps and valves. As the water negotiated the system, it dynamically illustrated how parameters such as tax rate affect an entire economy, eventually settling into equilibrium.

Another liquid – mercury – also appeared in the early days of electronic computing. The first commercial unit in the US, UNIVAC I (1951), stored nine kilobytes of data as sound pulses continually recirculating in tubes filled with liquid mercury acting as delay lines. The units, which were bulky and heavy, provided serial rather than random access because the pulses travelled in sequence. Timing was crucial, and the mercury was held at a constant 40 °C to keep the speed of sound stable. Another early computer, EDVAC, also stored data in liquid mercury.

Since the 2000s researchers have shown that tiny droplets of oil, moving through small channels filled with water, can implement binary logic. If a droplet blocks a channel, a second droplet arriving behind it is diverted into another channel, representing a “decision”. Proper design can emulate the Boolean logic that underlies conventional computing. With channels only 100–200 µm across, microfluidic logic could route and process small samples, providing a lab on a chip for chemical analysis, biological research or medical diagnostics.

Yet another liquid – one more exotic than mercury – and a soft solid were apparently at least considered for computation in the same era as UNIVAC 1. According to Iain Dey and Douglas Buck’s 2017 biography The Cryotron Files: the Strange Death of a Pioneering Cold War Computer Scientist, the MIT scientist Dudley Buck once worked on a data storage system using magnetic pulses in liquid deuterium held at cryogenic temperature. In that Cold War era, US government money was available for any research that might help America and the authors describe how some of it also went on studies into a soft, wobbly foodstuff, lemon Jell-O as well as the viscous semi-liquid hair preparation Wildroot Creme Oil, which might also support sound waves in a memory unit. None of this Cold War research panned out, although at least the Jell-O experiments could treat the entire lab team to dessert.

One solution is to carry out processing and memory functions in the same physical element, potentially using a new type of electric circuit element originally proposed in 1971 by the US electrical engineer and computer scientist Leon Chua. Its resistance depends on the accumulated charge and, since charge is the time integral of current, therefore carries a memory of the device’s past electrical activity.

Chua dubbed his new element a memory resistor or “memristor” – and the concept can be used when a read-write MTJ holds a memory of past electrical activity as a magnetic bit. In 2026 Shahar Kvatinsky at the Israel Institute of Technology and colleagues showed that small MRAMs formed from MTJs can perform logical operations inside memory (Adv. Electron. Mater. 12 e00348).

In principle, therefore, this could also provide arithmetic processing inside memory, thereby removing the von Neumann bottleneck. The non-volatile memory would also save energy relative to CMOS memory. Problems remain though, such as reducing noise and producing large-scale MRAMs – but the ability to merge memory and computation within MRAMs has been established at small scales.

Certain material structures can also play a dual function. The wonder-material graphene – a 2D hexagonal lattice of carbon atoms – is electrically conductive when a voltage is applied in its plane, driving the electrons. If the graphene sheet is also placed between proton-conducting electrolytes, a second voltage applied across the sandwich produces a proton current (a flow of positive charge) perpendicular to the plane.

In 2024 Marcelo Lozada-Hidalgo at the University of Manchester and colleagues found that certain values of electron density in this structure make the graphene an insulator (Nature 630 619), producing a reversible change from conducting to insulating that forms a non-volatile two-state memory. Their set-up allowed the researchers to perform logic and memory operations in a single device for the first time.

As graphene, MRAMs, and other approaches are under study for in-memory computing, another method emulates a natural process – and is perhaps the biggest departure from conventional computing.

Dual purpose

(a) Graphene is well known to be a good electrical conductor, but in 2024 an international team of researchers used the 2D substance to make a new electrically-controlled switching device that supports both memory and logic functions. The device exploits graphene’s ability to conduct protons as well as electrons. The team showed that placing a sheet of it between proton-conducting electrolytes also produces a proton current perpendicular to the plane, with the proton and electron transport allowing independent control of field and charge density. Shown here are the top and bottom voltages and the direction of electron and proton flow. (b) Map of in-plane electronic conductance, σ_e, as a function of electric field E and charge density n. The left and bottom axes show that these variables are controlled by the difference and sum of the top and bottom electron voltages, respectively). (c) Map of proton transport current, I, as a function of E and n.

Copying biology

In the 1980s, Carver Mead – a Caltech physicist and engineer who had been instrumental in developing integrated circuits and deeply understood the physics of computing – made a radical proposal. Instead of building computers around centralized digital logic, we should instead design them to imitate the strategies that make the human brain highly efficient. He coined the term “neuromorphic” computing for this approach and is widely considered its founder.

Using specific biological and biophysical features, the brain performs its cognitive and sensory tasks at the modest power of 20 watts. Its 86 billion neurons do not constantly use energy, but act sparsely in response to events, firing brief electrical spikes at definite timings and rates. A system like this can be expected to save energy compared to a conventional computer, which steadily consumes energy at the CPU clock rate.

Also, there is no von Neumann bottleneck in the brain. Information is stored as changes in synapses: the ~10¹⁴–10¹⁵ connections among neurons that control signal flow. As a spike arrives, a synapse immediately applies its stored information. The modified signal is passed on to neurons that repeat the cycle. Storage and processing occur together within this closely linked 3D network, which also operates in a massively parallel manner.

Mead had envisioned an analogue neuromorphic design, but in practice the biological features are expressed digitally to match CMOS technology. For example, in 2017 Intel introduced its Loihi chip with event-driven spiking and closely connected computation and memory. A later model was reported in 2025 (arXiv:2503.18002) that trebled the throughput for matrix multiplication – the main computationally-intensive operation needed to train an LLM – with half the energy a standard GPU chip uses.

Similarly, in 2014 IBM built and tested a chip that emulated spiking behaviour, while a later version, dubbed NorthPole, does not use spiking. In 2025, meanwhile, IBM researchers reported that 288 linked NorthPole chips could carry out AI inference on certain sizes of language models at favourable speeds and power usage.

The future of computing and AI

Most of the novel approaches are in the proof-of-principle or pre-commercial phase and may never reach wide use, for both economic and engineering reasons. The investment in CMOS technology and the associated computer architecture is enormous. Any overall change would be a massive undertaking. Although a neuromorphic chip might be more efficient, it would require huge investment to be formally adopted by today’s markets and chip-making industry.

Even so, there are valuable lessons to be learned from the research into novel approaches – such as better integration of memory and computation. There is also a consensus that hybrid solutions can yield immediate benefits. An accelerator unit, such as a bank of neuromorphic chips, integrated with CMOS technology, could increase speed and decrease power use for the critical matrix multiplication stage. Upgrades like these can be included as new supercomputers and AI centres are being built, improving general and AI computation and reducing their energy costs.

We should also think of the problem from the other end: yes, we can now produce a form of AI based on LLMs. But this is ultimately a brute-force approach that demands a great deal of time, money and resources. It should continue to be refined, but there should also be space for bold ideas that may lead to better and more sustainable forms of AI, and of the computation it requires.

The post The physics of novel computation: beyond bits and chips to spikes and spins appeared first on Physics World.

How many times have you wanted to throttle a journalist? Do you ever get incensed about articles, podcasts or videos that simplify, dumb down or belittle your research? Don’t you ever want to teach a science writer the basics?

Earlier this summer the US quantum physicist Christopher Fuchs got the chance. Thanks to some funding at the end of a grant cycle, Fuchs arranged a face-off between science journalists and writers, and a philosopher (me) at Royal Holloway, University of London. But the meeting wasn’t all about Fuchs having a big fat moan; he also gave the journalists the chance to push back.

Fuchs, who is from the University of Massachusetts, Boston, is the principal expositor of QBism, originally an acronym for “Quantum Bayesianism”, a research programme devoted to trying to figure out what the world must be like if quantum formalism is correct. But even top-flight writers, Fuchs thinks, get it wrong. And so emerged his idea for the workshop, called “Communicating QBism”.

Attendees at the workshop, besides Fuchs himself, included his collaborator Rüdiger Schack from Royal Holloway – the gracious host of the meeting. There was also John DeBrota, who’s a postdoc at Ludwig Maximilian University, Munich, and Matthew Liefer, associate professor at the Institute for Quantum Studies at Chapman University, California.

The science writers were all experienced. One was Philip Ball, the author of some 30 books who has a PhD in physics and contributes regularly to Physics World. Jo Marchant, the sole female writer to attend, has a PhD in genetics and medical microbiology and is a New York Times bestselling author who recently wrote for New Scientist on QBism.

The four other writers were Robert Henderson, who has a PhD in quantum field theory; George Musser, who has a PhD in planetary science and is a contributing editor at Scientific American; Ulf von Rauchhaupt, a science editor at the Frankfurter Allgemeine Zeitung who has a PhD in extraterrestrial physics; and Zack Savitsky, a physics correspondent for Science.

I was invited at the last minute as a philosopher and writer who might find value in the event. I did.

Pugnacious and self-deprecating

Royal Holloway’s wooded campus on the western outskirts of London is dominated by the Founder’s Building, a beautifully ornate late-19th-century red-brick castle-like structure modelled on a French chateau with a central courtyard. But that’s only where we ate. Fuchs’s face-off, which took place on June 18–19, was holed in a modest modern science building down the hill.

Fuchs, whom I’ve met and written about several times, including for Physics World and a philosophy journal, is charmingly pugnacious. He approaches talks and conversations with unwavering zest and easily out-talks critics. He is relentless in pointing out even years-old mistakes to journalists and writers [editor’s note: I can confirm this]. Yet Fuchs can also be endearingly self-deprecating.

If you didn’t know Fuchs, you might be forgiven for thinking that he had an inquisition in mind. “I explain the ideas until I’m blue in the face,” the invitation ran, but you journalists are “pretty deficit in getting QBism right”. He continued, “What is it that makes QBism so damned hard to understand for journalists and the lay public?”

Fuchs then described himself as “communication impaired” – which was disingenuous. Based on Shack’s estimate, he’s sent about 150,000 QBism-related e-mails, he’s got “3 Million Miler” status from American Airlines thanks to his trips to give talks, and he was a lead speaker at the Helgoland conference on the centenary of quantum mechanics last year.

Some invitees were cautious, even sceptical. “QBism isn’t just another quantum physics interpretation”, Marchant replied to Fuchs’s invitation. “You’re challenging ideas of what physics is even about and requiring a radically different conception of what nature is”. Ball, meanwhile, perceptively reminded Fuchs that QBism is so novel that “the misrepresentations don’t just come from journalists”.

As for Musser, he warned Fuchs that the encounter may not be pleasant. “We will need to have free, open and frank discussions”, he responded, that may be “infuriating to you”. He counselled Fuchs to bring “plenty of plushy toys” for participants to safely throw at each other.

Fuchs’s invitation, however, also expressed warm and genuine respect for the coterie of science writers, who all agreed to come. Still, Fuchs brought a box of plushies just in case.

Speaking about science

On the meeting’s first day, the writers listened and learned. Schack opened the workshop by going over QBism’s vocabulary. “Probability” is not a property of things but refers to the expectations that an experimentalist has about outcomes of an action they are about to take. “Measurement” is that outcome.

“Quantum formalism”, meanwhile, is a tool that any experimentalist can use for making the best estimate they can about which outcome they will get. “Quantum states” are not properties of the world but compendia of probabilities to inform the agent about which actions they ought to take to achieve their goals.

After Schack, Fuchs gave a talk showing that QBism is neither a philosophical add-on to quantum theory nor something motivated by an attempt to resolve issues to do with entanglement, Bell inequality violations, and so on. Rather, QBism is the only satisfactory coherent account of what the world must be like if the quantum formalism is correct.

Fuchs quashed the idea that QBism is solipsistic; quantum formalisms, he pointed out, have been hammered out for a century and can be picked up by anyone as the best guide to their laboratory experience. He vented ire over stories that use the word “observe” and visual images to characterize what experimentalists do as if they were flies on the wall rather than actors in measurement events.

When Fuchs complained about a clause in an article by Savitsky which suggested such an interpretation, the writers cried “Foul!”. They accused Fuchs of “niggling” about a few words in a lengthy 4000-word article. When Fuchs replied, “I want to niggle over words!” he dodged a plushie.

Learning about writing

On the second day of the meeting, it was the scientists’ turn to listen and learn. Henderson talked about his struggle to “think like a QBist”, explaining how, during the Covid-19 pandemic, he joined Fuchs’s weekly Zoom sessions known as “QBukis”. These made him feel like he had come across “a more advanced civilization of aliens maybe, to whom premises I’d never thought to question were deemed antiquated and naïve”.

Henderson had an epiphany one day when he saw a bird hopping across his snow-covered lawn. The bird, he realized, was not a thing-in-itself but “the designation of a bundle of expectations” that he was bringing to bear to recognize it. What’s most challenging in learning to think like a QBist, Henderson concluded, is that QBism is “playing a different game than the rest of physics, or even science”.

Marchant followed with a talk entitled “Why QBism keeps getting misheard”, in which she showed a picture of a tennis player about to smash a rocketing tennis ball. What was happening, she said, wasn’t just body movements and ball trajectories – but a process of unfolding and continually updated predictions of actions.

QBism sees experimentalists like that tennis player, Marchant said, shepherding new events into the world, but it’s unintuitive to think that way. “QBism isn’t just another quantum physics interpretation,” Marchant said; “you’re challenging ideas of what physics is even about and requiring a radically different conception of what nature is and how we are related to it”. This, she concluded “is always going to be difficult”.

Ball pointed out that journalists are forced to keep in mind “mental attractors” that entice the public, journalists and even scientists to think in classical rather than quantum terms.

Between talks, the writers cited other constraints, such as time, money, audience and the space allotted by editors, all of which shape and dictate their output. Furthermore, writers are sometimes forced to use words whose meanings vary from their technical use.

At one point Fuchs showed a slide of Marchant’s New Scientist article and complained about the word “perspectives” in the standfirst. But Marchant and others objected that Fuchs’s “Gotcha!” play was again committing a foul; writers must lead readers gently into difficult stories with prose that sometimes must violate what researchers mean. “We have to write so people keep listening,” Marchant pointed out.

Impressed, Fuchs had to admit that he does something similar in his lectures, not leading with his most radical ideas but holding off until later.

One scientist then asked why writers don’t routinely run stories by sources before publication. Even if you accurately regurgitate the sources’ words, the writers replied, they often insist on changes, demand that their editors alter or retract the story, heap abuse on you, or even threaten to sue, causing the magazine to drop your article.

When a writer asked why scientists should even care about representations of their work in the media, the answers were difficult to synthesize. They ranged from the noble wish to nurture a scientifically literate public to the self-interested hope that good coverage might influence public perceptions and thus lead to more money from funding agencies.

But what’s hardest writing about QBism, explained the writers, has to do with Henderson’s “civilization of aliens” and Marchant’s “keep ‘em listening” points. Readers instinctively think, contra QBism, that the world has permanent residents and chiselled-in laws. The tennis player’s dive for the ball can always be reconstructed afterwards from a god’s-eye perspective in terms of classical physics, and it’s second-nature for both the public and even scientists to assume that the end of physics is to make such reconstructions.

The critical point

Years ago I wrote a column “The press is a foreign country” whose message was that communicating science is like engaging with another culture. Science and the media, I wrote, are separate institutions with different values, traditions and methods and reasons for seeking and justifying knowledge. The cross-cultural interaction, though, cannot always be made trouble-free, with all conflicts reconcilable by facilitators or relationship counsellors.

Given the qualifications of the participants at “Communicating QBism” – all but Zack had PhDs – one might have thought that the cross-cultural interaction at the workshop would be relaxed. It was, for the most part. But good scientific communication, it emerged, is not always a matter of clear explanations, demonstrations of relevance, dazzling imagery, or scientifically literate journalists.

Positive interactions may require constantly negotiating trade-offs between accuracy and comprehensibility, as well as setting up flinty encounters in which both scientists and writers actively hunt down and expose their own assumptions. These encounters must risk conflict and discomfort on both sides. Good science communication, in short, can use some genial pugilism, and Fuchs’s workshop was an excellent example.

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By analysing the signals from extragalactic fast radio bursts, astronomers at the Massachusetts Institute of Technology (MIT) say that the “missing matter” in the universe is distributed further away from galaxies than most theoretical simulations predict. Their finding – which is counterintuitive since the gravity from galaxies tends to pull everything closer to them – could help us better understand how highly energetic galactic activities, such as jets from supermassive black holes and explosions from old dying stars, impact the formation of cosmological structures.

“Ordinary” matter, which is built from atoms and their protons and neutrons (collectively known as baryons), makes up stars and galaxies and everything we see around us. However, the best models of the universe we have today suggest that close to 90% of this baryonic matter is “missing”.

The radio signals of FRBs are stretched

As their name implies, fast radio bursts (FRBs) are brief, intense bursts of radio waves spanning multiple wavelengths. They were first detected in 2007 and since then, astronomers have spotted thousands of others, including some within our own galaxy. They are thought to originate from cataclysmic processes involving compact celestial objects such as neutron stars and typically last a few milliseconds or even less. And these FRBs can be used to probe the missing baryonic matter.

As they pass through the missing matter, the radio signals of FRBs are stretched (or “dispersed”) over time – that is, their overall duration becomes longer. The more missing matter they pass through, the more the signals are dispersed. The missing matter has an extremely low density – of just a single proton per cubic metre – so it is extremely difficult to identify, but researchers recently found that they could use the dispersion effect to detect it. In that previous study, they confirmed that intergalactic space, which contains most of the universe’s baryons, is home to tenuous clouds or filaments of diffuse plasma that make up the missing matter.

Data from CHIME and DESI

In the new work, a team led by astrophysicists Haochen Wang and Kiyoshi Masui has now gone a step further and mapped the extent to which this plasma extends. They did this by cross correlating the locations of millions of galaxies with the dispersion of nearly 3000 background FRBs on length scales of 0.1 to 50 Mpc.

The researchers used data from the Canadian Hydrogen Intensity Mapping Experiment (CHIME) catalogue and the Dark Energy Spectroscopic Instrument (DESI) survey. CHIME, a large radio telescope located in British Columbia, scans the entire northern sky for incoming radio waves and it can detect ultrashort, ultrabright radio signals. Indeed, it has detected about 4000 FRBs since it became operational. DESI, for its part, is an instrument mounted on the Mayall Telescope at Kitt Peak National Observatory, near Tucson, Arizona. It makes detailed measurements of the light coming from over 30 million galaxies – originally to provide estimates of dark energy, the mysterious force that is driving our universe’s expansion.

In all, the researchers detected 2870 FRB signals with CHIME and correlated these with the locations of around six million galaxies with DESI.

Missing baryonic matter scattered across a large radius

Their analyses revealed that on scales smaller than about 1 Mpc, the missing baryonic matter was indeed found around galaxies and galaxy clusters, but rather than being close to galaxies in a dense ball as expected, it was scattered across a large radius. “A galaxy is maybe a few 100,000 light years across, and we found missing matter out to about four million light years,” Masui says. “That’s further than the simulations predict.”

The new result backs up the idea that missing matter is projected out from a galaxy through highly energetic events, such as jets from supermassive black holes and explosions from old dying stars. These processes could be much more energetic than we think, note Wang and Masui, and they are stronger and much more violent.

The work, which is detailed in Physical Review Letters, proves that FRBs are a good way to study large-scale structures in the universe – in a similar way to how cosmologists have been using galaxies and the cosmic microwave background for decades, says Wang. “It has helped to establish FRBs as a new cosmological probe, especially for detecting the missing matter.”

FRBs will only become a more popular tool in this context, he adds, especially given that several new radio telescopes, with upcoming surveys such as CHORD, DSA-2000 and the SKA, are being constructed around the world to offer much better FRB data in the coming years. “Indeed, we have already received more FRB data from our telescopes and are working on expanding our study,” Wang tells Physics World.

And that is not all: the researchers say they are also busy improving their analysis technique. “Until now, we have mostly examined the dispersion of FRBs but we are now working on extracting information from FRBs’ spatial positions relative to galaxies. This will reveal more details on how the missing matter is distributed in the universe.”

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Exceptional points occur in open physical systems where two or more resonances merge so completely that both their measured values and their underlying states become identical. (Technically speaking, the eigenvalues and the eigenvectors coalesce.) Exceptional points are different from ordinary degeneracies, where two frequencies may be the same but the corresponding states remain separate.

Near an exceptional point, a tiny change in the system can produce a relatively large change in the resonances. That is why exceptional points have been proposed for sensitive devices such as optical sensors. But there is a catch: a large response is not automatically useful if quantum noise also increases at the same time.

In a new paper, researchers Jan Wiersig and Stefan Rotter tackled this problem using quantum Fisher information. This is a quantity that sets the best possible precision of a measurement under ideal conditions.

Their approach treats the sensor as a scattering device, where incoming coherent light is transformed into outgoing light, and asks how much information about a small perturbation can be extracted from that change.

The results are, unsurprisingly, complicated – but that complexity turns out to be revealing.

For several years, different groups have reached seemingly contradictory conclusions about whether exceptional points actually improve sensing at the quantum limit, with some studies reporting a clear advantage and others finding none. Wiersig and Rotter’s analysis helps explain these disagreements: the answer depends on the physical assumptions and, in particular, on how the input light, losses and perturbation are matched to the resonant modes.

The analysis therefore does not yield a simple yes-or-no verdict. Under suitably matched conditions, exceptional points can provide substantially more quantum Fisher information. For example, a factor-of-four enhancement for a second-order exceptional point in a two-microring system, and an even larger enhancement in the third-order case.

What’s more, the optimum operating point need not be the exceptional point itself. Moving slightly away from it can produce linewidth splitting, creating a longer-lived mode that interacts more strongly with the perturbation and thereby increases the useful signal.

The take-home message is that exceptional points are not magic sensitivity boosters. They can provide an advantage when the light field, perturbation and resonant mode are well matched. Internal losses may weaken or remove this advantage, although small losses do not destroy the overall picture.

Future exceptional-point sensors will therefore need to be designed as complete measurement systems, rather than around the exceptional point alone.

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Remote uncrewed aerial vehicles (UAVs), or drones, equipped with solar cells could be wirelessly charged using laser beams directed at them from the ground, rather than relying on traditional onboard batteries. The problem until now, however, has been keeping the drones cool – since laser light heats them up, so reducing the efficiency of the photovoltaic cells they carry on their wings. A team of researchers at the Civil Aviation University of China has now overcome this problem by incorporating a heat blocking technology based on antimony selenide (Sb₂Se₃) nanorods into these solar cells.

As drones take on longer missions, battery life has become one of the biggest barriers, explains Jianhua Han, who led this new research study. “Our team has been looking into laser wireless power transmission, which is a leading approach for long-distance wireless energy transfer, to replace these batteries.”

Laser wireless power transmission is particularly suited to aerospace applications such as UAVs equipped with photovoltaic cells. Perovskite solar cells show much promise in this context because they are cheap to manufacture, absorb light strongly in the visible part of the electromagnetic spectrum and have long charge-carrier diffusion lengths.

A perovskite laser cell-thermoelectric tandem device

In the new work, detailed in Matter & Light, Han and colleagues studied a type of solar cell known as a perovskite laser cell-thermoelectric (PLC-TE) tandem device, which consists of a carbon-based CsPbBr₃ perovskite as the PLC and bismuth telluride (Bi₂Te₃) as the TE material. The TE module is directly fixed beneath the laser cell and a carbon electrode is attached to its negative terminal  to create a series connection. When laser light is shone onto the device, the carbon electrode converts a portion of the incident laser energy into heat. The TE then harvests this heat, converting it into electricity through the thermoelectric effect.

And that’s not all: since one side of the device ends up being warmer than the other, this temperature gradient also helps convert the thermal energy into electricity. The larger the temperature gradient, the more electricity the TE layer can generate.

There is a problem though: while the carbon in the hybrid structure dissipates some of the heat produced by the laser, the structure can still heat up – reaching temperatures of up to 90°C, says Han. “That was much higher than we expected and made us realize that heat buildup was a far more serious problem than we had imagined.”

Sb₂Se₃ behaves like a thermal barrier

To overcome this problem, the researchers turned to Sb₂Se₃, which is a promising photovoltaic material. As well as its good optoelectronic properties, this semiconductor also has a low thermal conductivity, which allows it to behave like a thermal barrier when embedded in a device.

Han’s team synthesized nanorods from the Sb₂Se₃ and incorporated them into the upper portion of the CsPbBr₃ layer. The Sb₂Se₃ reduces heat dissipation in the carbon electrode and so helps maintain a significant temperature gradient in the TE device, thereby improving its overall energy conversion efficiency. Its thermal barrier properties also help decrease the PLC’s overall operating temperature during prolonged laser exposure.

The team then inserted the tandem device containing the Sb₂Se₃ nanorods beneath the wing of a stationary drone and carved out air channels through the wing to simulate real-world airflow conditions. When illuminated with high-power green laser light with a wavelength of 520 nm, they found that the device converted 38.49% of the incoming laser energy into electricity and successfully powered the drone’s propellor blade. This power conversion efficiency, says Han, is among the highest reported for this class of technology operating under similar conditions.

Device could help UAVs stay airborne for longer

“In terms of concept, this is the first time that a system-level scheme of the devices has been applied to a UAV power supply, expanding the work from pure materials research to application-oriented system design,” Han tells Physics World. “It demonstrates that powering UAVs with light is not just a theoretical concept, but an engineering pathway that can be practically implemented.”

The device could help UAVs stay airborne for longer, something that will be useful for applications like forest patrol, disaster monitoring and delivering packages, he says. But there is still much work to do before such applications become a reality. For one, the researchers will need to integrate the PLC-TE device into a lightweight drone for flight testing outdoors and to assess the safety of their technology. They will also need to find a way of accurately tracking moving drones with laser beams.

“Going from the ground-based proof stage to the real flight validation stage will require solving many engineering challenges,” says Han, “but our technology is a good starting point and verifying its viability is the core objective for the next phase in our study”.

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Building a useful quantum computer is not simply a matter of adding more qubits. The greater challenge is making these qubits reliable enough to perform long computations without errors overwhelming the result. Quantum error correction addresses this problem by encoding each logical qubit across many physical ones, but it comes at a cost: many of the operations required for a general-purpose or “universal” quantum computer become highly resource intensive once fault-tolerant error correction is introduced.

To address this resource challenge, researchers at the University of California, Davis, US have developed a classical simulation method that efficiently models the preparation of some of the most demanding quantum states. The method, which they describe in PRX Quantum, works even for large, high-fidelity protocols that were previously beyond reach.

Building a universal quantum computer

Logical operations in fault-tolerant (that is, error-corrected) quantum computing architectures fall into two broad categories. The first category is a set of operations known as Clifford gates that are relatively straightforward to implement and, importantly, can be simulated efficiently on a classical computer. By themselves, however, Clifford gates are not computationally universal. For that, you also need non-Clifford operations, which lie outside the set of classically-simulable gates and provide the missing ingredient for universal quantum computation.

To realize these non-Clifford operations in a fault-tolerant way, some qubits need to be in a special state known as a magic state. Preparing these magic states with sufficiently high fidelity is expected to dominate the cost of large-scale error-corrected quantum computers, so quantum computing theorists are searching intensively for more efficient preparation protocols. The problem is that this search contains a challenge of its own: how can we compare the efficiency of these approaches?

To assess a magic-state preparation protocol, we need to simulate it under realistic levels of error-inducing circuit-level noise. Yet the same non-Clifford operations that make magic states indispensable for quantum computation also make them difficult to simulate. Existing methods therefore become prohibitively expensive as protocols grow, limiting exact simulations to relatively small logical circuits.

Simplifying a difficult simulation

Rather than searching for a more efficient simulation algorithm directly, the UC Davis team of Samyak Surti, Lucas Daguerre and Isaac Kim first asked a more fundamental question: what mathematical structure do these protocols share?

Their framework for answering this question encompasses three broad classes of logical magic-state preparation protocols: code switching, magic state distillation, and Pauli-square-root Clifford (PSC) measurement-based protocols. In the first two classes, error propagation is relatively straightforward to analyse, but PSC protocols require a more sophisticated mathematical treatment.  Rather than viewing these protocols simply as quantum circuits, Surti, Daguerre and Kim characterized their underlying algebraic structure, showing that Pauli errors (the fundamental types of qubit errors) propagate in a highly constrained and predictable way under sequential commutation. This commutation preserves the algebraic relationships between errors and logical operators, while anti-commuting operations exhibit predictable transformations rather than generating uncontrolled complexity.

These properties mean that commuting operations can be systematically reordered without changing the outcome, allowing much of the circuit’s complexity to be absorbed into its algebraic structure. Hence, rather than tracking an exponentially large quantum state, the simulator follows how a compact description of logical Pauli and Clifford errors evolves through the protocol.

The paper formalizes these ideas through a sequence of lemmas, propositions and theorems that establish the mathematical properties of PSC protocols. The result is a series of algorithms for simulating realistic, noisy, logical magic-state preparation protocols with a computational cost that scales polynomially with both the number of qubits and what is termed the stabilizer rank of the target magic state, which is a measure of its non-Clifford complexity. Since the standard single-qubit magic state has a stabilizer rank of only two, this complexity remains manageable even as the underlying error-correcting code grows, in marked contrast to state vector simulations that scale exponentially with qubit number. The team’s advance therefore makes large-scale logical simulations practical for the first time.

Accelerating fault-tolerant quantum computing

Although the new framework does not reduce the physical resources required to prepare logical magic states, it does change how those protocols can be analysed and designed. By exposing the algebraic structure underlying a broad class of logical magic-state preparation schemes, the UC Davis team transformed a computationally hard problem into one that admits efficient classical simulation. Researchers can therefore evaluate, compare and refine candidate preparation protocols under realistic circuit-level noise without resorting to exponentially expensive simulations or uncontrolled approximations.

“The main motivation behind our work was to speed up the development of fault-tolerant quantum computer,” Kim tells Physics World. “I believe there is a large amount of uncertainty in how we will design and optimize magic state factories, which will likely remain as a bottleneck in the foreseeable future.”

As quantum computing progresses from proof-of-principle demonstrations to large-scale fault-tolerant architectures, the ability to characterize and benchmark logical operations efficiently will become increasingly important. This work offers more than just a faster simulator; instead, it provides a new theoretical foundation for designing one of the most resource-intensive building blocks of future quantum computers. “My hope is that this line of work can help us better design the fault-tolerant quantum computers we will be getting over the next few years,” Kim says.

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The first direct glimpse of vacuum birefringence has been claimed by astronomers who have studied X-ray and radio emissions of a neutron star that is both a magnetar and a pulsar. A central, but unconfirmed prediction of quantum electrodynamics (QED), vacuum birefringence involves the polarization of the quantum vacuum by powerful magnetic fields.

Made by a US-led international team, the observation could lead to the use of magnetars as natural laboratories to study other extreme-field phenomena of the quantum vacuum. However, another group headed by researchers in Italy remains unconvinced that the data constitute a “smoking gun” for vacuum birefringence. They believe that alternative explanations remain viable.

Birefringence occurs when the refractive index of a medium depends on the polarization of the radiation passing through it. When refraction occurs at such a medium, there is an angular separation of the two differently-polarized waves. This occurs with certain crystals such as calcite and lithium niobate, where the anisotropic lattice structure interacts differently with oppositely polarized photons. Birefringence can also arise from the interaction of photons with magnetic fields in plasma.

Virtual pairs

A key prediction of QED – first made in 1935 by Werner Heisenberg and Hans Euler – is that sufficiently strong magnetic fields can make a vacuum birefringent by polarizing the virtual electron–positron pairs that fluctuate in and out of existence. Ninety years on,  however, vacuum birefringence had not been observed because the huge fields required cannot be generated in the laboratory.

“Having a natural lab already existing that could look into some of these effects is something that would be very beneficial,” says astronomer Rachel Stewart of George Washington University in the US. “That’s something people have probably been looking into for decades.”

Stewart and colleagues’ natural lab is a magnetar. These objects comprise a rare subtype of neutron star that have extreme magnetic fields of up to 10¹¹ T. This makes magnetars the most magnetic objects observed in the universe and bright sources of X-rays. Data from NASA’s Imaging X-ray Polarimetry Explorer (IXPE) telescope have shown that this radiation is often polarized.

This is not surprising because the surface of a magnetar is likely to be surrounded by magnetized, birefringent plasma. The plasma’s field, however, should be tangled and variable, so the net polarization imprinted on light emitted into the far field should be relatively small.

Magnetic axis

If the magnetar’s intense magnetic field polarizes the vacuum of empty space, then the birefringence polarization imprinted onto the X-rays should follow the orientation of the magnetic poles into the far field as the magnetar rotates. Disentangling the two effects is difficult, however, because it is not generally possible to ascertain the orientation of the magnetic poles with respect to the direction of our observation.

A very few magnetars, however, are also pulsars that emit narrow beams of radio waves from their magnetic poles. The magnetic and rotational poles of a pulsar are misaligned, which causes the radio beam to sweep around like a lighthouse beam. If Earth happens to be in the path of the beam, we observe radio pulses.

In the new research, Stewart and colleagues observed the magnetar 1E 1547.0−5408, which is unique among observed objects for having persistent, bright radio emission alongside its X-ray emission. They combined observations from two space-based X-ray telescopes – IXPE and the Neutron Star Interior Composition Explorer (NICER) – with radio observations from Australia’s Murriyang telescope.

The radio observations allowed the team to the work out the angle between the magnetar’s magnetic and rotational poles and the angle between the rotational pole and the direction of our observation. This gave them the information needed to disentangle the two birefringence effects.

Large polarization

The researchers found a high degree of polarization in the detected X-rays – up to 80% at photon energies 2–3 keV in energy. They point out that this high degree of polarization is consistent with vacuum birefringence being driven by the magnetar’s powerful field.

The X-ray emission is closely aligned with the radio emission, which the researchers believe is naturally explained by the magnetic poles of the star being closely aligned with the rotational poles – and difficult to reconcile with alternative explanations.

However, another recent paper challenges this interpretation. Roberto Taverna of the University of Padova in Italy, who led the work, says that pairing the radio emission data with the X-ray observations was “very smart”, but he says that “it is not obvious to me whether the two observations – the radio and the X-rays – are compatible or not.” He says that, if the X-ray emission all emerged from one small region such as a hotspot slightly away from the radio polarization axis, the X-ray radiation would be polarized in the absence of vacuum birefringence. As a result he does not believe the observation is a “smoking gun”.

George Younes of NASA’s Goddard Space Flight Center in Maryland – part of the US group –  argues that Taverna and colleagues are “ignoring about 60 years of radio pulsar science…They are hiding behind the fact that magnetars are different from pulsars, so we don’t know exactly where the radio emission comes from and all results are on the table,” he says, “but there are fundamentals that we should not ignore.”

The US-led team is now investigating further to see whether they can find more evidence for vacuum birefringence. Nuclear astrophysicist Hoa Dinh Thi of Rice University in Texas, who led the theoretical effort, is now modelling QED effects of magnetism on radiation in the plasma. “In the far future we also plan to use machine learning in the model so we can explore the different sources together and understand better the properties of neutron stars and magnetars.”

Stewart and colleagues describe their work in Nature. Taverna’s team has published in The Astrophysical Journal. 

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A laser-ranging technique has allowed physicists to measure the frame dragging of the Earth with an uncertainty approaching one part in a thousand, representing the highest precision yet for this parameter. The new result not only provides one of the most stringent confirmations of Einstein’s theory of general relativity in the near-Earth environment to date, it also sets stronger constraints on some alternative theories that have been put forward to explain the unsolved mystery of the universe’s accelerated expansion.

Frame dragging, also known as the dragging of inertial frames, is one of the predictions in Einstein’s theory of general relativity. Here, a massive, rotating object not only curves spacetime, it also drags it around as it rotates. The effect is very large around huge objects like black holes but is much smaller around Earth. It can be detected, however, by monitoring the motion of certain satellites in orbit around our planet.

There is a problem though in measuring the very tiny shift of the orbital plane around the Earth predicted by general relativity because the Earth is not a spherically symmetrical body, explains Ignazio Ciufolini of the Chinese Academy of Sciences, who led this new study. He and his colleagues overcame this difficulty by analysing motion data from the recently launched Laser Relativity Satellite 2 (LARES-2), developed by the Italian Space Agency, and its predecessor LAGEOS.

The combined orbits of these satellites act like a huge gyroscope and their position can be measured via laser ranging: a laser pulse is emitted towards the satellite and reflected back from the retroreflectors covering its surface. “By measuring the time it takes the laser light to come back, we can very precisely determine the position of the satellite,” says Ciufolini.

LARES-2 is a small, spherical satellite with a radius of 0.212 m and it is extremely heavy, weighing in at nearly 295 kg. Its orbit, he notes, is therefore perturbed only by the Earth’s gravitation and to a much lesser extent by non-gravitational effects, such as the push of the photons from the Sun and the Earth.

Removing the influence of Earth’s lunisolar tides

One of the difficult steps in the measurements, Ciufolini explains, was removing the influence of Earth’s lunisolar tides. These are the subtle distortions in the Earth’s gravity field caused by the tides raised by the Moon and Sun, which would otherwise hide the signal the researchers were looking for. “The most challenging part was to get rid of the orbital influence of Earth’s ‘K1 tide’, which biases the precision of the frame-dragging measurement,” he says.

“Thanks to this precise measurement, which is an order of magnitude better than previous Solar System measurements, we have been able to set stronger limits of validity to some theories alternative to general relativity proposed to possibly explain the great mystery of the accelerated expansion of the universe,” he tells Physics World. “Some of these theories predict something that may be related to quintessence (a mysterious time-dependent scalar field).”

While these theories predict the same so-called post-Newtonian weak-field effects as general relativity, they predict a different frame-dragging effect, he adds. Increasing the accuracy of frame-dragging (and indeed other tests of general relativity) can therefore place further limits on these other theories. It could also shed more light on phenomena like the flow of time around rotating black holes, where frame-dragging is extremely pronounced.

Laser-ranged satellites remain in orbit for many decades (LAGEOS was launched by NASA in 1976) and will carry on providing data for a very long time. “The more time we have, the more observational data we can obtain and therefore tests of general relativity (not only frame-dragging but also other tests) can be carried out with much increased precision,” says Ciufolini. “This data could also improve our knowledge of the Earth and allow, for example, improved determinations of the Earth tides and its centre of mass, which is useful for the Global Positioning System.”

The study is detailed in Nature.

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A previously unrecognized source of seismic hazard caused parts of Japan to move eastwards by up to 5 mm within minutes of the 2011 Tohoku-Oki earthquake. Conventionally, such shifts occur when seismic waves generated by rupturing tectonic plates cause the plates to slip, triggering movements of the land mass and the ocean floor. But a new study finds that in the Tohoku-Oki quake, the real culprit was waves that travelled down to Earth’s core and back – a phenomenon more usually associated with efforts to image structures deep inside the Earth.

The 2011 Tohoku-Oki quake occurred at the boundary between the Pacific plate and the North American plate, with an offshore epicentre around 130 kilometres east of Sendai. At magnitude 9, it was one of the largest recorded earthquakes in history, and it caused widespread devastation, including thousands of fatalities. The tsunami that followed exacerbated this damage, with meltdowns of three out of six nuclear reactors at the Fukushima Daiichi power station releasing radioactive caesium into the air and water and prompting a large-scale evacuation with long-term health impacts.

The earthquake was bigger than most models estimated, which compelled seismologists to examine and revise existing models of the largest possible earthquakes and their frequencies in the boundaries of tectonic plates. Instrumented records of this earthquake are still revealing new information about geophysical processes in the boundaries of tectonic plates.

Surface to core and back

In the new work, researchers led by Sunyoung Park at the University of Chicago, US studied shear waves recorded following the earthquake in Japan’s dense network of high-rate Global Navigation Satellite System instruments. Along with the expected seismic waves from the earthquake rupture, the team found so-called ScS waves that travelled thousands of kilometres through the Earth, bounced off the core and travelled back to the surface, arriving across Japan almost simultaneously 13 minutes after the main shock. “The name ScS reflects that path: S[hear] through the mantle, c for reflection at the core-mantle boundary, and then S again on the return path,” Park explains.

Although seismologists have studied ScS waves extensively, they have mostly done so for the purpose of imaging the deep Earth. “Because [ScS waves] reflect from the core-mantle boundary, they have helped constrain the depth and properties of the core-mantle boundary; the structure of the lowermost mantle; attenuation and anisotropy in the mantle; and source characteristics of large earthquakes,” Park explains.

The team’s study offers the first evidence that ScS waves can also trigger significant displacement-causing slip after an earthquake, meaning that earthquake hazard researchers may need to consider these waves to fully capture consequences of earthquake ruptures on the land as well as deep within tectonic plates.

A high-quality, high-resolution dataset

Two aspects of the Tohoku-Oki earthquake made it an incredible opportunity to study the role of ScS waves in triggering a slip event. The first is the nature of the earthquake itself. As well as releasing tremendous amounts of energy, it occurred on a shallow tectonic fault that is dipping down. This combination sent strong shear wave energy travelling nearly vertically down to the core, generating ScS waves strong enough to trigger movement in the tectonic plates.

The second was the quality and resolution of data. “Because Japan is so densely instrumented, we can look for small, coherent signals that would likely be invisible elsewhere,” Park says. “This made it a natural case in which to ask whether delayed seismic phases might trigger additional deformation.”

Working with Hiroo Kanamori at the California Institute of Technology (Caltech), US, and Luis Rivera at the University of Strasbourg, France, Park considered whether Earth’s elastic response to the main shock could explain Japan’s 5-mm displacement. To better understand this possibility, they calculated displacements at all the instrumented locations for many possible configurations of the earthquake rupture. However, the results did not reproduce the observed eastward motion.

The researchers then simulated possible slip scenarios across the tectonic plate interfaces, hoping to better characterize the levels and spatial extent of the slip that caused the eastward displacement. “The inferred slip event likely involved interfaces where the Pacific plate subducts beneath the Okhotsk Plate, and where the Philippine Sea plate subducts beneath the Eurasian plate,” Park says. Exactly how far this slip propagated, however, is still unknown because of the paucity of instrumented locations beyond Japan.

A slow-motion slip

Although the most memorable earthquakes and tsunamis are the ones that manifest havoc on Earth’s surface, the tectonic plates underneath are in perpetual but slow motion. At higher depths, these slow-moving plates produce earthquake events that unfold over days or weeks. Such events are called slow-slip or silent earthquakes and are important for accumulating and releasing stress as part of the earthquake cycle.

Rather than triggering a fast earthquake rupture, the ScS waves from the Tohoku-Oki quake appear to have set off a slow slip event spread over a very large area at intermediate depths of 20–60 km. This is the depth range where seismologists commonly observe silent earthquakes, and it provides avenues for understanding the dynamic processes that impact the earthquake cycle. This continuous flux in Earth’s deeper layers is a source of curiosity for many seismologists, including Park.

“A broader motivation for me is a general interest in deep-shallow interaction in the Earth,” Park tells Physics World. “I am especially interested in cases where processes or wave propagation involving the deep interior can influence faulting and deformation in the shallow lithosphere or vice versa.”

The researchers report their findings in Science.

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Astronomers have created a spectacular composite image of a dying star’s remains in the act of being recycled.

The image shows the Helix Nebula, a bright ring of gas that is located 650 light-years from Earth in the constellation Aquarius.

Resembling a giant human eye, its familiar ring formed from material expelled by a star near the end of its life. The remnant of that star, a white dwarf, lies at the nebula’s centre.

Astronomers trained the Modular Optical Telephoto Hyperspectral Robotic Array (MOTHRA) on the nebula while it was still being constructed at the El Sauce Observatory in Chile’s Coquimbo Region.

When complete later this year, MOTHRA will use 1,140 high-end telephoto lenses and filters that function as a giant 4.8-m aperture refractor telescope to detect the extremely faint glow of gas across large swaths of the sky.

In the image above, the MOTHRA data are shown in black and were collected in November 2025 using 190 or so lenses. These have been combined with previous observations made by the Hubble Space Telescope and the Kitt Peak 4 m telescope, which are shown in colour.

The MOTHRA data reveal a collection of 22 complete or partial arc-shaped glowing shock waves on the eastern side of the nebula.

Dubbed bow shocks, the waves resemble those that form in front of a boat moving through water. In the Helix Nebula, mostly invisible clumps of stellar debris dart rapidly through the thin gas among stars. The glowing bow shocks mark where those clumps collided with the surrounding gas.

By studying the image, astronomers traced the star’s debris as it is stripped, broken apart and gradually mixed into interstellar space.

“We are seeing material shed near the end of a star’s life being broken apart and returned to the galaxy,” notes Yale University astronomer Pieter van Dokkum, who led the study. “That handoff – from recognizable stellar debris to the diffuse gas between the stars – has been very difficult to observe.”

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Credibility is a cornerstone of modern science and concepts such as reproducibility and peer review have evolved to ensure that the knowledge produced by scientists is high quality. However, for science to thrive and benefit everyone, scientists themselves must be seen as credible to the general public.

This episode of the Physics World Weekly podcast features Shumaila Bhatti and Dara Wald who are social scientists at Virginia Tech in the US. They have done a comprehensive study that reveals that the perceived motivation of a scientist plays an important role in how credible they appear to the public.

The study involved nearly 1000 subjects in the US and a key result is the identification of five audience classes that differ in terms of their perceptions of scientific credibility. Wald and Bhatti talk about their motivation for doing the study and its interpretation. One of their findings is that people in all classes don’t tend to doubt the expertise of scientists, but they would prefer scientists to honest and motivated by the public good.

The paper discussed in this episode is “There is not one public: divergent perceptions of scientists’ source credibility in the United States”.

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Researchers at Kyushu University in Japan have developed a flexible electronic circuit that can connect itself to another electronic circuit and then disconnect from it. The prototype structure is an important step towards electronic devices that can reconfigure and even repair themselves, and it could have applications in wearable sensors, soft robotics and medical devices.

Most of today’s electronic devices are fixed, or “non-modular”, explains study leader Fumihiro Sassa of Kyushu University’s Department of Electrical and Electronic Engineering. Typically designed for specific tasks or environments, they are not readily adaptable to new ones, and they often cease to function if even a single component in their electronic circuitry fails. This leaves them dependent on human operators or external robotic systems if it becomes necessary to expand their functionality or repair damage.

“This can be a serious limitation inside very small machines, in space equipment, in devices requiring specialized handling, such as wearable chemical sensors, or in systems containing very large numbers of wires and electronic elements,” Sassa explains. “In such cases, in-situ repair can be difficult. The whole system may need to be replaced.”

Connection and disconnection

To overcome this problem, the Kyushu University researchers have been developing what they term “kinetic electronics” modules. These consist of electronic circuits and actuators that deform when an electrical current is applied to them so that they can mechanically and electrically connect to other modules. Before this connection takes place, different modules are separate, but after connection or “docking” takes place, one module can independently deform another when power is supplied through the point that connects them.

In this way, explains Sassa, the circuits can rearrange their own hardware structure. “Such functions have traditionally been used in mechanical systems, such as spacecraft, trains and modular robots, but we have now applied them to an electronic device.”

Sassa and colleagues fabricated their electrothermal bimorph actuators from polypropylene and polyimide films with heater electrodes and electrical circuits formed on them through a two-dimensional top-down process. Because the two polymers expand differently, Sassa explains that Joule heating causes selected actuator sections to bend. “Prescribed sequences of these motions produce docking and undocking and once docked, passive mechanical engagement maintains the connection without continuous power being supplied,” he says. “Undocking requires a separate actuation sequence.”

Towards miniaturization and more intelligent control

The researchers say they are working on miniaturizing their system and looking how to control it more intelligently. In the present study, which is detailed in npj Flexible Electronics, they demonstrated the docking mechanism using a small number of millimetre-scale independent sensors and actuators formed together on the circuit, with motion being controlled in sequence by an external microcontroller. They are now developing photolithographic processes to further decrease the size of these components and have already fabricated actuators smaller than 100 μm using these techniques.

“In a similar way to large-scale integration in conventional electronics, doing this will allow us to integrate very large numbers of these sensing and actuation elements, allowing the electronic circuit to form and change much more complex mechanical structures and functions,” says Sassa.

“We are also interested in so-called distributed control, in which the central controller does not need to specify every movement,” he adds. “Instead, many elements would follow relatively simple local control rules, from which advanced self-reconfiguration and self-organization could emerge.”

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20 words Top dog!

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Researchers in the US have proposed a new metric to determine the economic viability of future fusion power plants. The measure is similar to one used by fusion researchers to ascertain the output of fusion reactions, which is known as the Q factor.

Nuclear fusion, which powers the stars, involves two light nuclei binding to form a heavier nucleus, releasing huge amounts of energy in the process. Harnessing fusion on Earth using the hydrogen isotopes deuterium and tritium could lead to an environmentally friendly and almost limitless energy source.

In the 1950s, the engineer and physicist John Lawson laid out what became known as the “Lawson criterion” for fusion. It describes the combinations of temperature, plasma density and energy confinement time that can produce net energy from the plasma due to fusion, regardless of its absolute power or volume.

Specifically it calculates a factor known as “plasma Q”, which is the ratio of fusion power produced to the external power required to sustain the plasma, with a Q = 1 meaning break-even.

When it comes to magnetic confinement, in which magnetic fields are used to contain a high-temperature plasma, the Joint European Torus based in Oxfordshire, UK, which ended experiments in 2024, achieved a Q of 0.67 in 1997.

The ITER experimental fusion reactor, which is currently being built in Cadarache, France, aims to have a Q of 10 when fully operational towards the end of the 2030s.

Developments in industry have also sped up in recent years and just last month the Fusion Industry Association released a report finding that private fusion companies raised almost $4.5bn in funding over the past year – a 70% increase over the previous year.

The report discovered that 71% of the 65 companies surveyed expect the first fusion plant to deliver commercial electricity by the 2030s. Others, however, remain unconvinced that fusion will soon be a viable energy source.

With that in mind, researchers are now proposing a framework for understanding what is required to make fusion energy commercially viable in the marketplace.

While the costs of basic experiments can be easily documented, estimating the costs of a fusion reactor is somewhat more challenging.

“It’s challenging to reduce complex scientific and engineering requirements to economic consequences,” says economist Andrew Lo from the Massachusetts Institute of Technology (MIT), who co-authored the new study (J. Fusion Energy 45 49). “But if we don’t do that, we’re not going to get the funding we need to achieve the impact we want.”

A new ‘Q’

The new framework includes 10 parameters that evaluate the economic viability of a fusion energy power plant. Some of these are scientific and physical, dealing with the energy consumed and produced in a given plant.

Other parameters are based on engineering and economics, such as the costs of plant construction, returns from invested capital, the efficiency of converting fusion power into an economic product as well as the durability of components used in the energy conversion.

The “economic Q” is then given as the ratio of capital gained to that expended.

MIT nuclear engineer Dennis Whyte, who also co-authored the study, says that the framework is about what it takes to achieve a net-positive economic return with the economic Q needing to be greater than 1 for basic viability.

Whyte, who was yesterday appointed chief executive of the United Kingdom Atomic Energy Authority, adds that the parameters do not depend on the size of the reactor being built, so any inputs can be scaled to a given project or power output.

“When you’ve got a framework to evaluate it in a quantitative way, it tells you about the literal worth of making a particular design decision,” adds Whyte. “That seems to me at this moment of fusion development absolutely critical, and what we’ve been missing.”

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The quantum tunnelling of hydrogen atoms plays a central role in many physical, chemical and biological process, but a practical means of controlling it has proved elusive. Researchers from the University of Tokyo, Japan have now demonstrated that the way hydrogen permeates through a material depends on the degree of symmetry in the material’s crystal structure. By controlling this symmetry, scientists could therefore gain control over hydrogen’s ability to tunnel, potentially leading to safer and more efficient media for storing this industrially important clean-burning fuel.

“We found that hydrogen undergoes pronounced quantum tunnelling in a highly symmetric crystal environment, whereas the tunnelling is strongly suppressed when the symmetry is lowered,” explains Katsuyuki Fukutani, who led the research together with colleagues Takahiro Ozawa and Sudhansu Sekhar Das. “This is particularly exciting because it identifies crystal symmetry as a fundamental principle for controlling the quantum behaviour of hydrogen in materials, opening new possibilities for tailoring hydrogen transport.”

A model hydrogen-storage material

The researchers, who work at Tokyo’s Institute of Industrial Science, obtained their results by studying how hydrogen atoms move through a model hydrogen-storage material, vanadium, at low temperatures. To do this, they combined two complementary techniques. The first is called nuclear reaction analysis and it measures the hydrogen’s depth distribution directly with high resolution. The second involves measuring electrical resistance, which sensitively monitors how the hydrogen redistributes itself over time.

These measurements revealed that at temperatures of around 70 K, hydrogen atoms begin to migrate through vanadium’s crystal lattice, hopping between its interstitial spaces. At low hydrogen concentrations, this hopping occurs within a highly symmetric structure known as α-phase vanadium, and the hydrogen atoms easily tunnel between neighbouring lattice sites. At higher hydrogen concentrations, however, vanadium’s crystal lattice distorts, forming a β-phase. Under these conditions, the hydrogen atoms must overcome an energy barrier (of 148 meV in this case) before they can tunnel to neighbouring sites.

Quantum tunnelling or classical thermal activation?

Based on changes to vanadium’s electrical resistance, the researchers were able to calculate the diffusion coefficient of hydrogen over a wide range of temperatures, including those for which quantum tunnelling is important. They then interpreted these results using quantum-mechanical calculations of hydrogen motion, which revealed that the crystal symmetry determines whether hydrogen moves by quantum tunnelling or by classical thermal activation. They found that in the α-phase, hydrogen’s ground states are delocalized over tetrahedral sites thanks to tunnelling. In the β-phase, in contrast, the uniaxial strain produced by the distortion of the crystal lattice leads the quantum states of the hydrogen atoms to localize around certain (O_z) sites in the material.

Hydrogen is the lightest element, so Fukutani says it’s not surprising that it exhibits pronounced quantum behaviour. However, while quantum tunnelling had long been assumed to play an important role in hydrogen diffusion, it was difficult to obtain direct experimental evidence for it because we cannot easily observe hydrogen inside materials using conventional techniques. “We wanted to clarify how hydrogen actually behaves in the quantum regime and identify the factors that control its tunnelling,” he explains.

New possibilities for controlling hydrogen permeation and storage

“Our findings suggest that hydrogen transport can be controlled by tuning quantum tunnelling through crystal symmetry — for example by applying external strain,” he adds. “This capability opens up new possibilities for controlling hydrogen permeation, storage and even catalytic reactions.”

More broadly, Fukutani says the team’s work establishes crystal symmetry as a new design principle for tailoring quantum hydrogen behaviour in functional materials. The Tokyo researchers now plan to extend their work to a wider range of hydrogen storage media, including metal alloys and oxide materials. “Ultimately, we hope to establish a universal framework describing how local atomic structure and crystal symmetry govern the quantum behaviour of hydrogen,” Fukutani tells Physics World.

They report their present work in Nature Communications.

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All scientific inquiry involves some kind of uncertainty, but the uncertainties in cosmology are particularly daunting. As well as being complex and difficult to describe, the systems cosmologists investigate are almost by definition out of reach. In these conditions of uncertainty, how confident can we be in the models we’ve built? How can we come to know how galaxies form, how the universe began or how much dark matter it contains?

In The Random Universe: How Models and Probability Help us Make Sense of the Cosmos, cosmologist and astrophysicist Andrew Jaffe offers a masterful and refreshing take on these questions. As the director of the Centre for Inference and Cosmology at Imperial College London, UK, and a past co-investigator on ESA’s Planck satellite that provided us with so much new information about the cosmos, Jaffe is well-equipped to walk readers through the tools that allow us to learn about the world despite its uncertainties. Anchoring his insights in beautifully narrated episodes from the history of physics, astrophysics and cosmology, he sheds light on how our theories of the universe evolved into our current best cosmological model – which nonetheless still has limitations.

Jaffe is particularly good at recounting how we refined, revised and even replaced some of our assumptions in light of incoming evidence such as the first measurements of stellar distance; the discovery of galaxies beyond our own; and precise measurements of cosmological parameters. Throughout this journey, he engages thoughtfully with a rich philosophical tradition that runs from David Hume in the 18th century through Willard Van Orman Quine, Imre Lakatos and Paul Feyerabend in the 20th.

Bayes’ theorem is important because it tells us how to update our degree of belief in light of new evidence

The book’s main protagonist, though, is the mathematician Thomas Bayes. For Jaffe, Bayesian probability is key to dealing with uncertainty, and even to solving Hume’s notorious problem of induction: how do we justify inferences from a finite set of observations to generalizations that go beyond them? Bayes’ theorem is important, Jaffe argues, because it tells us how to update our degree of belief in light of new evidence. It shows us why and how, even in an uncertain world, “the more observations we make, the surer we become”.

Of course, before we can use probability to deal with uncertainty, we first need a model. As Jaffe puts it, “Absent a model, I can’t assign a probability, and absent a probability, I can’t quantify my uncertainty about the world.” So, what exactly is a model? I found Jaffe’s answer to be one of the most captivating elements of the book. As the title of a subsection of chapter five puts it, “a model is a story about the world”. Without models, Jaffe tells us, our world would be an unexplained series of unrelated events. Models are also what allow us to take a finite set of data and use it to create something new. Without this leap, Jaffe suggests, we cannot learn anything about the world, because “you can’t make sense of an experimental result unless you have some model to interpret it”.

Of course, if the way we interpret data depends on our model, then different people may well obtain different interpretations depending on which model and which prior probability they choose. This charge of subjectivity is a longstanding accusation against Bayesians, but Jaffe offers at least a partial solution: “If you and I agree on the model, we should assign the same probability.” This, Jaffe argues, is where objectivity emerges, writing that “we come to the same conclusions if we start from the same premises”.

Models allow us to understand the world by bridging subjectivity with objectivity, and the personal with the collective

Many contemporary philosophers are at odds with the idealized view of science as an objective and linear enterprise that produces theories from a God’s-eye view. Instead, they strive to portray it as something that is social and human, but reliable nonetheless. Jaffe’s own views seem to align with this endeavour; as he puts it, “the scientific coupling of models and observations is a living, breathing, subjective endeavour, simultaneously collective and personal”. Through their interplay with data, he argues, models allow us to understand the world by bridging subjectivity with objectivity, and the personal with the collective.

Not everyone will agree with Jaffe that Bayesian probability offers a solution to Hume’s problem of induction. Personally, I (or perhaps the hardcore rationalist in me) was not convinced. Nevertheless, I found the book’s thesis – that uncertainty is not a hindrance to knowledge, but an opportunity to learn (and learn more) about the world – simultaneously liberating, humbling and empowering. I recommend The Random Universe to scientists, philosophers and anyone interested in better understanding the role of probability in science; the philosophical problems with how we handle uncertainty; and how our standard cosmological model came to be. I also hope it will encourage more collaborations between philosophers and scientists. There are many questions we can explore further if we work together.

• 2025 Yale University Press, £25hb, 288pp

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The event horizons of black holes that are far from equilibrium can now be described by the first and second laws of thermodynamics thanks to new work by theoretical physicists at Pennsylvania State University in the US. The result augments the work of the late Stephen Hawking and others who showed in the 1970s that these classical concepts have applications in idealized, static black holes.

Black holes are objects so dense that their gravitational pull prevents anything – even light – from escaping them. The “point of no return” of any object falling into a black hole is called the event horizon, and it represents the black hole’s mathematically defined “edge”.

Although black holes can be described using concepts from quantum mechanics and Einstein’s general theory of relativity, some 50 years ago physicists like Hawking and Jacob Bekenstein showed that the equations governing them are also astonishingly similar to the fundamental laws of thermodynamics. “This seminal observation sparked a rethinking of black holes in thermodynamics terms,” explains Abhay Ashtekar, a physicist at Penn State’s Eberly College who led the new study. In particular, Ashtekar says it meant that black holes could be assigned an entropy that is equal to the area of their event horizon.

The problem, he continues, is that technically, these relationships are only valid for black holes in equilibrium – that is, those that are stable and do not change over time. In contrast, real astrophysical black holes are constantly changing: they form, merge and eventually evaporate because of quantum effects.

“In these dynamical objects, event horizons are ‘teleological’, meaning that we need to know how a black hole will behave for all of eternity to be able to define its entropy today,” Ashtekar explains. “This notion of black hole entropy is therefore physically untenable. Indeed, this limitation was already recognized in the 1990s and it has been the elephant in the room since then.”

Extending the laws of thermodynamics

In their new work, Ashtekar and colleagues sought to overcome this limitation by replacing static event horizons with an alternative concept known as dynamical horizon segments. These segments are characterized by the physical properties of a black hole at a given moment in time, and other researchers have employed them in numerical simulations of black hole mergers and gravitational collapse. Indeed, Ashtekar and various colleagues had previously shown that dynamical horizons were a physically admissible replacement for event horizons.

However, Ashtekar says that these earlier studies had not addressed two central questions. These involved defining intensive parameters – analogues of pressure and temperature in ordinary thermodynamics systems such as gases – and defining the energy of a black hole by itself in a highly curved region of space-time at a given instant.

“Our study now shows that Einstein’s equations imply that these dynamical horizons also satisfy equations very similar to the first and second laws of thermodynamics,” Ashtekar tells Physics World. “What is more, the change in thermodynamical quantities of these horizons at any given moment in time are caused directly by fluxes of energy and changes in the angular momentum of the black hole at that instant.”

The researchers’ new calculations show that even when black holes are very far from equilibrium, their evolution defines specific trajectories in the space of different equilibrium states. “This allows us to transport observables from these states to instantaneous non-equilibrium ones,” explains Ashtekar. “Such a procedure cannot be applied to conventional thermodynamics systems; black holes are very special in this regard.”

Event horizons “entirely absent” when quantum effects are included

According to team member Daniel Paraizo, the new work treats the event horizon as a dynamical horizon segment that forms in a gravitational collapse and then evaporates because of quantum effects. Intriguingly, Paraizo says that within this framework, event horizons vanish entirely when quantum effects are included – a fact which, he says, “removes a great deal of confusion currently surrounding the issue of information loss from a black hole, for example”. This same finding, he notes, also supports an idea that Hawking advocated shortly before his death in 2018: the possibility that a “true” event horizon never actually forms.

The Penn State researchers now plan to build on their present work with theories involving both classical and quantum gravity. Team member Jonathan Shu says that such theories may provide a thermodynamic explanation of several puzzling features that have been observed in numerical simulations of black hole mergers. “We have also already extended our results to theories of gravity beyond general relativity,” he reveals. “For quantum gravity, dynamical horizon segments have been successfully deployed in the so-called semi-classical phase of black hole evaporation and work is underway to address still unanswered questions about the final stages of the process using a theory known as loop quantum gravity.”

The researchers report their work in Physical Review Letters. Ashtekar will also be speaking on this subject at Penrose Fest@95, which is due to be held in Oxford, UK in September.

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A system will generally move towards equilibrium when a change is made to it in a process called relaxation. To predict the state of the system after some period of time, we only need to know its current state and the external conditions. However, some polymers have memory behaviours where the evolution of the system is not only dependent on the current state, but also on previous states. This is known as the Kovacs effect.

In this work, the researchers investigated the Kovacs effect in a system consisting of suspensions of rod-like nanoparticles. By applying an electric field to these nanoparticles they align, therefore the particles change the liquid’s optical anisotropy, which can be measured as birefringence, which is how the liquid changes light polarization. More birefringence means the particles are more aligned. Importantly, there are faster- and slower-relaxing nanoparticles because of their polydispersity and different sizes, meaning they align at different rates. By changing the strength of the electric field, the faster and slower nanoparticles become out of sync with each other. The future behaviour will then depend on the system’s previous history that is overall hidden by the global birefringence measurement; this is the Kovacs effect.

The researchers modelled the orientational dynamics using the Smoluchowski equation, which describes rotational diffusion of particles. They found that relaxation is not determined by a single timescale or relaxation mode. When some of the modes are fast and some are slow, memory effects will occur. The Kovacs effect is important because it shows that a simple strategy of applying a strong electric field before switching to the target field does not necessarily speed up relaxation. Due to memory effects arising from particles relaxing at different rates, the system overshoots the target state, reducing the expected gain in speed.

To overcome this, the researchers designed improved two- and three-step protocols that suppress the slowest relaxation modes rather than simply matching the average birefringence. These protocols reduce the memory effect, produce a smoother approach to equilibrium, and achieve faster relaxation, although the benefit of additional switching steps becomes progressively smaller. This research improves our understanding of memory effects in complex systems and provides a practical strategy for controlling nanoparticle dynamics more quickly and efficiently.

Do you want to learn more about this topic?

Scientific developments of liquid crystal-based optical memory: a review by Jai Prakash, Achu Chandran and Ashok M Biradar (2016)

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Topological materials have been receiving a lot of attention in recent years because of their potential applications in future electronic and quantum technologies.

These are a type of material whose electrons have properties that stay stable even when the material has small defects, impurities, or imperfections. They often have surface or edge behaviour that is very different from the interior, because of the structure of the material’s quantum states.

Researchers use quantities such as Berry curvature and Chern numbers to describe topological materials. Berry curvature measures how an electron’s quantum state changes as its momentum changes. Adding this curvature across the whole band gives a Chern number, a whole-number label that can show whether the material is topological.

A key question in this area is: when a material has topological properties, how much of that behaviour is actually tied to quantum entanglement?

In a new paper published recently, Kazuki Ikeda and Steven Rayan tackled this question using the spinless Haldane model. This is a widely used theoretical model for understanding topological materials. This model describes electrons moving on a honeycomb lattice, which has two different sublattices, called A and B.

Here, the researchers added an extra layer of analysis. Instead of only calculating whether the model is topological, they were able to determine where the topological signal comes from.

By introducing a filter based on quantum entanglement, they tested whether the Berry curvature is associated with electron states that are spread across both A and B sublattices, or with states that mostly sit on one sublattice.

They also focused on what happens when the system moves between different topological phases, giving a more organised way to describe what changes when the energy gap closes and the material switches phase.

These results will provide invaluable insights into understanding and designing topological materials going forward.

What’s also interesting here is that, in order to obtain these results, the authors employed Langlands-inspired mathematics to keep track of what changes when the material switches between topological phases.

The Langlands programme is an ambitious mathematical dictionary that tries to translate problems about numbers into problems about symmetry, geometry and analysis.

Although the link in this work is purely conceptual, it does show that Langlands-style structures can organise real physics problems in topological matter.

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Tissue engineering offers a means to restore, maintain or replace biological tissues. But it is difficult to grow blood vessels using conventional fabrication techniques like 3D printing, as they are typically not precise enough to print fine capillaries and veins. A team of engineers from the Massachusetts Institute of Technology (MIT) has now developed a new approach to do just that, by using mechanical forces. Their blood-vessel-on-a-chip could be the first step in the scalable production of vascular networks that could then be implanted in the body to replace tissue that has been damaged by disease or injury.

The researchers, led by Ritu Raman, made their chip by filling a Petri dish with a gel containing nutrients and cell-growth factors. They then embedded a small magnet into the gel. Finally, they introduced a thin, hollow tube into the gel and coated the inside of the tube with live endothelial cells – the cells that naturally line blood vessels in the body.

Once anchored onto the inner walls of the tube, the endothelial cells began sprouting new, capillary-like vessels in the gel. And when the researchers moved the embedded magnet back and forth in different directions and by varying degrees, they found that the mechanical forces created by the moving magnet could stretch the vessels and increase the number of new capillaries that grew, as well as their length.

‘Steering’ blood vessel growth

“We also showed that blood vessel growth, or angiogenesis, could be directionally patterned using the mechanical forces created by the magnet and that these directions could change dynamically over time,” explains Raman. “This allows us to ‘steer’ blood vessel growth in all three spatial directions (x, y, z) and make complex geometries (like L-shaped branches) that would not be possible to fabricate using conventional methods.”

The researchers had previously demonstrated that biological cells are highly responsive to mechanical forces in the body, but they did not know how different types of forces – for example, stretching in different directions and at different degrees and frequencies – impacted the 3D structure of blood vessels. The main obstacle lay in developing a coupled magnet system to precisely stretch blood vessels in different directions. To achieve this, they designed a method for mechanically stimulating tissues, dubbed “magnetic matrix actuation”.

In their new work, which is detailed in PNAS, they went a step further and developed a method to accurately yet non-invasively stretch 3D blood vessel tissues they had built in the laboratory.

To better understand the effect of mechanical forces on angiogenesis, the MIT team decided to look into the role of a gene known as PIEZO1, which is just one of the many mechanically sensitive genes in the body. They built on the work of molecular biologist Ardem Patapoutian, who received the 2021 Nobel Prize in Physiology or Medicine for discovering that ion channels in cells open and close in response to mechanical pressure. One such ion channel is PIEZO1, which is regulated by the PIEZO1 gene.

By suppressing this PIEZO1 gene in the endothelial cells they studied, the researchers indeed observed that significantly fewer new blood vessels grew in the gel. This, they say, provides evidence that the applied mechanical forces in their experiment may have been opening the PIEZO1 ion channel in the endothelial cells, so triggering the new blood vessel growth.

“My group has always been interested in engineering artificial tissues that can be implanted in the body to repair damage caused by disease or traumatic injury, but such artificial tissues require integrated networks of blood vessels in order to function,” says Raman. “We hope that our method for precisely fabricating complex networks of blood vessels within engineered tissues will enable the development of such implants,” she tells Physics World.

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NASA’s Transiting Exoplanet Survey Satellite (TESS) mission has notched up its first discovery of an exoplanet via a method known as microlensing. The planet is a “super Jupiter” known as Gaia23bra b, and TESS observed it when the planet and its host star acted as a gravitational lens, magnifying the light from a second, more distant background star.

Astronomers have several ways of finding planets beyond our solar system. The most successful of these by far – and the one that TESS was designed for – is the transit method, which is responsible for roughly 75% of all exoplanet detections to date. This approach relies on observing the periodic dimming of a star’s light as a planet passes between the star and an observer here on Earth.

The transit method does have limitations, however. The main limitation is that we can see transits for only a small number of planets, namely those with orbital planes that are almost exactly edge-on to Earth. An alternative approach known as photometric microlensing is somewhat more flexible in this respect, as it relies on the star-planet system magnifying the light from a background star, which is known as the source. This magnification occurs because the gravitational pull of the planet-star system warps space, bending and magnifying the source’s light (as Albert Einstein predicted as part of his general theory of relativity) like a lens and producing characteristic spikes in its brightness.

A second bite at the exoplanetary cherry

Astronomers initially identified a planet in the Gaia23bra system using observations made in 2023 by the European Space Agency’s now-retired Gaia space telescope. However, while Gaia picked up the unexpected brightening of a background star, it did not identify this event as coming from a binary-star system, and it could not pick out the planet itself because its observations were too sparse, explains Mallory Harris, an astronomer at the University of New Mexico, US who led the TESS study.

In the new work, Harris and colleagues scoured TESS data from the same period. Because TESS’ observations were much denser – it observed the region every 200 seconds for nearly 60 days – they were able to identify extra features in the brightness of the light curve that indicated the presence of a planet in the system. Subsequent analyses revealed that this planet is about 1.63 times the size of Jupiter, and it orbits its host – an orange dwarf star 20% smaller than our Sun – at a distance similar to that of Jupiter from our Sun.

Complementary techniques

The transit technique is particularly sensitive to planets that orbit close to their star because these planets are the most likely to transit and block out most of their host stars’ light as they pass in front of them. In contrast, Harris explains that microlensing is most sensitive to planets orbiting at Earth-like distances or further from their stars, making it better for studying planetary systems more like our own solar system. “With microlensing, we can find smaller planets with greater orbital distances, including worlds in the habitable zone of their star and even farther away,” she says.

The transit technique and microlensing are therefore complementary because each reveals a category of planet that the other may not be able to detect, adds team member Diana Dragomir. The only problem, Harris notes, is that microlensing observations are limited-time opportunities. “Microlensing events happen once and they’re gone – they don’t repeat,” Harris says. “I like to joke that we’ll probably find the first Earth analogue with microlensing and then wave at it as it goes by because we’ll never see it again.”

That said, Harris says that Gaia23bra will be an important observing target for the Nancy Grace Roman Space Telescope. “Microlensing is currently the only method capable of detecting Earth‑mass planets at Earth‑like orbital distances,” she explains. “We already knew that this technique could find planets, because it has done so in the past using ground-based observatories.

“What we demonstrated in this work is that high-cadence observations (even with low spatial precision) and high-precision long-baseline observations can work together to find a microlensing planet. And that it is possible to specifically do this by pairing TESS observations with those from another instrument.”

This synergy between long-time-scale surveys and high cadence observations could be therefore applied towards future searches for potentially habitable worlds, she tells Physics World. Although Gaia was retired last January, making it unlikely that astronomers will find many additional events via a Gaia–TESS combination, Harris adds that there could nevertheless be other microlensing planets in the past eight years of archived TESS observations. “I’m excited to see whether there are other events like this already hiding in the TESS data and whether future surveys can work together with TESS to find more microlensing planets in different parts of the galaxy,” she says.

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Black hole collisions, merging neutron stars, exploding supernovae – these massive cosmic events are all observed by interferometer-based gravitational-wave observatories such as LIGO. Detection of the ripples in space-time caused by these phenomena is dependent on the careful control of the mirrors used in these observatories.

Led by Jonathan Richardson at University of California, Riverside, a research team has demonstrated a new wavefront actuator that can correct deformations in the surface of the mirrors by applying carefully mapped heating patterns. In a new development, reported in Classical and Quantum Gravity, Richardson’s team has used thermal imaging cameras to pinpoint where the corrections are needed. This approach should massively reduce the main limitation on the sensitivity of gravitational-wave observations.

Limiting LIGO

Since their first detection in 2015, the world of gravitational-wave observation has thrived. Now, with two major updates planned for pioneer interferometer observatory LIGO (LIGO A+ and LIGO A#) and plans for a more powerful generation of new sites, the field has reached a major turning point. Richardson describes this transition as moving from “an initial discovery era – a time when the closest, loudest events were just barely resolvable above the detectors’ noise floors – to an era of precision science”.

Richardson notes that, even now, observations such as that of a binary black hole merger with a record signal-to-noise ratio of 80 are allowing researchers to test our most fundamental theories of the nature of gravity and black holes. Heightened sensitivity will allow the observation of waves that have travelled far greater distances, over longer time periods, and are weaker as a result. These new developments will allow astrophysicists to peer further out into our universe and further back in cosmic time than ever before.

This major increase in sensitivity requires new levels of power, with LIGO A# reaching an unprecedented 1.5 MW of circulating laser arm power. The mirrors used in these detectors absorb some of the power of the incident lasers as thermal energy, resulting in heat-induced distortions that have a detrimental effect on the sensitivity of the detector. It is these deformations that place a limiting factor on the capabilities of gravitational-wave observatories.

A surprisingly simple solution

Richardson’s team has already taken huge steps towards reducing this effect with the development of new adaptive optics. In principle, these devices can apply a variable blanket of heat across the surface of the mirror that cancels out the thermal deformation from the laser heating at the nanoscale. Unfortunately, the application of this method is limited by researchers’ ability to precisely map these aberrations. This lack of sensing capability posed a roadblock on the path to high-powered gravitational-wave observation.

Richardson’s group discovered a solution to this problem when testing this new technology on a full-scale 40 kg LIGO mirror. They realised that they could accurately reconstruct the optical distortions across the entire 34 cm-diameter mirror by combining direct measurements of the surface temperature with a well programmed model of heat flow in the material.

In a surprising turn of events, the thermal imaging cameras needed to survey the full aperture of the mirror are widely commercially available and can be calibrated using LIGO’s Hartmann wavefront sensors that are already in place. Without the need for a lengthy process of technology development, as is usually required to solve LIGO instrumentation problems, Richardson is “all the more hopeful that we will reach megawatt-scale interferometry in the coming years”.

The future of gravitational-wave detection

The planned improvements to LIGO will drastically increase the observational power of this leading facility, but designs for a new generation of observatories could present even greater opportunities.

Cosmic Explorer is the US-led contribution to a new class of interferometers. Its arms will reach an enormous 40 km each, with ten times the sensitivity of LIGO. Richardson’s team will be responsible for implementing their cutting-edge research in laser wavefront sensing and correction as part of Cosmic Explorer’s base design. As a testing ground for these developments, LIGO will pave the way for an exciting new era of gravitational-wave detection.

With these levels of sensitivity, Cosmic Explorer aims to observe gravitational waves from hundreds of thousands to millions of black hole and neutron star mergers per year. Gravitational-wave detection will then reach close to the edge of our observable universe, looking back approximately 14 billion years across cosmic time.

Using existing, widely available technology, Richardson’s research group is pushing the limits of gravitational-wave detection and spurring on the development of a new, more powerful class of observatory.

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Heat flows from hot objects to cold objects – or does it? Although unidirectional heat flow is a natural consequence of the second law of thermodynamics, which states that entropy must either increase or stay the same, an international team has experimentally demonstrated that a quantum mechanism can reverse this flow of heat while remaining consistent with the laws of thermodynamics. The team then used the same mechanism to design a quantum engine that acts as a refrigerator while simultaneously extracting work.

The demon in the details

Imagine two chambers of gas side by side, separated by a permeable membrane. If the gas in one chamber is hotter than the other, then as time passes, more particles from the hotter chamber will move to the cooler chamber than vice-versa and heat will flow from the hotter chamber to the cooler one.

Now imagine a small agent, or “demon”, standing next to the partition. What if the demon allows cold gas particles to move into the hotter chamber, but stops the hot gas particles from moving to the colder chamber? In this scenario, we have achieved something called anomalous heat flow: the transfer of heat from a cold object to a hot object.

But there’s a catch. For the demon to accomplish this task, it must have a finite memory. That means that eventually, its memory will need to be erased before it can store new information. And it turns out that the erasure of this memory, even when combined with the anomalous heat flow, increases the total entropy. Thus, the second law is not violated.

Causality and the quantum switch

How can one realize such a demon? In the latest work, which is published in Physical Review Letters, Giulio Chiribella, Enrico Russo and Rosario Lo Franco worked with Zhong-Xiao Man and colleagues at Qufu Normal University in China to show that a quantum mechanical tool could perform the task of such a demon experimentally.

In quantum mechanics, things don’t need to be in a definite state all the time. They can be in a superposition of multiple states. For instance, a cat in a box can be both dead and alive at the same time until you open the box (perform a measurement). Then the cat’s wavefunction “collapses” into a definite state of either dead or alive.

Similarly, quantum mechanics also allows superpositions in the order of events. In the classical world, event A might happen before event B or vice versa. However, in quantum mechanics, we can instead have a scenario where the orders of operations are in a superposition. This indeterminate sequence of events is known as indefinite causal order, and it was crucial for achieving anomalous heat flow.

“The direction of heat exchange is not determined only by temperatures,” explains Man, a physicist who studies quantum information and quantum optics at Qufu. “When the order of two thermalization processes is coherently controlled, a quantum system can show heat flows that would be impossible in an ordinary classical picture.”

Experimental implementation

The team implemented this control using a device called a quantum switch that has an extra input known as the control quantum bit, or qubit. If the control qubit is in a 0 state, the order of operations is A followed by B. If it is in a 1 state, the order of operations is reversed (B followed by A). However, because the control qubit is a quantum object, it can also be in a superposition of the 1 and 0 state, just like the cat in a box. It is this superposition that implements indefinite causality.

To create this quantum switch, the experimentalists in the team used an interferometer to put light in a superposition of two different paths, with the photons experiencing a different order of events in each path. “A photonic set up…reproduces the effect of a quantum switch with modest resources,” explains Chiribella, a quantum information theorist at the University of Hong Kong.

The team also used this set-up to build a version of an engine that transfers heat from a cold body to a hot body while performing work. This is counterintuitive, given that in one framing of the second law of thermodynamics, heat transfer from a cold to hot body must be accompanied by work being done on the engine (rather than being done by it). However, the experiment didn’t break the second law because the control qubit of the quantum switch behaves like the memory of the demon. At the end of each engine cycle, the control qubit must be reset to its initial superposition state. In totality, the second law is obeyed.

“One of the most exciting aspects of this work is that a highly counterintuitive thermodynamic effect can be explored with photons in an optical laboratory,” observes Lo Franco, a quantum physicist in the Department of Engineering of the Università degli Studi di Palermo, Italy. “This makes the result not only conceptually interesting, but also experimentally accessible and relevant for future quantum technologies.”

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Physics faces a persistent and uncomfortable paradox. While we repeatedly assert that scientific excellence depends on creativity, rigour, resilience and collaborative problem-solving, the way we select the next generation of researchers still relies heavily on institutional prestige, grades and prior access to opportunity. Although easy to use, these criteria are deeply entangled with structural advantage resulting in a system that is efficient to operate and familiar – yet systematically exclusionary.

Traditional admissions criteria are heavily shaped by unequal access to resources, inside knowledge, mentors and cultural capital

Most academics recognize the limitations of traditional admissions criteria, but we continue to rely on them. Degree classification, university ranking, publications and reference letters feel like comfortable objective indicators of merit. In reality, however, they are heavily shaped by unequal access to resources, inside knowledge, mentors and cultural capital.

Two students with equal underlying potential, for example, can present very different CVs depending on whether they had access to a research-intensive institution, informal advice networks, paid research internships, or simply, the financial security to take risks. When admissions panels default to these signals as primary filters, they are not solely selecting for ability – they are also selecting for accumulated advantage.

This is not merely a matter of fairness but a strategic problem for science. Science and technical subjects in the UK face chronic recruitment and retention challenges. At the same time, major issues facing our society are too complex to solve from a single perspective. Physics skills are in growing demand across the UK and Ireland with PhD graduates entering industry, policy, entrepreneurship, education and beyond. This demands not only technical brilliance, but adaptability, communication and ethical judgement.

To achieve the interdisciplinary breadth required to tackle today’s issues, we need to implement thoughtful strategies and processes. If we continue to draw from a narrow and self-reproducing talent pool, we constrain not only who gets to participate in science, but the kind of science we are able to do.

A new approach

At the Centre for Doctoral Training (CDT) in Diversity-Led, Mission-Driven Research (DiveIn) based at the University of Glasgow, we saw an opportunity to move away from PhD admissions criteria being focused on prior privilege towards one based on demonstrable competencies relevant to excellent research and successful completion of a PhD. While most PhD programmes recruit students to predefined projects, which rewards prior disciplinary alignment and insider knowledge, DiveIn instead recruits a cohort first and co-creates projects later.

We worked with the Equity in Doctoral Education through Partnership and Innovation (EDEPI) programme to design a CDT with this mind. EDEPI was created to tackle persistent inequalities that create barriers to access and participation for racially minoritized groups. The EDEPI framework identifies three broad areas: comprehension and evaluation (analytical and problem solving, communication, planning and organization); delivering results (integrity, working with others, independence); and socio-emotional competencies (motivation, curiosity, resilience). We expanded the EDEPI framework to emphasize an appetite for interdisciplinary research; cohort-based development; and advocacy.

A core pillar of the DiveIn approach to the EDEPI framework is anonymization. Our applications are divided into separate components, with personal data, CVs and competency statements de-linked during evaluation. Assessors also never see names, genders, nationalities or institutional affiliations.

The DiveIn admissions process consists of four key elements. The first is an anonymized, competency-based written application, structured around five targeted questions probing motivation, resilience, curiosity and self-reflection. The second is a task-based exercise, in which all applicants analyse the same dataset and explain their reasoning – testing analytical thinking and communication independently of discipline.

Another aspect of the process is a double-marked, wide-ranging assessment, ensuring that no single impression dominates and that different aspects of the application are judged independently. The final aspect is a transparent, structured interview with questions shared in advance and mapped explicitly to competencies.

Applicants are assessed for their ability to thrive in a diverse, collaborative cohort

Importantly, applicants also receive active support, which includes webinars explaining the process, guidance videos for each question and live drop-in sessions. This is not coaching for advantage – it is an explicit attempt to dismantle the “hidden curriculum” that privileges those already familiar with academic selection rituals. Applicants are, therefore, assessed not only for individual PhD readiness, but for their ability to thrive in a diverse, collaborative cohort.

Diversity gains

DiveIn’s first full recruitment cycle provides some encouraging evidence that our approach is working. The resulting cohort is naturally diverse in background, discipline and experience. Our results also suggest that undergoing such a shift can widen participation without lowering standards and may, in fact, improve the quality and impact of the research that the PhD cohort carry out. In other words, the process did not abandon standards but changed what those standards were designed to measure.

If we continue to admit PhD candidates primarily based on narrow retrospective signals, we will systematically under-select precisely the kinds of researchers the future requires. Conversely, if we treat admissions as a design problem – something that can be structured, tested, iterated and improved – we open the door to a more resilient, creative and socially responsive generation of researchers. As diversity gains in the technology sector are stalling, this reform to admissions could help sustainably boost diversity in UK Tech.

We can build systems that are fairer, more principled, and more aligned with the realities of modern research

We now need to refine, scale and continue to evaluate the programme. But the core insight is robust: we can do better than prestige-driven selection. We urge anyone who selects PhD students for their programme to think about these issues and make use of the resources available at EDEPI on inclusive PGR admissions. We can build systems that are fairer, more principled, and better aligned with the realities of modern research.

For a discipline built on careful measurement and experimental design, it is striking how little physics has applied those principles to choosing who gets to become a scientist. Perhaps it is time we did.

• This article was written with Ross Forgan, Sandra Dopico Ardao, Qammer Abbasi and Caroline Gauchotte-Lindsay.

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A radio signal has been amplified by scattering it from a stationary coin-sized electronic circuit that behaves as though it is rotating at an enormous rate. Conceived by a team at the City University of New York, the experiment is said to provide the first observation of rotational super-radiance involving electromagnetic waves. This wave-amplification effect is inspired by rotating black holes and was predicted more than half a century ago. Andrea Alù and colleagues found that only radio waves carrying a particular kind of twist were boosted, by as much as a factor of six in power.

In 1969 Roger Penrose pointed out that a rotating black hole holds a vast reservoir of energy that, in principle, can be tapped. “An object entering the region around the black hole can split into two parts, one falls into the black hole while the other escapes with more energy than the original object had, effectively taking some rotational energy from the black hole,” Alù, explains.

Two years later the Soviet physicist Yakov Zel’dovich realized that the same thing should happen to waves. “If a wave carrying angular momentum reflects from a rapidly rotating absorbing cylinder, the reflected wave could be amplified and come back stronger than it arrived,” says Alù. That amplification is called rotational super-radiance, which Alù describes as, “a process in which a wave becomes stronger by extracting energy from a system that rotates very rapidly”.

The catch has always been the word “rapidly”. For the effect to occur, the rotation must outrun the wave itself, and for light or radio waves that means rotational rates no mechanical object could survive. The effect has been coaxed out of water waves swirling around a vortex and out of sound waves bouncing off a spinning absorber, but electromagnetic waves had been out of reach. “While the idea is fascinating, no experimental demonstration was reported for electromagnetic waves, due to the required very fast speeds,” Alù says.

Clever solution

The CUNY team has found a clever way around the speed restriction. “Instead of physically spinning an object, we created an artificial rotation by periodically changing the properties of a network of resonators in space and time in a way that mimics rotation,” says Alù. The new device is disarmingly simple, comprising three small electrical circuits wired into a loop roughly two centimetres across, each one tuneable like a radio dial. The tuning of all three is wobbled up and down, with each kept slightly out of step with its neighbours, so the pattern sweeps around the loop like a wave passing through a stadium crowd.

“Although no physical object is rotating, this travelling modulation pattern acts like a rotating system,” Alù explains. And because the apparent speed is set purely by how quickly the electronics are driven, it can be pushed as high as one likes. “In fact, this speed can be faster than the velocity of light without violating any physical law.” Nothing material moves, so nothing outruns light.

The researchers fed a 100 MHz radio signal into the loop. This light was in a specific twisted state (possessing orbital angular momentum). They then swept the rotational rate from 5 MHz up to 195 MHz. Below 100 MHz the reflected light weakened steadily, as expected. Above 100 MHz, however, the synthetic rotation overtook the wave and the behaviour flipped. The reflected signals reappeared at the same frequencies as before — 60, 70 and 80 MHz — but were twisted the opposite way, and were stronger rather than weaker. That reversal, Alù notes, is “a key signature of entering the regime associated with super-radiance”. The gain arises in special windows the team calls angular-momentum bandgaps, which open once the synthetic rotation is fast enough and through which “energy can be transferred from the synthetic rotation to the wave”.

Fussy amplfier

The amplification was fussy about its input. “Our observed amplification was selective to the angular momentum of the input wave, only waves with particular angular-momentum properties experienced gain,” says Alù. Stranger still, the effect feeds on waste. In an ordinary amplifier, energy leaking out of the device is the enemy. Here a leakier circuit gave more gain, exactly as the thermodynamic reasoning behind super-radiance demands.

Alù is careful about what the experiment does and does not deliver. “The experiment does not study actual black holes or quantum gravity. Instead, it creates a laboratory system that reproduces some of the same physical principles involved in rotational energy extraction.” What it offers, he says, is “a controllable analogue platform where researchers can test and explore concepts that are otherwise difficult or impossible to study experimentally in astrophysical black holes”.

Three circuits in the loop allow only three distinct twists, so the immediate goal is bigger loops supporting a wider range. Beyond that lies the jump from radio waves to visible light, and a quantum version in which synthetic rotation might conjure photons out of empty space. Practical spin-offs may arrive sooner. Amplifying only one twist at a time is a natural fit for encoding information, and, Alù suggests, “new forms of lasers, with selective emission of angular momentum, can be envisioned”.

The research is described in Nature.

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Two theoretical physicists – including a Nobel laureate – have solved a mathematical problem that flummoxed them for 10 years with help from Claude, the large language model (LLM) developed by the US-based firm Anthropic. In addition to its importance for fundamental physics, the result is significant because it offers further evidence that artificial intelligence (AI) is reshaping the nature of research in some fields.

The problem that kept Francesco Zamponi and Giorgio Parisi awake at night originates in the field of complex systems and relates to a phenomenon known as jamming. “Jamming describes a sudden transition at which a fluid system becomes completely rigid, yet remains disordered,” explains Zamponi, a physicist at the Sapienza Università di Roma, Italy.

To visualize this, Zamponi suggests imagining a box filled with spheres (such as tennis balls) that are floating in zero gravity, free from friction or weight. When there are only a few spheres in the box, they have plenty of room to move, bouncing off each other and the box like a classical gas. However, if you add more spheres or inflate the existing ones, space becomes increasingly scarce, and a sphere that tries to move soon impinges on its neighbours. Eventually, a critical density is reached, and every sphere is securely held by those around it, causing the entire system to “lock up” into a state where no more movement is possible.

If the spheres freeze into a regular, geometric pattern, they form a crystal-like structure that resembles carefully stacked oranges at the market. If they are compressed or added quickly, though, a crystal cannot form. Instead, they freeze into a completely disordered packing state, like a traffic jam.

Generalizing the problem

Moving beyond physical spheres into more abstract territory, Zamponi notes that jamming is an example of a highly general mathematical problem known as constraint satisfaction. “In this framework, the spatial positions of the spheres act as the variables, or degrees of freedom, while the strict rule that no two spheres can overlap serves as the constraint,” he explains. As more variables are incorporated, Zamponi adds, satisfying all the rules simultaneously becomes increasingly difficult.

Because of this precise mathematical mapping, jamming concepts are widely applied in neuroscience and artificial intelligence. In a machine learning model or a biological brain, for example, the synaptic weights represent the degrees of freedom, while the data classifications or memories that must be learned serve as the constraints.

“Just like physical spheres, an artificial neural network undergoes a jamming transition,” Zamponi observes. “In the ‘liquid’ phase, the network easily configures its weights to satisfy all constraints, allowing it to classify data perfectly. But when tasked with too much data, it hits a wall, corresponding to the ‘solid’ phase. It can then no longer satisfy all the conditions, and it begins to make errors.”

A surprising relation

In 2014, Parisi, who received half of the 2021 Nobel Prize in Physics for “the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales”, and Zamponi spotted a surprising relation in the theory of jamming. Working with colleagues in the US and France, they found that in numerical calculations, two mathematical parameters, denoted a and b and related to the scaling of the distribution of contact forces and inter-sphere gaps as the system reaches the jamming point, mysteriously add up to 1. These parameters are very important for characterizing the physical structure of the packing, but try as the researchers might, they could not obtain a formal mathematical proof that a + b = 1.

Asking generative AI for help was Parisi’s idea. The problem was well-suited for machine assistance because it was well-defined, with a clear conjecture and a known numerical answer but no analytical proof. He and Zamponi chose Claude because it boasts more advanced coding and mathematical reasoning capabilities than other models of its kind.

Even so, they didn’t ask it for the proof immediately. “We first prompted Claude to replicate the numerical calculations our group had developed a decade ago,” Zamponi explains. “Once it had successfully reproduced those exact results, we took the natural next step and asked it: ‛If a + b = 1, can you prove why?’”

The model produced an initial conceptual path that was essentially correct, but that contained minor mathematical errors and required several iterative refinements and verifications. Still, Zamponi says, the “core intuition” belonged to the AI: “We had spent years looking for a complicated solution – like deeply hidden structural symmetry – but Claude showed us that the solution was far simpler; it was right there in front of us, but we had just missed it.

“The new proof connects our infinite-dimensional theory, which is more abstract but mathematically rigorous, with a framework developed at the same time by our colleague Matthieu Wyart and his team at the École Polytechnique Fédérale de Lausanne (EPFL),” Zamponi continues. “Wyart’s theory is built on more concrete physical notions, but it relies nevertheless on some assumptions.” The new result, he tells Physics World, confirms that both starting points lead to the same physical laws.

“More important than the industrial revolution or the birth of the Internet”

Zamponi believes that the advent of generative AI could be on par with, or even more important than, the industrial revolution or the birth of the Internet. As a “telescope for the mind”, he says it could become indispensable for research, allowing scientists to test ideas at unprecedented speeds. It could also lower specialization barriers and facilitate interdisciplinary work by unlocking complex literatures that would otherwise take too long to master.

On the downside, though, Zamponi is concerned that LLMs also encourage the production of poor-quality, pseudo-scientific research, straining the peer-review system. “We desperately need to figure out how to filter and review this influx,” he says. “We also need to design novel pedagogical frameworks to responsibly integrate tools like Claude into undergraduate and graduate research courses.

“To use these tools responsibly, we believe transparency is key. This is why we chose to publish our full conversation with Claude alongside our paper. If an AI sparks a genuinely new idea, we believe that its ‘thought processes’ should be public record.”

Jamming and random sequential absorption

Zamponi is now applying the approach detailed in the new work, which is published in Journal of Statistical Mechanics: Theory and Experiment, to a problem involving the random sequential absorption (RSA) of hard hyperspheres. This classic protocol for generating random packings involves introducing spheres one by one at completely random positions. “It is a vital tool for understanding the geometry of void spaces and packing efficiency, which directly relates to finding optimal error-correcting codes and navigating the mathematical ‘curse of dimensionality’,” Zamponi says.

While both RSA and jamming transitions describe how systems of hard spheres lock up, they represent two fundamentally different physical processes, he explains. In traditional jamming, particles are mobile and fluid and they continuously rearrange and relax until the entire system undergoes a collective, sudden transition into a rigid, solid-like state. RSA, on the other hand, is a strictly out-of-equilibrium, irreversible process where particles never move once placed. RSA therefore reaches a “saturation” limit rather than a true collective jamming transition.

The post AI model helps physics Nobel laureate out of a decade-old mathematical jam appeared first on Physics World.

One of my favourite books about physics is The Second Kind of Impossible: the Extraordinary Quest for a New Form of Matter by Paul Steinhardt. It chronicles how the physicist and his colleagues established the extra-terrestrial provenance of a mysterious quasicrystal sample and then trekked to its likely place of origin in the Siberian wilderness.

That sample was first identified by the Italian geologist Luca Bindi, who features throughout the book and specializes in the discovery of new minerals. I was delighted to see that Bindi has a new paper out that identifies a hitherto unknown material. That excitement was tempered by the fact that the alloy was created by the catastrophic nuclear explosion over the Japanese city of Hiroshima.

On this day in 1945, an atomic bomb was detonated at 580 m over the city, creating a fireball where temperatures exceeded 7000 °C. As many as 140,000 people were killed by the bomb, which destroyed about 70% of the city’s buildings.

Rapid condensation

The fireball was a turbulent plasma of vapourized material from the city. This included building materials, metals, soil, water and, we mustn’t forget, some of the city’s residents. The plasma condensed rapidly creating glassy particles of micron–millimetre size that rained down on the Hiroshima area. These “hiroshimaite” particles mostly comprise of calcium, aluminium and silicon and can be found in the sandy beaches of Hiroshima Bay.

“The fireball left behind materials that never existed before,” says Bindi – who is based at the University of Florence. He adds that these hiroshimaites are helping scientists understand how matter behaves under extreme conditions – describing the fireball as a “giant accidental material-science laboratory”.

Unusual structure

In this latest study, Bindi and colleagues in Italy, the US and Switzerland have identified a new metal alloy in a piece of hiroshimaite. The metallic grain is about one micron in size and is a homogenous mixture of six metals and silicon. X-ray diffraction shows that the alloy has an unusual crystal structure. This, along with the alloy’s high silicon content, make it a special material that has never been seen before.

According to Bindi, the alloy was formed by the condensation of a complex metallic vapour that was created by a range of materials that were caught up in the nuclear fireball. As the fireball cooled rapidy, a tiny droplet of metals and silicon condensed from the plasma. Then as the temperature dropped at an extraordinary rate, the droplet solidified and its metastable crystal structure was frozen in. This violent quenching prevented the alloy from evolving to a more common crystal structure.

This is not the first time that Bindi has found a new material in the debris of a nuclear explosion. A few years ago his was part of a team that discovered a quasicrystal in a piece of trinitite – glassy material that was created in July 1945 by the Trinity nuclear bomb test in New Mexico.

Bindi and colleagues report their results in Science Advances.

The post New material was created in Hiroshima nuclear explosion appeared first on Physics World.

This episode of the Physics World Weekly podcast features Yonatan Cohen, who is co-founder and chief technology officer of Quantum Machines.

The company was started in 2018 by three physicists from Israel’s Weizmann Institute. It develops control systems for quantum computers and has about 300 employees and 500 customers worldwide.

Cohen explains why hybrid quantum–classical control systems are increasing in importance as quantum computers scale-up to include more and more qubits. He also talks about Quantum Machines’ strategy to support a wide range of qubit types – including  superconducting circuits, trapped ions, neutral atoms, spins and NV centres.

We chat about some of the company’s products and its collaborations with quantum-technology companies including Rigetti Computing and Diraq. Cohen also gives career advice for physicists who want to work in the quantum sector.

The post Building bridges between quantum and classical computing appeared first on Physics World.

Here’s how the game works:

1. 1. Enter a word guess – in this game the word has six letters.
   2. After submitting your guess, each letter in the guessed word is coloured to provide feedback:
      • Green: The letter is correct and is in the correct position in the target word.
      • Yellow: The letter is correct but is in the wrong position in the target word.
      • Grey: The letter is not in the target word at all.
   3. Using this colour feedback, refine your next guess.
   4. Continue guessing until you correctly identify the hidden word(s) or run out of attempts.

If you want a clue to the answer, read the article here.

Fancy some more? Check out our puzzles page.

The post Word wave puzzle no.7 appeared first on Physics World.

An international team of astronomers has released the highest-resolution image ever captured of the Sun’s visible surface. Taken by the Daniel K Inouye Solar Telescope in Hawaii, the picture reveals tiny plasma whirlpool-like patterns that have never been seen before (Nature doi:10.1038/s41586-026-10871-3).

The Sun’s visible surface – the photosphere – is a thin layer of its atmosphere where the fluid plasma becomes transparent. This region is known to be dynamic and complex, with factors such as magnetic field and convection currents shaping the atmosphere.

The studied region by the astronomers is a magnetically active area close to a sunspot. In the image, the solar surface appears dominated by band-like and vortex-like structures.

The authors associate these features with Kelvin-Helmholtz instabilities, a well-known effect in fluid dynamics in which rippled structures form when two fluids slide past each other at different speeds.

This generates shear forces at the interface, causing minute disturbances to grow into wave- or vortex-like flows.

The vortices occur at the edges of so-called granules, which densely cover the Sun’s visible surface and measure between 500 and 2000 km in diameter.

Some of these “fringes” are little more than 20 km wide and resolving these structures is comparable to discerning a €1 coin from a distance of 180 km.

The findings provide the first known confirmation of Kelvin-Helmholtz instabilities on the Sun and researchers suggest that the instability might explain why the Sun’s outer atmosphere gets so hot, and why magnetic energy builds up and moves around the surface.

“The newly discovered plasma vortices impressively demonstrate how minute processes – at the limit of what we can resolve using all available techniques – significantly determine the nature of our star,” notes Sami Solanki, director of the Max Planck Institute for Solar System Research in Göttingen, Germany.

The post Astronomers capture highest-resolution image ever of the Sun’s surface appeared first on Physics World.

A new mechanism governing the geometric shapes of growing elastic sheets has been identified by a trio of physicists in Israel. Through a combination of simulations and experiments, Eran Sharon and colleagues at the Hebrew University of Jerusalem showed that the dimpled patterns that form in a growing elastic object have topological origins.

This mechanism is unrelated to geometric incompatibilities, which are known to dimple natural materials. The discovery could lead to a deeper understanding of how complex shapes emerge in the natural world – and to the development of new artificial materials.

Thin sheets are ubiquitous in nature: examples include leaves, petals, and the cellular linings of organs and blood vessels. The complex makeup of natural sheets means that local regions within them have preferred mechanical rest states that are incompatible with those of other regions. As a result, there is no way to arrange the sheet so that every part is simultaneously stress free – leading to effects like wrinkling, bending, and buckling.

Called geometric incompatibility, this phenomenon is responsible for numerous geometric forms in the natural world, enabling growing tissues to shape themselves without any external influence. For some time, researchers have attempted to mimic these natural mechanisms in synthetic materials.

Richness of shapes

“Looking at natural growth processes, as in plants growth, or embryo development, we see amazing richness of shapes and shape development that currently cannot be achieved with conventional fabrication methods,” says Sharon.

Sharon’s group has already shown that many patterns in nature can be understood in terms of the Gauss and Mainardi-Codazzi-Peterson incompatibilities – which were developed in the 19^th century. Together with team member Michael Moshe, whose group explores the interplay between mechanics and geometry in soft materials, their work led to discoveries including the mechanical origins of shape selection in rose petals.

Now, Moshe and Sharon have teamed-up with Yafei Zhang to identify a phenomenon that cannot be explained by those mechanical instabilities. In their experiment, they started with a uniform elastic sheet formed into a hollow sphere, with circular holes at each pole. When they added wedges of material into the sheet to mimic growth, it initially behaved like a smooth, growing sphere – but only up to a certain point.

Missing mechanism

“The growing sheet satisfies the established local compatibility conditions, and is thus expected to show smooth ‘boring’ shape,” Moshe explains. “Yet it unexpectedly, develops a crumpled appearance, suggesting that an important shaping mechanism was missing from the existing framework.”

Important clues came when the team cut into the crumpled sphere along a meridian, from pole to pole. Instantly, the crumpling disappeared, and the sphere relaxed back to its original smooth shape. This effect also occurs in simulations of a smoothly growing sphere.

With no changes to the Gauss or Mainardi-Codazzi-Peterson incompatibilities governing the mechanical forces in the sheet, the trio concluded that the sudden transformation emerged from an entirely different mechanism, rooted in the mathematical principles of topology. In this view, unlike smooth geometric transformations such as bending, stretching, or twisting, which preserve a shape’s mechanical properties, cutting introduces a sudden transformation that changes its mechanical behaviour.

In this way, the meridional cut brought the sphere into a new topological state. “Unlike conventional incompatibility, this frustration is topological in character, and can be quantified by a global measure,” Moshe explains. “It provides a new mechanism by which growing sheets can select complex, wrinkled or dimpled shapes.”

The trio’s discovery now raises new mathematical questions about the limits of growing elastic sheets, beyond which their smooth geometries can no longer be maintained. “What we have discovered that the geometrical principles we knew before should be supplemented with topological considerations, leading to an even wider class of shaping principles,” Sharon says. “This allows a better understanding of morphogenetic processes and expands our abilities to shape synthetic structures.”

In turn, the team’s insights could uncover new understanding of how shaping mechanisms could be harnessed, perhaps leading to the discovery of new metamaterials, with shapes and mechanical functions programmed into their growth.

The research is described in Physical Review Letters.

The post Topology affects the crumpling of growing elastic sheets appeared first on Physics World.

A new report by the Trump administration that outlines a model for the future government support for science and technology has drawn heavy criticism from the US scientific community. Entitled Science: A New Golden Age, it emphasizes developments by public–private partnerships at the expense of university-driven research with critics asserting it places politics above science.

The 104-page report aims to update a 1945 document – Science, the Endless Frontier – that was issued by Vannevar Bush, who served as director of the US government’s Office of Scientific Research and Development in the 1940s. The report eventually led to creation of the National Science Foundation (NSF) in 1950.

The 2026 report focuses on how government R&D spending reaches the scientific community and claims that the US research enterprise has become too centred on established research institutions rather than individual researchers.

The report wants the government to significantly reduce the amount and number of grants it gives universities and instead make large investments in industry and non-profits. It also calls for a significantly scale-up of the use of artificial intelligence in science.

“We must renew the R&D enterprise on which our scientific leadership depends,” US science adviser Michael Kratsios and Office of Management and Budget (OMB) director Russell Vought write in an accompanying memorandum.

Yet critics says that funding for exploratory science is not the administration’s only target. “It’s very clear that Kratsios/Trump want to destroy universities, or what he calls ‘legacy institutions’,” says public policy expert Shobita Parthasarathy from the University of Michigan. “There is no respect for basic research, which has historically driven innovation in the US [but that] industry won’t fund.”

Neal Lane, former US science adviser who served as NSF director between 1993 and 1998, takes issue with how individual agencies are asked to implement the points raised in the report. “Unlike previous rules, which were uniform guidance, allowing an agency like NSF to set their own rule, the new rule is a binding uniform regulation applying to all agencies as written,” he says.

Lane is also unhappy with the report’s dismissive approach to peer review, which it argues slows down innovation, proposing instead to diversify funding mechanisms with alternatives such as “golden tickets” rapid grants and prize challenges.

“For many decades, expert peer review has been regarded as the gold standard for funding research and publishing the results,” he says. “It is not credible for the administration to claim it supports ‘gold standard science’ without peer review.”

‘Misguided approach’

While some see merit in aspects of the report, or at least a need to rethink the underpinning of scientific research, the American Association of University Professors (AAUP) see the administration’s approach as a misguided way to address those challenges. “Reforms must strengthen scientific independence – not weaken it,” an AAUP statement asserts.

That view is echoed by the Federation of American Scientists (FAS), which note that while the report calls for a “lighter, faster, and more capable research enterprise”, it says that the to the “uniform guidance that governs how federal grant funding is administered runs counter to that goal”.

The report comes as the administration’s proposed budget for financial year 2027, which Congress must approve, would cut overall government spending on R&D by 22%, with support for the NSF slashed by more than 50%, NASA by 23% and the Department of Energy’s Office of Science by 15%. The OMB also proposes guidelines that would allow agencies to terminate grants that “no longer serve agency priorities or the national interest”.

Tess DeBlanc Knowles, a senior director at the US thinktank the Atlantic Council, says US science will be hit badly if those cuts go ahead. “No amount of experimentation can counteract the damaging effects that dramatically reduced funds will have on the foundation of the US’s scientific and technological leadership and ability to train the next generation of scientists,” she says.

• A new report by the American Institute of Physics has found that physics and astronomy PhD graduates are quitting the US in record numbers. The proportion of non-US citizens leaving the US post-degree nearly doubled, from 16% in 2024 to 29% in 2025 – the largest one-year increase since 1997. The report also says about 12% of US citizens post-physics PhD left the US in 2025, compared to just 5% two years earlier.

The post Critics deride US administration’s ‘golden age of science’ report appeared first on Physics World.

Kristian Dominek Barajas is head of quantum theory at the UK-based quantum computing company Oxford Ionics, which merged with the US firm IonQ in 2025. Barajas got his PhD – which was focused on developing analytic methods for high-accuracy models of driven quantum systems beyond the rotating-wave approximation – at the University of California Los Angeles, US, via the American Physical Society’s Bridge Program. The programme provides pathways into research for qualified students who might not otherwise continue their physics education. He now serves as chair of the APS Committee on Minorities (2025–2026), where he helps shape national initiatives that support physicists from historically marginalized backgrounds – particularly people of colour, LGBTQIA+ physicists, and physicists with disabilities.

What skills do you use every day in your job?

Because I’m relatively new to the field, I often have to break difficult questions down into simpler ideas before I can grapple with them. That has trained me to take a really complicated problem and give it my best guess, and that first-pass intuition often gets me surprisingly close to the full solution.

The other thing I’d highlight is leadership skills. I come from an untraditional background – it took me a long time to do my undergraduate degree, and afterwards I worked in a lot of different jobs, including working at a pet store, where I was training to become a team lead. When I went to grad school, I applied through the APS Bridge Program, which is great, and it gave me an opportunity to get into research. But again, my path wasn’t traditional: I did soft condensed matter physics for four years, and then my advisor passed away unexpectedly, so I switched fields to trapped ions because I needed to graduate. I had no background in quantum physics at that point, so it was quite a transition.

Experiences like this added up. By the time I joined Oxford Ionics right before the merger with IonQ, even though I was the “greenest” person in my team in terms of being new to the field, I had the most leadership experience. That meant I went from being an entry-level quantum theorist to a senior quantum theorist in two or three months. A month and a half later, I became the atomic, molecular and optical (AMO) theory manager. The experience I’d gained made it easy to set priorities and get people to go in the correct direction.

What do you like best and least about your job?

My least favourite part of the job is that I don’t get to read much new research. The job is so fast-paced and there’s so many things happening every day that getting the chance to sit down and read an article is quite rare. I use AI tools to help me find and keep up with new research. Part of my workflow involves asking AI to identify relevant papers and give me an initial sense of what I need to know. I still skim the papers themselves as much as I can, but I don’t get the chance as often as I’d like to pick up a manuscript and spend a whole day working through it like I did in academia.

We also don’t always have the time to write papers about what we’re doing. It’s not that we aren’t allowed to – in fact, we’re encouraged to pursue that if we want to do it – but finding time is challenging.

I’m constantly getting to do new and interesting physics, and I absolutely love that about my job

The upside is that the pace at which I get to do research far, far outweighs what I experienced in academia. What we accomplish on our team in four to six weeks is comparable to the amount we would do in six months in academia. It is absurd how fast we get to move. I’m constantly getting to do new and interesting physics, and I absolutely love that about my job.

What do you know now that you wish you’d known at the start of your career?

I wish I’d known that feelings of imposter syndrome don’t always have to be something to fear. For me, they can also be a reminder that there is still so much more to learn, and that can be exciting. That’s why I was so excited for the opportunity to earn my PhD in physics: it gave me the chance to keep learning. Now, whenever that old imposter feeling comes up, I try to see it as an opportunity to learn rather than a reason to hold myself back. I wish I had embraced that earlier in my career and not been so afraid to try things.

The post Ask me anything: Kristian Dominek Barajas – ‘I’m able to take a really complicated problem and give it my best guess’ appeared first on Physics World.

Na₂Mn₃O₇ is a magnetic material that behaves unusually and therefore can provide insight into how magnetism emerges in complex materials. Magnetic materials contain entities known as spins, which can be thought of as tiny magnets with north and south poles. These spins interact with neighbouring spins, and as a material is cooled, they often align into an ordered pattern that extends across the entire material, known as long-range magnetic order.

However, Na₂Mn₃O₇, which contains magnetic Mn⁴⁺ ions, behaves differently. It has strong magnetic interactions, very little disorder, and a two-dimensional arrangement of magnetic ions. Under these conditions, a material with relatively large spins would normally be expected to develop long-range magnetic order at low temperatures. Surprisingly, no magnetic ordering is observed, even at very low temperatures.

The material also exhibits two distinct magnetic crossovers. Around 110-120 K, the magnetic susceptibility reaches a broad maximum, indicating that strong magnetic correlations are developing. Around 60-70 K, a feature appears in the specific heat, showing that the system is undergoing a further internal reorganisation. The presence of two separate temperature scales suggests that the magnetism develops in two stages.

Using theoretical and computational techniques, the researchers showed that this unusual behaviour originates from the crystal structure of Na₂Mn₃O₇. The crystal structure divides the magnetic lattice into strongly connected hexagonal clusters of six Mn ions. These clusters behave like magnetic ‘molecules’, with the spins inside each hexagon becoming strongly correlated. Interactions between different hexagons are much weaker and frustrated, preventing the formation of long-range magnetic order across the material.

This research is important because it demonstrates that even large-spin magnetic materials can exhibit quantum-disordered behaviour. More broadly, it shows that crystal structure can be used as a tool to engineer new magnetic states by organising spins into strongly correlated clusters that suppress conventional magnetic ordering.

“What is striking in Na₂Mn₃O₇ is that the crystal structure does more than slightly distort the magnetic lattice. It reorganises the spins into strongly correlated hexagons that behave as emergent magnetic molecules, while frustration and quantum fluctuations prevent these units from ordering collectively.“ – Yasir Iqbal, Indian Institute of Technology Madras

Do you want to learn more about this topic?

Frustrated magnets in high magnetic fields—selected examples by J Wosnitza, S A Zvyagin and S Zherlitsyn (2016)

The post Magnetic molecules explain a puzzling material appeared first on Physics World.

Graphene, an atomically thin material of a single layer of carbon atoms, is a fascinating material for high-speed electronics, spintronic devices, and neuromorphic components due to its exceptional tunable electrical conductivity. One area of research focuses on understanding how electrons flow through graphene to enable the design of advanced devices. For applications, ultrathin metal-oxide layers (e.g., aluminum oxide and titanium oxide) are routinely deposited on graphene, which deliberately alter electron flow and provide greater control over its properties, in devices ranging from transistors to spin valves. However, although the effects of these coatings are known, researchers have not previously been able to directly observe what is happening inside the device. Instead, their understanding has relied primarily on theoretical models, numerical simulations, and indirect electrical measurements.

In this work, the researchers used X-ray Photoelectron Spectroscopy (XPS) to map electrical potentials across devices while they were operating. They examined the electrical landscape, identifying regions with steep slopes corresponding to strong electric fields and flatter regions corresponding to weaker electric fields, to determine how oxide coatings modify this landscape. They found that metal oxides flatten the electrical landscape through a process known as p-type charge-transfer doping. This occurs when the oxide removes some electrons from the graphene, altering its local electrostatic environment and reducing the voltage gradient. As a result, local electric fields become weaker. The oxide layers suppress the electric fields, reducing them by more than 50%, a significant effect for device operation. A key advance of this research is the visualisation of this effect at very high spatial resolution, whereas previously it could only be inferred from electrical resistance measurements. In addition, by making a direct comparison with electrical measurements, the researchers confirmed the observed effects are due solely to electrostatics and charge redistribution.

Modern electronic devices increasingly depend on controlling electricity at very small scales. By locally adjusting electric fields using oxide coatings, researchers gain an additional design tool that enables different regions of a graphene circuit to be tuned independently. This is particularly important for spintronic devices, which are highly sensitive to local electric fields, and neuromorphic computing hardware, which requires precise control of local electrical properties.

This work represents a breakthrough in the ability to directly map charge distributions and electric fields inside operating 2D-material devices, enabling improved device design.

Do you want to learn more about this topic?

Phonons and thermal transport in graphene and graphene-based materials byDenis L Nika and Alexander A Balandin (2017)

The post Mapping electric fields in working graphene devices appeared first on Physics World.

India has produced some exceptional women physicists over the years. From Bibha Chowdhuri, who co-discovered the meson and became the first Indian woman to receive a PhD in physics, to Ritu Karidhal, who played a pivotal role in making India the fourth country in the world to reach Mars, the country boasts a large pool of talented women.

But despite women accounting for more than 40% of Indian science graduates, they still only make up about 16% of all physics faculty at universities in India, close to the disappointing global average of roughly 17%. As in many other parts of the world, there are myriad reasons for the low numbers, ranging from social pressure to prioritize families over research careers to a lack of visible role models and even sexual misconduct.

IOP Publishing, which publishes Physics World, recently held a webinar to celebrate the contributions of female physicists in India and explore the challenges they face. It featured Kaveri Hukku, chief executive of ATOS Instruments Marketing Services, Asima Pradhan from SOA University, who recently retired from the Indian Institute of Technology in Kanpur, and Urbasi Sinha from the Raman Research Institute in Bangalore.

The webinar was organized by Shobha Shukla from the Indian Institute of Technology Bombay in northern Mumbai, who co-chaired the event with Physics World editor-in-chief Matin Durrani. One of India’s leading researchers in nanophotonics and materials science, Shukla is also a member of the editorial board of IOP Publishing’s Journal of Physics: Photonics.

“We are celebrating the women who are writing history in labs, industry and lecture halls right now,” said Shukla in her opening remarks. “This celebration is not a luxury. It is a necessity. It is how we build a culture of equity and innovation.” The following is an edited summary of the webinar, which you can watch in full on the IOP Publishing website.

Expert views

Kaveri Hukku did a bachelor’s and master’s degree in physics before going into industry, where she is now chief executive of the Bangalore‑based firm ATOS Instruments Marketing Services. Founded in 2013, it supplies research institutions and companies in India with advanced scientific instrument and equipment developed by third-party manufacturers from across the world.

Asima Pradhan is a laser physicist whose main interest lies in biomedical optics. With a PhD from City University of New York, Pradhan was based at the Indian Institute of Technology (IIT) in Kanpur for more than 30 years. After formally retiring in 2024, she is now an adjunct professor at SOA University in Bhubaneswar, where she also works for her start-up firm PhotoSpimedix, which is developing portable optical devices for clinical applications.

Urbasi Sinha, who studied physics at Jadavpur University and has both an MSci in natural sciences and a PhD from the University of Cambridge, UK, is head of the quantum information and computing (QuIC) lab at the Raman Research Institute in Bangalore. It is one of the first labs in India to use entangled and “heralded” single-photon sources for quantum science and technology applications – including India’s first project on satellite-based quantum communication.

How has your career developed and what kind of research are you currently involved in?

Kaveri Hukku: My story is actually very simple. Growing up, I was only interested in sports and games. There was no time for studies in my life. But when adulthood came knocking on my door, my parents sat me down and said “You need to support yourself – you’re not going to do it with your table tennis”.

So with some knowledge in maths and physics, I did a BSc in physics and then a master’s. After that, I found myself at the Indian Institute of Technology Bombay, where I managed to do some physics research at a serious level for a couple of years. But due to many circumstances outside my control, a PhD never happened.

Just as I was trying to decide on a future course for my life, our lab bought an ellipsometer [a device that measures changes in the polarization of light after it interacts with a sample], but the firm who sold us that system couldn’t set it up. It took me a few nights, but I managed to set it up, and from that I also got a job offer with the company. That started my career with instrumentation.

Urbasi Sinha: What excited me about physics from a very early age was how it combined clarity of thought with a sense of wonder, and this is what has driven me throughout my career. I’m an experimental quantum physicist, and I have worked extensively on different aspects, whether it is quantum optics, interferometry, quantum communication, randomness, and so on.

Essentially, I have used single photons and entangled photons both for making foundational insights and for developing emerging technologies. What is so exciting about my research is that it allows one to ask very deep questions about the nature of quantum mechanics, while also building systems that may have real technological value.

A recurring theme has been to connect fundamental aspects of quantum mechanics with practical questions of trust, validation and performance. A large part of my research currently is focused on quantum communication networks; the challenge of connecting photon sources with quantum memories, entanglement swapping, building these entanglement distribution-based quantum networks as part of India’s national quantum mission.

Asima Pradhan: After completing my master’s degree in physics in India, I moved to the US to do a PhD in experimental biophotonics under the supervision of Robert Alfano at the City University of New York. Coming from a family of doctors and engineers, I’d been keen on working in biophysics and, during my PhD, I did the first fluorescent spectroscopy experiments on human tissue. I’m very proud to have been part of that pioneering work.

When I came back to India and joined IIT Kanpur, I was based in the physics department, where an interdisciplinary research culture simply did not exist

Asima Pradhan

Then I did a postdoctoral stint at the University of Montreal, Canada, where I conducted some work on photodynamic therapy, collaborating with the physics, chemistry and pathology departments. I had a really good time working in such an interdisciplinary area, but when I came back to India and joined IIT Kanpur, the scenario was very different. I was based in the physics department, where an interdisciplinary research culture simply did not exist back then.

I worked around that and started collaborations with hospitals. We conducted experiments on light-tissue interactions with polarized light. From there, we went into translational research where we actually made a device for use in hospitals. So having begun my professional journey studying particle physics and field theory, I’m now trying to be an entrepreneur. I took voluntary retirement from IIT Kanpur two years ago, but I’m still doing research as an adjunct professor at SOA University in Bhubaneswar.

What skills do you use every day in your role?

Kaveri Hukku: Our profession can be made as simple or as demanding as you want it to be. I try to maintain high technical and analytical skills because the scientists I deal with do a lot of very involved science. But they don’t always come and ask for, say, a specific camera. Instead, they will just tell me what research goal they want to achieve.

So to keep up with them, even on a very simple level, you have to know a little bit of science. You also need to be pragmatic and say if a particular instrument is not right for the experiment, and which devices would be better for their aims. Moreover, it’s a people-facing job, so you have to be able to communicate, and have integrity and honesty such that people feel in safe hands.

Urbasi Sinha: Beyond having a textbook knowledge of physics and maths, precision is very important, as are good human skills. Patience is another vital attribute to have, whether we know it or not, as is the ability to persist when progress is slow. As I’ve grown older, I’ve also realized that communicating research in a way that excites people is vital, because we want to ensure that our field thrives.

Asima Pradhan: Technical skills, such as precision optical alignment, electronics and Monte Carlo simulations, are essential. But soft skills are vital too. For example, if you want to secure funding, you need to understand the psychology of the people sitting on the other side. The same goes for conducting interdisciplinary research: it can be very difficult to convey things using terminology everybody understands.

What do you like best and least about your job?

Kaveri Hukku: What I like most is keeping in touch with physics and physicists because they still let me potter about their labs and look over the shoulders of their students to make some comment here and there. And I get to work with a lot of young people, which always keeps you young yourself. It’s very satisfying seeing young scientists now building their own labs and wanting to buy instruments from me. That part gives me great joy: in my very small way to be part of their science journey, especially women.

The thing that I really don’t like, and never have, is travelling. My job involves a lot of travelling, packing bags, airports, hotels – but it’s not my cup of tea.

Urbasi Sinha: What I enjoy most is hearing about the everyday problems of younger people in the lab and helping them troubleshoot. I also enjoy translating fundamental quantum mechanics into technology. We do a lot of that sort of work in our in the lab – in fact, we have launched a start-up company called QuSyn Tech, where we are actually building a product.

What I don’t enjoy is avoidable friction. In any academic system, there’s inevitably some friction because research can be challenging. But when there are obstacles that are institutional, administrative or bureaucratic – or when things get petty, especially with our gender – that’s what I don’t enjoy very much.

Asima Pradhan: What I enjoy most is the fact that tissue fluoresces. I always say that when you shine light on someone and if you have the right camera, we all glow. The diffuse scattering itself is, for me, still very exciting. Playing with light and tissue gives me a lot of satisfaction, especially seeing the colours on tissue due to elastic scattering and fluorescence. Now I have a device that I’m testing in hospitals, and so it gives me pure joy just to see that we can get fluorescence from a patient.

What I do not enjoy is the fact that funding is always a little limited. There are restrictions, there are over-regulations, when there should be a certain amount of freedom. Even now, after retirement, I still feel the same.

What difficulties have you faced in your career and how did you overcome those barriers?

Kaveri Hukku: I actually faced huge challenges because, when I started my career, I was pretty much the only woman who was in this field. People would wonder why a woman had come to give this product presentation and she doesn’t even have a pretty face? What is she going to get out of this?

So it was hard getting acceptance, and then there was travelling and the expectation that you would not take time off for family. It was a very warped work–life balance that I had to take on as a challenge back then, because the commercial world was – and is – cut-throat.

If you just keep at it and you believe in yourself, I think you can overcome any gender bias

Kaveri Hukku

Even now, I can still be the only woman at a meeting, but I just keep going. If you just keep at it and you believe in yourself, I think you can overcome any gender bias.

Urbasi Sinha: So far as my personal family and extended family is concerned, I have been very privileged. I don’t think I’ve had any barriers in terms of what I wanted to do. But there can be less dramatic barriers, such as being underestimated as a woman or being held to different standards, just because you are a different gender from the rest. It could even be that important decisions are shaped in informal spaces where not everyone may be included.

In the sitcom Friends, there’s this beautiful episode in which Rachel wants to be part of her office culture, but all the decisions are made out on the balcony where everyone is smoking. Rachel doesn’t smoke, but she decides to pick up smoking just to be part of the group. It’s hilarious because it’s a sitcom, but it captures the sentiment very well. Decisions are often taken in surroundings that some of us do not naturally belong to, for whatever reason.

I have definitely encountered challenges of those kinds, the underplayed ones, over the years. What has helped me most has been to stay very anchored in the science, build a very clear intellectual identity, and to remain focused on depth and originality. I also think it’s important to be well prepared, have good documentation and be willing to speak up when needed.

What has helped me most has been to stay anchored in the science, build a clear intellectual identity, and remain focused on depth and originality

Urbasi Sinha

So I think one develops both resilience and perspective that not every obstacle reflects your worth. That is very important for us to realize as women. And we should not internalize low expectations or limiting assumptions. In the long run, strong work and consistency matter a great deal.

Asima Pradhan: My father was a well-known physicist, which inspired me to study physics. But when I was doing my undergraduate degree 50 years ago, we had a class full of boys and there were only a few girls there. This is true in IIT today; you still see fewer girls.

The boys came from boys’ schools, and had not seen many girls, so they caused some disturbances. Because of this, we had to stand outside, wait for the teacher to come in and then sit in the front, and we hated it. That actually affected us to some extent, but we took it all in our stride. In contrast, during my pre-doctoral studies, we had seven girls and three boys, so that was a privilege – and, interestingly, all of us stayed in physics.

What do you know today, that you wish you knew when you were starting out in your career? And what advice do you have for other women physicists at the start of their career?

Kaveri Hukku: I wish I had known that handling money is extremely important. Whenever money is involved – whether it is in your professional life, with your siblings or with your friends – always keep finances very clear and very well-documented and then you will maintain your relationships well. Money can be like poison, but if you handle it well, you can do a hell of a lot with it. You should neither be scared of it nor give it enough power, but give it the respect it needs and figure out how you want it to be part your life.

Urbasi Sinha: We often talk about working hard, which is very important, but it’s also about what you choose to spend your time on. I have realized, as I have matured, that the choices of problems, collaborators and environment matter just as much as how hard I work.

It’s also important to build depth in your subject and not just say yes to everything. Sometimes we, as women, have a tendency not to say no. Maybe we find it a little more difficult to say no. But if we don’t, then we end up being a Jack of all trades or, in our case, a Jill of all trades, and master of none. That is something I’ve learned as I’ve grown older.

Another thing – and it’s interesting because I didn’t think this in the beginning – is that visibility does matter. The phrase “good work speaks for itself” is something we say, but then at some point it is good to communicate work as well. And Physics World, of course, is the perfect forum for this. Confidence and communication early on as a scientist are important.

My advice to young women physicists would be to invest in real expertise, to cultivate a scientific voice of your own, and not to underestimate your capacity for leadership, because you can seek out mentors, but also those who will really advocate your case.

And finally, sometimes we say: “Only when I’m completely ready, will I step forward”. But you’re never completely ready. So, step forward. Confidence will follow.

Asima Pradhan: When I came back to India from the US, I didn’t realize certain things. For example, I got a job at one place and my husband, who happens to be a physicist too, got a job somewhere else. We were very clear that, once we got back to India, we would somehow be together at some place, but that did not happen. It did not happen due to many reasons that I feel should change.

There are unwritten rules about couples not being in the same department. Some people work around such things, but it did not happen for us. We ended up working for 30 years at two different places, and only now are we together after our retirement. So the younger women need to figure out what their priorities are.

If your priorities are both family and your profession, then do not compromise too much. The next generation loses out by that. So one has to negotiate before committing. The system should also work around it. The times were different when I joined and I see change. However, it is still not enough.

• You can rewatch the IOP Publishing webinar on which this article is based at tinyurl.com/2w79m3cs.

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Usually, when physicists want to model the merger of two black holes, they use supercomputers. Now, however, physicists in the US have found a possible shortcut. In a study published in Physical Review Letters, they show that, of the final states permitted by energy and angular momentum, the remnant of a non-spinning black hole merger ends up in a state quite close to one that maximizes the system’s entropy – a surprising and puzzling result that reinforces the deep connection between thermodynamics and black holes.

“Our group has long believed that black hole thermodynamics could provide a new perspective on binary black hole mergers,” says team member Monica Rincon-Ramirez, a postdoctoral researcher at Pennsylvania State University. “While black hole thermodynamics is well established for equilibrium systems, much less is understood in the highly dynamical regime of mergers.”

Merging black holes

Black hole mergers occur when two black holes that orbit each other spiral inward with increasing speed, losing both energy and angular momentum by emitting gravitational waves until they eventually converge in a violent clash. After the moment of merger, the remnant oscillates vigorously, “ringing down” into a quiescent, rotating object known as a Kerr black hole that can be described in terms of just two quantities: mass and spin.

Meanwhile, the gravitational waves – ripples in the fabric of spacetime – from this energetic collision propagate through space virtually uninterrupted. These gravitational waves encode information about their source, and when we detect them on Earth (millions of light-years away from their origin), we can use them to predict the remnant’s size and spin. However, doing this requires solving complex equations from Einstein’s general theory of relativity using computationally expensive numerical simulations.

Connecting black holes and thermodynamics

Thermodynamics is the branch of physics concerned with the relationships between energy, heat, work and temperature. For ordinary matter, thermodynamics can describe how energy flows from one system to another in simple terms, even for complex systems with numerous particles and degrees of freedom. For example, rather than meticulously tracking each individual particle, concepts such as entropy – a measure of a system’s disorder – can be used to describe the final state of the entire system.

Physicists have long known that black holes obey laws that closely parallel the laws of thermodynamics, with the event horizon and surface gravity of black holes being analogous to entropy and temperature, respectively. Building on this established connection, Rincon-Ramirez and colleagues at the University of Mississippi, the University of California, Berkeley, and Northwestern University as well as Penn State investigated whether black hole thermodynamics could go beyond describing the properties of isolated, stationary black holes and provide, in addition, a principle for determining the final state of a merger.

The maximum-entropy conjecture

After accounting for the energy and angular momentum carried away by gravitational waves, the researchers tracked the evolving mass and angular momentum of a binary, mapped these values to those of hypothetical Kerr black holes, and calculated the corresponding entropy. They found that the Kerr entropy reaches a maximum at a mass and spin strikingly close to the final mass and spin predicted by numerical relativity simulations. Indeed, the two methods agreed with each other to within a few percent. “The Kerr entropy turned out to be remarkably meaningful for the binary system as a whole,” Rincon-Ramirez says.

Interpreting and presenting these results proved to be a challenge, however. “What we found was completely unexpected,” says Rincon-Ramirez. After deliberating among themselves as to why the final black hole’s parameters should lie so close to those of the maximum-entropy black hole, they ultimately chose to extend the conversation to the scientific community. By presenting their puzzling results and a broad conjecture, which they term the “maximum entropy conjecture for black hole mergers”, they hope to sharpen their findings through rigorous testing and eventually place them on a firm mathematical foundation within general relativity.

In the meantime, the researchers plan to extend their conjecture to more general binary black hole systems. By studying systems such as highly spinning and eccentric binaries, they hope to gain further understanding of the role of thermodynamic quantities in general relativity. “Ultimately, we hope this work will contribute to a more complete thermodynamic framework for highly dynamical spacetimes,” Rincon-Ramirez says.

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Deuterium nuclei fired into thin foils of palladium and titanium keep fusing when the nuclei’s incident energies are reduced to the level where the process should be all but extinguished. Instead, physicists in the US have found that as the incident energy is reduced, the fusion rate plateaus – even at the lowest energies probed. Indeed, the low-energy fusion rate exceeds predictions for isolated nuclei by more than 10¹⁸. While significant, the enhanced fusion rates remain far too small for energy generation.

The results suggest that a metal’s electrons and internal defects can influence how fusion occurs, according to the researchers at the University of California, Davis and Lawrence Berkeley National Laboratory

Nuclear fusion powers the stars, but here on Earth it has so far been impossible to create a practical fusion reactor that delivers usable energy to the electricity grid

“Fusion is hard in the laboratory because positive nuclei repel each other,” explains team member Thomas Schenkel at Berkeley. Quantum mechanics offers a loophole – nuclei can tunnel through the repulsive barrier without having enough kinetic energy to overcome it. However, the tunnelling probability is very small at low energies.

Not fade away

Physicists measure these nuclear collision energies in kiloelectronvolts (keV). Today’s fusion reactors tend to operate plasmas at temperatures that correspond to collision energies of about 10 keV. Below that, reactions fade away, and earlier experiments showed that fusion pretty well stopped  near 5 keV.

Yet a solid is a very different environment to a plasma. “Metal lattices contain electrons, defects, and locally concentrated deuterium, all of which can combine to create reaction environments that do not exist in a conventional plasma,” says Jeremy Munday who along with Micah Karahadian is based at UC Davis . The metal’s electron cloud partly shields the repulsion between nuclei, letting them approach more closely. This “screening” effect has been studied since the 1990s and is still not fully understood. The field also carries the scars of the 1989 cold-fusion debacle, during which experiments reporting enhanced fusion rates in solids at room temperature could not be reproduced.

Schenkel and Munday came to this field in the 2010s as participants in a Google-funded effort that revisited the 1989 claims. The programme found no evidence for room-temperature fusion, but it seeded their current collaboration.

Membrane reactor

The team’s apparatus places a metal foil, a quarter of a millimetre thick, between two very different environments. “At the heart of our experimental setup is a type of membrane reactor that combines an electrochemical cell with a deuterium ion beam,” says Schenkel. On one side, an electrochemical process – “similar in principle to charging a battery,” says Munday – pushes deuterium into the metal from a liquid. On the other side, in vacuum, a beam of deuterium ions strikes the same foil, burying itself just a few millionths of a millimetre below the surface.

Each fusion event spits out a fast proton or neutron, caught by two independent detectors. “Detecting these products independently, along with extensive background and control measurements, gave us confidence that the signals came from fusion,” Munday says.

As the team reduced the incident energy, they were surprised. “We observed the well-known exponential rate drop, but then the rates did not drop anymore but rather plateaued as we further decreased the ion energy,” says Schenkel. The plateau appeared below about 2 keV in both metals, and loading extra deuterium electrochemically roughly doubled the yield.

“This is an enormous relative enhancement, although the absolute fusion rate remains far too small for energy production,” Munday stresses. “The immediate significance of our work is therefore the discovery of a new physical regime in which the material actively influences the nuclear reaction, rather than the demonstration of a practical energy source.”

Welcome corroboration

Konrad Czerski, professor of nuclear and medical physics at the University of Szczecin, Poland, sees the result as welcome corroboration. “The Berkeley study represents an independent confirmation of the effect found by our research group over two years ago within Europe’s CleanHME project,” he says. His team saw a similar plateau in zirconium, palladium and titanium with a different technique. The palladium results of the two groups agree well, he notes, but the titanium data differ.

Czerski is not persuaded by the American team’s explanation, which attributes the plateau to unusually strong screening in the foil’s damaged surface layer. His group’s measurements, he argues, “demonstrate unambiguously that the yield plateau arises from fusion of deuterium at ordinary thermal energies, and the screening energy doesn’t change.”

The disagreement underlines how much remains open in the field. “The most important next step is to identify the microscopic origin of the low-energy plateau,” says Munday. This would involve untangling the roles of screening, surface damage and the way deuterium moves and gets trapped in the metal. The US team also wants to test whether light or crystal vibrations can affect the reaction rate. Near-term applications, he suggests, might include compact neutron sources rather than reactors.

Czerski has a bolder vision for the future. “The experimental setups and the results obtained can launch a new research field focused on materials and enhancing the electron screening effect in nuclear reactions,” he says – one that “can finally lead to commercial applications, and even possibly to construction of a new energy source.”

The research is described in Nature Communications.

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Women at high risk of breast cancer are more susceptible to developing cancers in the gap between routine screening exams. These so-called “interval cancers” tend to be fast-growing and account for 20% to 30% of all breast cancer cases.

To identify aggressive cancers that develop between scheduled screenings, researchers at Massachusetts Institute of Technology (MIT) have developed a point-of-care ultrasound system that generates high-resolution 3D images of breast tissue. The 3D portable ultrasound system for real-time examination (3D PURE) supplements mammography with its ability to detect anomalies reliably in dense breast tissue (in which mammography is less sensitive).

Guided by an easy-to-use visual interface, 3D PURE enables a nurse, a physician such as a primary care provider or gynaecologist, or even the patient herself to frequently perform longitudinal breast imaging.

Second-generation design

Principal investigator Canan Dagdeviren explains that this second-generation prototype overcomes limitations of a prior system designed by the MIT team, through advances in transducer design, acoustic materials and adaptive beamforming. These developments have enabled real-time wide-angle 3D imaging in a portable form factor, with improved image resolution to accurately identify cysts, solid masses, fibroadenomas and microcalcifications.

The ultrasound system comprises a newly designed 128-element box-shaped 2D transducer array incorporating a corner-gap offset geometry, which suppresses peak crosstalk by 3.73 dB at the corner-most element. This design prevents amplifier saturation, and supports operational transmit voltages of up to 24 V. The array is integrated into a compact multilayer electronics stack comprising preamplifiers, transmit electronics and a custom chirp data acquisition system.

There’s also a conductive backing layer (a toluene-diluted polyurethane matrix with a high percentage of tungsten and zirconia filler) that forms a continuous shielding layer around the elements, improving acoustic attenuation and providing electromagnetic shielding. The compliant mechanical nature of the material enhances acoustic damping, reducing ultrasound reverberations more effectively and improving signal fidelity.

“The addition of a backing layer to the ultrasound transducer is a key advantage to the system,” explains co-lead author Md Osman Goni Nayeem. “It provides both better directionality of ultrasound waves and better bandwidth, which improves the resolution and quality of the resulting images.”

The researchers also incorporated layered aberration-correction reconstruction (LACR), an adaptive 3D beamformer, into the 3D PURE design. LACR compensates for the heterogeneous speed-of-sound in the breast, which comprises glandular and fibrous tissues plus a superficial layer of fat. They believe that this represents the first wide-angle 3D ultrasound imaging system to implement aberration-correction beamforming.

“What we are trying to do is predict the speed-of-sound properties of the tissue being imaged, and then use that to reconstruct the image more accurately. We see up to a 10% improvement for the resolution just by applying this [beamforming] technique,” says co-lead author Shrihari Viswanath in a press statement.

The system is designed for ease of use. A visual user interface called “Mirror my First UltraSound” (MyFUS) guides users to reliably reposition the ultrasound probe at the same anatomical location during repeated imaging and long-term monitoring. Meanwhile, a wide field-of-view minimizes the number of scans needed to cover the entire breast.

The team undertook an in vitro study comparing the performance of the 3D PURE system with that of a conventional 2D handheld ultrasound system (HHUS). Ten study participants imaged a breast-shaped tissue phantom embedded with sub-millimetre targets. Nine of the 10 participants showed improved microtarget detection efficiency with 3D PURE relative to the conventional system – identifying more of the targets using 3D PURE (79.7%, compared with 60.7% for the 2D HHUS), with a higher detection efficiency (14.02% of available targets per minute, compared with 9.58%).

The researchers also worked with radiologists to assess a variety of breast anomalies in vivo. The radiologists verified that the 3D PURE system could accurately visualize calcifications, cysts, implants, fibrous tissues and solid masses within a large volumetric field-of-view. The researchers independently validated the system’s accuracy when imaging dense fibrous breast tissue and rib structures.

Seven volunteers with no prior experience of using an ultrasound system tested the MyFUS visual interface. After initial instruction by an ultrasound technician, they were able to repetitively position the probe at a specific location on their breasts, achieving a 94.10% mean overlap value on frontal projections, and 87.42% on side projections. This test reconfirmed that novice users could achieve reproducible longitudinal monitoring results with the aid of the visual interface.

The researchers now hope to create an interface for use with mobile phones or tablets. This type of system could make breast ultrasound more accessible to patients in economically constrained countries lacking adequate breast cancer scanning and regions with shortages of trained ultrasound technicians.

“The high operator dependence of conventional ultrasound is a barrier to its use in decentralized or home-monitoring settings,” the researchers write. “The MyFUS vision interface transforms longitudinal monitoring from an expert-driven procedure to a self-guided, reproducible process that can be used by novice users. This reproducibility is vital for longitudinal monitoring in limited clinical settings, to regularly track the growth of an anomaly or the response of a tumour to therapies without visiting clinics.”

The 3D PURE system is described in Nature Communications.

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Every breath we exhale carries a complex chemical narrative written in thousands of volatile organic compounds (VOCs). These tiny molecules, produced by human metabolic processes and invading pathogens, hold immense diagnostic potential. Yet, translating this molecular cloud into a definitive medical diagnosis has long faced an analytical bottleneck. Now, an international team of physicists from Botswana and South Africa has harnessed machine learning to decode these complex signatures, offering a rapid, non-invasive pathway to detect tuberculosis (TB) directly from human breath.

Breaking the analytical bottleneck

Traditional gas chromatography-mass spectrometry (GC-MS) excels at separating complex molecular mixtures based on volatility and mass-to-charge ratios. However, a single breath sample generates thousands of overlapping spectral peaks. Manually sifting through this dense landscape is a painstaking, time-consuming process.

To find a faster, more systematic approach to molecule identification, researchers in the Nano –Breath taking group led by George Chimowa from Botswana International University of Science and Technology (BIUST) collected breath samples from three distinct cohorts: patients with active TB, individuals with multidrug-resistant TB (MDR-TB), and healthy control volunteers.

Standard analytical pipelines often rely on aggressive data pre-processing to smooth and simplify the GC-MS spectra. However, this filtering risks erasing subtle, low-concentration molecular features that might hold critical diagnostic clues. Bypassing this limitation, the BIUST group fed a high-dimensional dataset of 1867 spectral features (from 87 breath samples) directly into four competing supervised machine-learning algorithms: decision trees, random forest, k-nearest neighbours, and support vector machines (SVM). The researchers published their findings in Discover Artificial Intelligence.

Geometric optimization avoids the pitfalls of high-dimensional data

The team found that the linear SVM classifier led the algorithmic comparison, distinguishing among the three patient cohorts with 93% accuracy.

This performance stems from how the algorithm handles high-dimensional data spaces. While distance metric models often suffer from overfitting errors, where experimental noise is misidentified as a meaningful diagnostic signal, SVM relies on geometric boundary optimization to separate classes.

Much like clearing a wide highway down the centre of two opposing crowds, it identifies a hyperplane that maximizes the margin between groups. Instead of tracking every individual in the crowd, the algorithm relies solely on a sparse subset of border points known as support vectors. By focusing strictly on these boundary “guards” and ignoring the background movement, this approach completely isolates the classifier from the noise inherent to the surrounding high-dimensional feature space.

Beyond raw classification accuracy, the model yielded a crucial insight for future clinical applications. It pinpointed a specific window within the gas chromatogram, a retention time between 10 and 30 min, where the most diagnostic, high-variance VOCs elute. This 20-min window corresponds to medium- and large-molecule VOCs, including specific chemical biomarkers associated with TB, such as tridecane, decane and O-cymene.

By demonstrating that these vital diagnostic features are concentrated within this single slice of data, the physicists have shown that future diagnostic hardware can be specialized, eliminating the need to analyse the entire spectrum. Narrowing the focus to this specific elution window can drastically shrink data-processing times and maximize instrument throughput in clinical settings.

AI and the future of medical diagnostics

TB remains one of the world’s deadliest infectious diseases. Traditional diagnostics rely heavily on slow sputum cultures and backlogged laboratory queues, delaying critical treatment. A rapid, non-invasive breath test powered by an optimized physical classifier offers an ideal alternative for resource-limited settings where laboratory infrastructure may be scarce.

While the researchers emphasize that larger validation trials are required, the work signals a profound shift in medical diagnostics. It mirrors advanced data-modelling techniques used in engineering, such as those predicting structural degradation in self-healing aerospace composites.

By fusing analytical physics with artificial intelligence, this research points to a future where immediate, automated bedside disease detection could be rapid, accessible and driven entirely by the mathematical profiling of a patient’s breath.

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If you’ve ever kept a drink cool on a hot summer day by placing it inside a frozen, gel-filled sleeve, you’ll understand the appeal of phase change materials (PCMs). The reason these sleeves work so well (and so much better than simply putting your drink in a cold bath or cool room) is that the solid inside them has a high latent heat, meaning it can absorb relatively large quantities of energy before melting and beginning to warm up.

But what if surrounding your drink with a frozen PCM isn’t enough? What if you want to cool your drink more quickly and evenly? One option would be to create a PCM sleeve with fin-shaped extensions that protrude into your drinking vessel. These fins would cool your drink – or, equivalently, allow your drink to melt the PCM – much more efficiently than a simple sleeve. But what should the fins look like? How far apart should they be? And how many of them do you need?

These are the questions that Paolo Proia, Mauro Sbragaglia and Giacomo Falcucci considered in a study published in EPL – though not with the aim of keeping their drinks cold. As researchers at the University Tor Vergata of Rome, Italy, Proia, Sbragaglia and Falcucci are interested in PCMs that store and release heat like a battery. Such materials are useful in fields such as electronics and refrigeration where heat is a common byproduct. Other applications include maintaining the efficiency of solar panels by preventing them from getting too hot and keeping buildings cool in the daytime via insulation.

Physics World spoke with them about their work.

What was your motivation for doing this research?

Our interest in PCMs stems, in part, from our interest in their many applications, especially in the ecological transition to less carbon-intensive fuels. PCMs are particularly good at managing heat in hydrogen storage with metal hydrides, for example, because storing hydrogen in these materials produces heat, while releasing the hydrogen requires it. Using a PCM to store the heat of the adsorption process and give it back during the release means that the produced heat doesn’t go to waste. Instead, it improves the efficiency of the process.

We’re also fascinated by the complexity of the equations involved. The coupling of fluid and temperature dynamics already causes interesting phenomena such as convection. By adding a phase transition to the mix, you introduce a moving boundary that complicates the system even more, both phenomenologically and analytically, since the describing equations must account for it.

We started this paper as a way of extending our previous work on the insertion of fins inside a PCM to three dimensions. PCMs are exceptionally good in latent heat but severely lacking in sensible heat; in other words, they store heat well, but they absorb and release it poorly. Fins are useful in relieving this flaw since they enhance the heat transfer surface and provide a horizontal heat source, which is instrumental for the development of convection, the main driver of heat transfer in this kind of system. By switching to a 3D system, we had more freedom to explore complex layouts of multiple fins and the importance of their relative position.

What is the most important advance in the paper?

The most important result is that naively inserting fins too close to each other can cause interference. If there are overlaps in the fins’ “influence zone”, the system will waste energy by, in effect, trying to melt something that was already molten from heating by a nearby fin. Moreover, by comparing a single fin and multiple fins with the same total surface, we found that the latter configuration benefits from the gaps between the fins. This is because the substance in these gaps melts early and starts acting as an extra heating surface, contributing to the development of bigger convective structures.

Why is it so challenging to model melting in phase change materials in 3D?

Beyond the analytical requirements we already mentioned, the success of this type of modelling depends on having a resolution that is high enough to capture correctly all the phenomena in the system. This means the number of computational sites N must be sufficiently large. In 2D, we “only” have N² sites to model, but in 3D, this scales to N³. That creates a challenge because making N too large would severely slow down the simulation. Moreover, we must be sure to respect the restraints on the physical parameters for which the lattice Boltzmann method is a correct approximation of the equations involved. So, we underwent a thorough validation process to pinpoint the best parameters for the algorithm.

What do you plan to do next?

First, we’d like to further optimize the code. The main bottleneck is the speed of a single iteration. Ideally, we’d like to study a wider range of layouts and physical conditions, but with the code we have now, that would impact heavily on performance. For example, a slower-melting substance requires more iterations to completely melt, which translates into more real-life time to model, sometimes outside the limits of feasibility. This problem would obviously be solved if we can make a single iteration faster.

Another issue we have is that some ranges of physical parameters can make the simulation unstable. Fortunately, there exist some remedies to this, and we plan to eventually adopt them.

Finally, we would be happy to see other researchers use these findings in their own optimization studies on fin shapes and spatial layouts. It would also be very interesting to see someone study this problem from an analytical angle or to see some experimental validation. In the medium term, we are planning to conduct our own experiments to use as a benchmark for our computational results.

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Engineers are constantly striving to improve the safety and performance of electric vehicle (EV) batteries. Much effort has been put into developing new electrode materials over the years, but future improvements may not follow the same path and may just be as simple as utilizing physical pressure.

A recent study, led by researchers at the University of Cambridge, suggests that EV batteries could be made to last up to twice as long, by applying the right amount of pressure to the electrodes. It is, however, a fine balancing act, as too high or too low a pressure can cause the battery to fail. To employ this approach in real world systems, engineers will need to make sure that the process is easily repeatable without significant pressure error, but it’s an interesting avenue of battery engineering that has come to fruition.

“We carried this work out to improve the sustainability of batteries,” says Michael de Volder, one of the lead researchers on the study. “Given that we are not very good at recycling batteries, extending the lifetime of batteries reduces the need for mining critical minerals for making new batteries and therefore improves their sustainability.”

For their study, reported in Nature Energy, the researchers developed a dilatometer with pneumatic bellows to apply pressure to the electrodes. The bellows act like a clamp to maintain a uniform and constant pressure on the electrode, while a sensor detects small volume changes that occur as the battery charges and discharges.

The researchers tested their electrode pressurization approach on commercial nickel manganese cobalt (NMC) lithium-ion pouch batteries (which have a flexible packaging), without changing their electrolyte or electrode composition. By using commercial batteries with a standard setup, they could test them fairly under different pressures.

“In this work we optimized how hard battery anodes and cathodes should be pushed together to maximize the lifetime of batteries,” de Volder tells Physics World. “Importantly, we also unravel which degradation mechanisms kick in if you press too hard, or not hard enough.”

Doubling battery lifetime

The researchers found that increasing the stack pressure fourfold over typical initial values used in conventional coin cells – to an optimal pressure of 12.5 bar – doubled the lifetime of the NMC811 cells. They compared the results with NMC cells tested at an extra-low pressure of 1.5 bar, a low pressure of 3 bar, a medium pressure of 6.5 bar and a high pressure of 37.5 bar.

Different degradation mechanisms emerged at high and low pressures outside of the optimal pressure zone. Low stack pressure accelerated cathode cracking, causing an increase in transition metal dissolution and excessive formation of the solid electrolyte interphase (SEI) layer. The cracking is likely due to a small number of particles bearing most of the mechanical load, leading to localized high-stress concentrations that initiate crack propagation.

Higher stack pressures, meanwhile, caused increased lithium plating on the anode. The team observed that the electrode thickness reduced during initial cycling but then underwent rapid thickness growth. When the electrodes are at their thinnest, they have a lower porosity that limits lithium transport, leading to higher overpotentials and higher lithium plating. This increases the amount of “dead” lithium and reduces the usable lithium inventory in the battery, causing it to degrade faster.

“We found that when the pressure applied to battery cells is sub-optimal, certain dangerous degradation processes can be accelerated. So, in a way, pressure optimization might improve the safety of batteries. However, more research is needed before we can draw reliable conclusions on this front,” says de Volder.

The pressurization results in this study are still in the early stages, but if shown to be viable at scale in commercial systems, could help EV batteries to last longer. In theory, this could give second-hand EVs a higher market value as the vehicle will have a longer battery life when sold. Additionally, if EV batteries can last longer, it will reduce the pressure on lithium mining operations and reduce the amount of raw material required for battery manufacturing (assuming the same demand) – something that is becoming an issue due to the skyrocketing price of lithium.

Cambridge Enterprise, the university’s innovation arm, has filed a patent, so the research team and university obviously see commercial viability in the process. When asked about the team’s future plans, de Volder tells Physics World that “we studied pressure optimization for one specific battery chemistry, but we anticipate that gains can be made in the lifetime of other battery chemistries too”.

The post Pressurizing EV battery electrodes could make them last longer, if it’s done right appeared first on Physics World.

This episode of the Physics World Weekly podcast features Antonia Seymour, who is chief executive of IOP Publishing.

Seymour has more than 30 years’ experience in a publishing industry that has evolved significantly from the days of paper journals to today’s sophisticated digital technologies.

In this interview we explore how scholarly publishers are responding to the rapid growth in research output, the rise of artificial intelligence and the increase in threats to research integrity.

A wholly owned subsidiary of the Institute of Physics, IOP Publishing produces more than 100 scholarly journals as well as Physics World.

The post How scholarly publishers are safeguarding trust in science appeared first on Physics World.

To play, click or drag one or more tiles to move them into the empty space. Repeat until you have reconstructed the image.

Image courtesy: iStock/Muhammed Zeynel Ozturk

Fancy some more? Check out our puzzles page.

The post Identifying maximum viscosity: a slide puzzle appeared first on Physics World.

Physicists in the UK have reacted with dismay following the decision by the Science and Technology Facilities Council (STFC) to cancel funding for several high-profile international projects. The Institute of Physics (IOP), which publishes Physics World, says that the axing of support threatens the UK’s international reputation as well as the ability to attract people into the subject.

The STFC cuts come after the council announced late last year that its core annual budget would rise by only £7m to £842m over the four years from 2026 to 2030. One of seven research councils within UK Research and Innovation (UKRI), the STFC runs the UK’s national facilities and supports particle physics, astronomy and nuclear physics (PPAN) research in the UK.

In a strongly worded statement, IOP president Paul Howarth is now urging the government to review “this ruinous set of decisions”, calling the cuts a “terrible blow” that will do “real damage” to the UK’s scientific reputation and put future economic growth at risk.

“Despite reassurances, physics has not been protected, crucial facilities remain under threat and jobs are being lost,” says Howarth. “Scientific capability that has taken years to build up is being put at risk by these decisions – it undermines a number of our most important international collaborations and could put a whole generation of young people off a career in science.”

Balancing the books

Although UKRI has received a record £39bn investment across the four-year period, it said last year that projects at STFC would need to be cut given inflation, rising energy costs as well as “unfavourable movements in foreign exchange rates”. Together, the STFC’s annual costs are projected to rise to over £1bn per year by 2030, forcing it to find ways to balance its books by 2029.

Earlier this year, the STFC said it would have to cut its core science budget by at least 30% over 2024/2025 levels. UKRI also noted it would stop funding two UK facilities – the Relativistic Ultrafast Electron Diffraction and Imaging facility and the C-MASS mass spectrometry centre. A UK-led upgrade to the LHCb experiment at CERN and support for the Electron–Ion Collider at Brookhaven in the US would be axed too.

That announcement caused significant distress within the physics community, prompting the heads of UK university physics departments to publish an open letter to then science minister Patrick Vallance, expressing their “deep concern” about funding changes adding that such cuts cause “reputational risk”.

UKRI then carried out further consultation with researchers and the STFC’s expert advisory bodies, with the results of this “funding prioritisation exercise”now revealed. There is some good news for STFC-funded “discovery-led” PPAN research, which physicists had feared could be cut by a third. Following lobbying, UKRI says this work is being “protected”, although it will still fall by 2.7% over the next four years.

Under attack

While facilities such as Diamond Light Source, the ISIS Neutron and Muon Source, and the Central Laser Facility will not be mothballed, the STFC’s budget for multidisciplinary facilities will reduce by 15% over the next four years to save £28m. As a result, ISIS will have to reduce operational time at the facility.

Yet the STFC warns that if saving and income targets for the programme are not met by 2028 then further action could be taken, which could involve closing a multidisciplinary facility.

STFC’s national laboratories and estates budget fares slightly better, falling by 8% over the four-year period, but individual facilities will be hit harder. The operational budget of the Boulby Underground Mine, for example, will be slashed by 40%.

Particle fever

The STFC insists that subscriptions for international projects, such as CERN and the European Southern Observatory, will remain protected despite their costs expecting to rise by 19% over the next four years. But other projects, including the EIC as well as the LHCb upgrade, will not be funded. The latter is expected to operate until 2033 by which time it would have reached the end of its lifetime after years of intense radiation damage.

An upgrade was planned so that it could take advantage of the upgrade to the LHC – the High-Luminosity LHC (HL-LHC) – and offer an order of magnitude increase in luminosity over upgrade I.

Tim Gershon from the University of Warwick, who became international spokesperson for the  collaboration this month, says that the outlook for STFC-funded science is “grim”.

“With a 15% cut last year and an outlook that sees funding shrink further due to inflationary pressure, not even excellent-rated and internationally-leading science like LHCb can be supported,” he adds. “LHCb is the canary in the coalmine for the future sustainability of particle physics and astronomy research.”

Gershon states that the decision to cut UK involvement in LHCb will throw away the leadership it has built up. “Not only is this a tragedy for researchers and engineers who have dedicated their lives to making LHCb one of the most successful experiments in history, it destroys opportunities for current and future students to be involved in world-leading scientific discovery,” he adds.

This is a short-sighted move, to save a tiny fraction of the overall UK science budget

Catherine Haymans

Gershon says it will take some time to understand what the UK’s decision means for the upgrade and how other funding agencies will react but without UK expertise it will be hard to progress given the UK is the largest partner in LHCb with a 20% stake.

“Ultimately, the LHCb Upgrade is an essential part of the full exploitation of the HL-LHC, which is the top priority of the European and CERN strategies for particle physics,” adds Gershon. “We are determined to deliver the best detector that is possible within the available resources. But such a major change to the level of expected resources makes this extremely difficult.”

Peter Millington, a particle physicist from the University of Manchester, says that the outcome is “bad news” for accelerator physics and the applications that it fosters, particularly in medical physics. “It is completely at odds with UK priorities across all industrial strategy growth-driving areas, while also eliminating skills pipelines pivotal to a wide range of sectors and eroding the UK’s long-held position as a global scientific leader.”

Astronomy woes

Astronomy is another area that is bearing the brunt of the cuts. The UK contribution to the e-MERLIN network of seven radio telescopes, which includes the iconic Lovell telescope at Jodrell Bank in northern England, is also ear-marked for cancellation. Its funding will now run out in 2028 and the move not only threatens e-MERLIN but also the future of Jodrell Bank , which the Royal Astronomical Society calls a “deeply troubling development”.

Catherine Haymans, Astronomer Royal for Scotland, says she is “absolutely devastated” for those working on e-MERLIN.  “This is a short-sighted move, to save a tiny fraction of the overall UK science budget,” she says. They are now considering contacting the new Department for Business, Innovation, Science and Trade to reverse the decision.

Other astronomy cuts include the UK withdrawal from the James Clerk Maxwell Telescope located in Hawaii as well as 20% cuts for the UK’s Square Kilometre Array Regional Centre and activities at the Vera C Rubin Observatory in Chile, which recently began a 10-year survey of the universe.

Jim Wild, president of the Royal Astronomical Society, notes the cuts are “devastating news” for UK astronomy. “At a time when technological innovation is crucial to our country’s prospects, discarding unique, globally significant observatories threatens both our scientific future and the inspiration of future generations of astronomers,” adds Wild.

Michele Dougherty, executive chair of the STFC, who is also Astronomer Royal, says that the situation requires “tough, but necessary decisions”.

“After listening to our community we have protected core discovery research within PPAN, through a more focused portfolio that safeguards postdoctoral researchers, protects PhD opportunities and maintains the UK’s international leadership.” adds Dougherty, who stepped down as president of the IOP in January over the conflict of interest with her position at the STFC. “These are never easy choices, but we have made what we feel are the right decisions to bring STFC to a sustainable financial position by 2029/30″.

The post Future of UK physics threatened by ‘ruinous’ funding cuts, says Institute of Physics appeared first on Physics World.

A few years ago, I was lucky enough to see the Bayeux Tapestry – the famous embroidered cloth depicting the Norman invasion of England in 1066. More than 900 years old, this historic piece of art is only 50 cm wide but more than 68 m long. It’s also extremely fragile, which why I was astonished when I heard that the Bayeux Tapestry was going to leave its home in Normandy and be transported across the English Channel to the UK.

The loan of the artwork, which was agreed between former British prime minister Keir Starmer and French president Emmanuel Macron last year, has now taken place. The tapestry arrived under police escort on 10 July and will be on display at the British Museum in London from September 2026 until July 2027. It is the first time the tapestry has been back in England, the country where this linen cloth was originally made.

I’m fascinated by how non-invasive optical techniques have been crucial in advancing our understanding of the tapestry

So what’s all this got to with physics? Well, I’m fascinated by how physics – and specifically, non-invasive optical techniques – have been crucial in advancing our understanding of the tapestry and its historical significance. Thanks to physics-based equipment developed by hi-tech manufacturers, we’ve learned about how the Bayeux Tapestry was initially made, what damage it subsequently suffered, how it was repaired, and the nature of its current condition.

Such information is vital not only for increasing our historical awareness, but also for current conservators who want to understand the tapestry’s underlying condition and find out how to preserve it for future generations. And before the pedants write in, yes I know that while it’s known as the Bayeux Tapestry, technically it’s an embroidery. That means it was created by stitching woollen threads onto a linen backing, which is helpful to know when reviewing the physics involved.

Optical sleuthing

The beauty of using optical methods to study the Bayeux Tapestry is that they are non-destructive and non-intrusive – and so can typically be applied in situ. In 2017 a three-year project was started, in which conservationists used high-resolution 2D imaging, photogrammetry, multimodal scanning and advanced image reconstruction techniques to determine the tapestry’s condition and conservation needs. The project revealed considerable information about how this artwork was created and modified over time.

Thanks to these high-resolution images, we now have a single digital map of the entire tapestry, making it possible to zoom in and look at individual threads. It’s yielded information such as the width of stitches and the positions where the wool threads cross the original linen background. As a result, historians now believe the tapestry was made by a single group of embroiderers, who – knowing the skills that existed at the time – were probably based in Canterbury, UK.

Techniques such as infrared spectroscopy and fluorescent and reflection ultraviolet imaging have revealed information about what’s underneath the surface of the tapestry

From the size and direction of the stitches, we also think the outlines of the figures were stitched first, with the shapes filled in afterwards using coloured wools in a strict, specific order. Meanwhile, techniques such as infrared spectroscopy and fluorescent and reflection ultraviolet imaging have revealed information about what’s underneath the surface of the tapestry. In particular, they’ve located the presence of stains such as glue, wax (dripped from candles that lit the tapestry) and even oil from the hands of people who touched it.

Infrared light passing through the dark-coloured wools have also revealed original sketch lines that were drawn on the linen base before the wool stitching started. It reveals the original artist’s draft, likely to be someone familiar with manuscript drawing – perhaps an illuminator of religious books.

3D imaging with photogrammetry

Researchers in France, led by Stéphane Le Mouélic from Nantes University, who originally did a PhD in astrophysics, have also used computer software to combine more than 440 overlapping 2D photos taken from multiple angles to create a detailed 3D model of the Bayeux Tapestry (J. Cult. Heritage 71 211).

It digitally “irons out” all the sags and wrinkles in the line fabric, recreating the original, “flat” tapestry and allowing the original physical shape of the artwork to be revealed for the first time. The 3D model can be viewed for free at the Bayeux Museum website, allowing historians, researchers and members of the public to study it without having to handle the delicate material.

Physics-based techniques have also allowed us to deal with the fact that parts of the fabric have been repaired over the last 900 plus years. Some of those repairs used non-authentic dyes and colours, while others covered up the original stitching. But using computer vision and image processing, threads that were added later can be subtracted digitally, providing a clearer, corrected view of what the original tapestry looked like.

Finally, optical tools can help keep the tapestry safe for future generations. Museum curators need to know if the cloth is sagging, tearing, or changing shape over time. Instead of putting heavy tools on the cloth, lasers can scan the cloth to accurately map of the contours of its surface. By repeating this exercise every few years, conservationists can spot if any part of the cloth has stretched or sagged, enabling minor problems to be rectified before they end up causing significant damage.

Without the huge amount of investigative and restorative work carried out, the Bayeux Tapestry would never have been allowed to make the journey to London

In 2025 Le Monde newspaper reported that experts had, over the previous five years, meticulously documented 24,204 stains, 9646 holes and 30 tears in the artwork. Without the huge amount of investigative and restorative work carried out, the Bayeux Tapestry would never have been allowed to make this year’s journey to London. Advanced and detailed optical measurement has “de-risked” the tapestry’s trip.

Tickets to the British Museum exhibition are reportedly being snapped up faster than those for Glastonbury. So if you don’t get to see the tapestry in person, feel free to marvel at this wonderful historical artwork by checking out the interactive online digital copy. It really is physics and history in the making.

The post The Bayeux Tapestry: how optical techniques have let this artwork come home appeared first on Physics World.

Quantum theory is one of humanity’s great intellectual achievements, radically transforming our understanding of nature at the deepest level while delivering unprecedented technological advances. We have thus always felt it a great pity that most young people never get the opportunity to engage with the theory at a substantive level.

The solid-state physicist David Mermin, who has studied the fundamentals of quantum mechanics, once memorably wrote of quantum theory: “We now know that the Moon is demonstrably not there when nobody looks”. It was a comment that certainly captures the imagination, but it is difficult to appreciate what he meant meant without engaging with the mathematics that lies behind it.

In an attempt to see if we could change that, we ran our first Quantum in Pictures programme at the University of Hertfordshire earlier this month. A five-day, in-person course, it was attended by about 45 students aged 16–18 and was built around Quantum Pictorialism – a diagrammatic approach to quantum theory pioneered by Bob Coecke from the University of Oxford and collaborators.

The crucial point is that the pictures aren’t illustrations of some more fundamental mathematics hidden underneath. The pictures are the mathematics. A rigorous graphical calculus built from spider diagrams enables students to reason directly about quantum processes. Since this diagrammatic formulation is fully equivalent to the usual Hilbert space formalism, the students were doing quantum mechanics for real.

We felt truly privileged to share the mysteries of quantum mechanics with a fantastically friendly, interested and diverse cohort from schools across south-east England. What struck me was how readily they engaged with the material: asking excellent (and sometimes rather challenging) questions, debating ideas and working collaboratively through the problem-solving sessions.

The graphical problems proved particularly popular, with repeated cries for “more spider diagrams!”. The course was deliberately ambitious, but by the end, they were able to work through the complete quantum teleportation protocol. Indeed, one student was confident enough to get up and reason through it for the whole class (something we certainly would not have dared to do at their age).

As Maya, a year-12 student from Highams Park Sixth Form in London, put it: “I really enjoyed seeing how ideas in quantum physics could be explained through simple pictures and diagrams. I was surprised that concepts like quantum teleportation, which seemed very complicated at first, could become much easier to understand through this approach. The programme has made me even more interested in studying physics and exploring quantum theory in the future.”

The approach also worked for students without a traditional mathematics or physics background, such as Andrew, a year-12 student from Sir John Lawes School in Harpenden.

“The programme was captivating,” he said. “The concept of using diagrams was innovative and explained things in a logical manner to help me understand topics such as quantum teleportation. The programme showed the stark differences between classical and quantum physics through real-world examples, enriched by talks from industry experts and pioneers with different backgrounds.”

Muhammad Hamza Waseem, who helped develop the programme and joined us on the final day, captured the atmosphere perfectly. “I found the enthusiasm, curiosity, and irreverence of the students very inspiring,” he said, “and I hope that they take the same spirit into their university education and beyond.”

That sense of joy and excitement was, for me, the lesson of the week. We’ve been thoroughly convinced that quantum theory isn’t intrinsically beyond the reach of curious 16-year-olds. We just need to give them the right mathematical language. The next step is an optional graduate-level exam, which will put that claim to the test. Watch this space.

• The authors would like to thank staff, researchers and students from the University of Hertfordshire who volunteered their time to make the programme possible. They are also grateful to Ian Loffler, Bob Coecke and Muhammad Hamza Waseem for their support and inspiring contributions.

The post Can a 16-year-old really understand quantum teleportation? appeared first on Physics World.

Science is often easier to learn and understand when its abstract ideas are presented through the lens of our everyday world. Indeed, a key challenge for science teachers is to make the subject as interesting as possible to students, usually by showing its applications to real-world problems. As a former college lecturer turned science journalist, Trisha Muro is very well suited to this task.

To introduce her new book It’s (Just) Rocket Science: Exploring Physics Through Spaceflight Missions, Muro recalls how, while teaching high-school physics, she had a student drop out of her course because they “thought it would be more like ‘story’ physics”. Muro wasn’t exactly sure what the student meant, but the phrase stuck with her over the years, eventually leading her to write this book. Within its pages, Muro presents quintessential physics concepts in the context of spaceflight. She touches upon everything from the Apollo space programme to the Mars rovers, to provide the narrative aspect that makes abstract science relatable.

I’d argue that rather than story, the examples she uses in the book are more like case studies, as there is not much of a continuing narrative. Indeed, I couldn’t help but wonder if by “story”, Muro’s student meant science-fiction physics rather than real-life examples, but that’s semantics. What Muro has written is a very effective guide to all manner of basic physics that draws upon all her experience as a physics teacher and all her skills as a science writer.

In It’s (Just) Rocket Science, each chapter features an interview with one or two scientists (refreshingly, mostly women) providing insights into how the missions that they work on employ physics. There are some clear and concise explanations and neat analogies throughout. Muro provides a treatise on general relativity by highlighting the Hubble Space Telescope’s observations of gravitational lensing. She also includes a fascinating explanation of momentum via the physics of NASA’s DART mission, which impacted and deflected the little asteroid Dimorphos. Muro’s description of the electromagnetic spectrum is aided by discussions about interplanetary radio communications, the spectroscopic measurements of Venus that the forthcoming DAVINCI mission will make, and the X-ray vision of the Chandra Observatory.

The chapters I enjoyed best were in part two of the book where, as a self-confessed Space Cadet, Muro talks about how she attended a NASA Space Camp in the 1980s. (She is donating 100% of the proceeds from this book towards funding scholarships for children to attend the camp too.) In this section, Muro takes us through the science of rocket launches and landing on other worlds. She explains how the balance of forces as described by Newton’s laws of motion will enable NASA’s Dragonfly helicopter mission to fly on Saturn’s moon Titan. I especially liked the ice-skating analogy that Muro used to describe gravitational slingshots. Imagine two ice skaters, one being yourself and the other a champion speed skater, writes Muro. You get a head start, then the speed skater races up alongside you, takes your hand just for a moment and then lets you go, giving you an energy boost.

Muro gets through an impressive amount of science in a short space – the first 50 pages alone are full of heavy topics such as Kepler’s laws of orbital motion, planetary transits, exoplanet science, Lagrange points, gravitation, the three-body problem, general and special relativity, the concept of space–time, the speed of light, the Doppler effect, and even an equation or two. Phew! That’s a lot of science, and while at times it might feel dense to the uninitiated, at no point is it too confusing or impenetrable for the science or space enthusiast.

Muro’s willingness to include equations (there are even two interludes featuring derivations) reminds us of her teaching background. I found it refreshing to see maths presented front and centre when most popular-science books shy away from it, in an attempt not to lose readers. In this book, the maths isn’t complex and it is crucial in showing us why various physical laws work the way that they do.

One small issue for me was Muro’s decision to incorporate both imperial and metric units, which made for some confusing reading. In some instances, she mixes the systems in the same sentence – for example, giving a distance in kilometres followed by a weight in pounds, or a speed in miles per hour followed by energy in joules. Muro comments in the chapter about momentum and the DART mission that she has been using both systems to help readers become more comfortable with them. However, if the conversions between imperial and metric are not going to be given, then I’m not sure she really succeeds at making people more comfortable using metric.

If I were to nitpick further, I’d point out that when Muro strays from straight physics and engineering to astrophysics, some mistakes do crop up. These include stating that objects in the early universe are “red” because they have been cooling for billions of years. What is really happening is we are seeing them as they were long ago and their colour is the product of cosmological redshift, not temperature. Another is implying that gravitational waves are what cause the orbits of asteroids and comets to be perturbed. This ignores the fact that gravitational interaction from the planets, particularly Jupiter, is the dominant influence. However, these errors do not detract from the otherwise clear and correct explanations of the physics, which are easy to read and pitched perfectly for students below university level.

Overall, It’s (Just) Rocket Science is an excellent book that turns abstract physics into something more relevant. With the popularity of the recent Artemis II mission, the book’s focus on space missions will hopefully help it find an audience who will really take all that Muro has to teach on board.

• 2026 Johns Hopkins University Press £25.50 hb 384pp

The post Bringing physics down to Earth through rocket science appeared first on Physics World.

Many catalysts are made using core-shell nanoparticles, in which the core is a structurally important or inexpensive material and the thin shell surrounding it is an expensive metal such as platinum. Since catalytic reactions occur on the surface, this helps to reduce the amount of platinum required and therefore lowers costs. Crystal structures are described based on the smallest repeating unit of the crystal (the unit cell) using the Bravais lattice system. Three important crystal structures are face-centred cubic (fcc, atoms at the corners and faces of a cube), body-centred cubic (bcc, atoms at the corners and centre of a cube), and hexagonal close-packed (hcp, a hexagonal arrangement of atoms).

Different materials have different crystal structures; for example, platinum is fcc, many alloys are bcc, and magnesium and zinc are hcp. In core–shell nanoparticles, differences between the crystal structures of the core and shell mean that the atoms do not line up perfectly. This mismatch creates strain, which can significantly affect catalytic performance. In this work, the researchers explored how a platinum shell grows on a different crystal structure in a process known as heteroepitaxy.

They studied platinum shells (Pt, fcc) grown on cores made of ruthenium (Ru, hcp), palladium–copper (PdCu, bcc), and specially synthesised ruthenium with an fcc structure. It was found that each system accommodates the atomic mismatch differently. In hcp/fcc particles, some areas lined up coherently while others contained defects called dislocations, which formed networks in particles smaller than 10 nm. In bcc/fcc particles, both the core and shell stretched or compressed to fit together. In fcc/fcc particles, the matching crystal structures aligned more readily, but twin defects formed in which one region mirrored another.

Overall, this study shows that the way a Pt shell grows on a nanoparticle core is determined by a balance between the energies of the interface, shell, and core, with the system naturally adopting the lowest-energy configuration. These findings could help scientists achieve atomic-precision interfacial engineering, controlling the catalytic, mechanical, and electrical properties of core-shell nanoparticles.

Do you want to learn more about this topic?

PLP-Logo-2.png, find out more. Single metal nanoparticles: optical detection, spectroscopy and applications by P Zijlstra and M Orrit (2011)

The post Understanding core-shell nanoparticle growth appeared first on Physics World.

Quasicrystals are unusual yet relatively common materials.  They show up in lots of different places from alloys to colloids and even in meteorites. They have some ordered structure, but unlike ordinary crystals their patterns never repeat.

This mix of order and irregularity leads to interesting behaviour when waves move through them. In optical versions of these materials, light can become trapped or guided in ways that doesn’t happen in regular structures.

In a new study published recently, a team of researchers investigated what happens when light beams with a twist, called vortex beams, travel through quasicrystals that have been deliberately altered. They began with a classic pattern known as the Penrose tiling and then introduce large scale defects by removing or adding wedge shaped sections. This let the researchers tune the rotational symmetry of the structure and compare how light behaves in each case.

Using a standard model for how light travels through the material, the researchers showed that these modified quasicrystals can support new vortex states. These include two distinct types of vortex solitons, which are twisted beams of light that keep their shape as they travel rather than spreading out.

Usually, these light states require carefully tuned input power and are easily disrupted. What’s different in this case though is they form even with weak input and remain stable under small disturbances. This makes them far more applicable to real-world conditions.

These vortex beams can carry information in the amount of twist they have, providing an extra way to encode data alongside commonly used properties such as intensity or colour. If they remain stable as they travel, they would allow more information to be sent through the same optical system. This could be very useful in optical communication systems, where fast and efficient data transmission is essential.

The post A new way to trap and twist light inside quasicrystals appeared first on Physics World.

A new method of stabilizing radioactive molecules could open the door to sensitive searches for physics beyond the Standard Model. The approach, which involves cooling radium-bearing molecules to just above absolute zero, offers a tabletop alternative to experiments that use particle accelerators to look for violations of fundamental symmetries. According to lead researcher Nick Hutzler, a physicist at the California Institute of Technology (Caltech), US, it also shows that university laboratories can safely handle these radioactive materials, paving the way for similar studies at other institutions.

One of the greatest puzzles in physics is the fact that the early universe created more matter than antimatter. For decades, physicists have tried to solve this mystery (and others) by using particle accelerators to search for violations of nuclear symmetry at ever-higher energies. However, molecules that contain heavy radioactive nuclei could also act as super-sensitive sensors for symmetry violations – with the advantage that the equipment required to manipulate them generally fits in a single room, rather than an entire building.

Pear review

The basic idea is this: when electron orbitals overlap with a nucleus, the system’s atomic or molecular energy levels shift by tiny amounts that depend on the nucleus’ size and shape. Variations in nuclear structure due to symmetry-violating effects would therefore produce changes in the electron orbitals, and these changes could be measured with high-precision spectroscopy.

Asymmetric nuclei are ideal for this purpose because their lopsided shape makes small changes easier to detect. Radium, for example, has a pear-shaped nucleus, and radium-containing molecules offer additional advantages because the repulsion and attraction of neighbouring atoms further distorts the electron orbitals.

The downside is that radium is both radioactive and highly reactive, making it dangerous to handle without specialized equipment that is not present in standard university laboratories. It is also only available in extremely small quantities.

Sweet as candy

In the latest study, which is published in Science, physicists at Caltech and chemists at Johns Hopkins University and Michigan State University (all in the US) found a possible way around these obstacles. Their first step was to make radium stable and transportable. For this, they developed a process that resembles candy-making, though they do not recommend eating the results. By “caramelizing” small amounts of radium-226 in a solution of xylitol sweetener, they created a material they could transport in small quantities, keeping radioactivity levels low enough to comply with standard radiation-safety frameworks.

Next, they added their sticky radium “goo” to gold foil; installed it in a copper cryogenic cell; and cooled it to 4K using helium gas. They then used a laser to excite the radium into a chemically reactive state, allowing it to bond with targets such as hydroxide, deuteroxide and fluoride. Collisions with surrounding helium atoms further cooled these radium-bearing molecules into a mixture of only a few rotational and vibrational states. At this point, the team was finally able to perform the first-ever high-precision spectroscopic analysis of such molecules.

Opening doors

Hutzler acknowledges that several challenges remain before precision searches for symmetry violation can begin in earnest. Though theory predicts that these radium-bearing molecular species will be amenable to standard laser cooling and trapping techniques, no one has yet cooled them to ultracold temperatures. Another challenge will be to extend the process to other isotopes. Radium-225, for example, has a better nuclear shape for high-precision searches for symmetry violation, but it is also much more radioactive than radium-226, with a half-life of 15 days rather than 1600 years.

The team is also interested in studying the spectra of other radioactive species, with the aim of better understanding nuclear structure and chemistry at the extremes of the periodic table. A final possibility, Hutzler adds, would be to study other radium-containing molecules, as this would enable different precision measurements.

David DeMille, a physicist at Johns Hopkins who studies symmetry violations in atomic and molecular systems but was not involved in this research, calls it an “extremely promising way” to search for interactions that violate charge-parity (CP) symmetry. The efficiency with which the team converts solid-phase radium atoms into gas-phase molecules is a good sign, he adds, and extending the process to other radioactive molecules could help scientists understand species that have been observed astronomically.

However, DeMille points out that achieving ultracold temperatures poses additional challenges, including finding a way to release the confined molecules into a larger, much more complex experimental setup, without helium, while maintaining safe conditions. That said, he notes that the spectroscopic results are, in themselves, an important step towards reaching this ultracold regime.

The post Cold radioactive molecules offer a tabletop route to new physics appeared first on Physics World.

A new type of “photonic multi-lane highway” that can carry multiple topologically-protected optical signals at once – without the need for a bulky insulator  – has been demonstrated by researchers in China. The technology, which relies on a new type of material called a photonic valley half-semimetal to achieve topological protection, is currently at the prototype stage. However, the researchers believe that, if fabrication challenges can be addressed, the combination of spatial efficiency and topological robustness could be promising for future photonic technologies.

In the past 20 years, photonic topological insulators have become widespread for connections in devices such as on-chip photonic circuits because their edge modes can only conduct light in one direction and are therefore are inherently immune from scattering off imperfections. However, the protected edge mode of a topological insulator comes at a cost: the bulk must have an optical band gap, which means it must be opaque to the relevant frequency. Meanwhile, the photonic analogue of another concept from electronics has also become popular in optical waveguides. Gapless photonic semimetals – analogous to graphene –  can be placed between topologically distinct optical insulators to broaden the guided modes, but non-guiding insulating claddings are still required.

To address the fundamental trade-off between spatial efficiency and topological protection in conventional topological waveguides, researchers in the group of Che Ting Chan at the Hong Kong University of Science and Technology in China and their collaborators introduced a novel photonic structure called a photonic valley half-semimetal. Here, the valley degree of freedom refers to inequivalent local energy extrema in momentum space, which can be used as independent degrees of freedom for transport. Crucially, a single photonic valley half-semimetal plays a dual role via its two valley channels: one valley acts as a gapless semimetal that enables waveguiding, while the other functions as a topological insulator that provides a topological barrier for the corresponding valley mode in adjacent regions.

Four stacked layers

The researchers designed a waveguide comprising four stacked layers of a honeycomb structure made from interconnected rods of the magnetic material yttrium iron garnet, which interfered with the propagating photons. By altering the diameters of the rods or the magnetic field, the researchers  constructed four inequivalent photonic valley half-semimetal domains and arranged them in a specific periodic sequence. This creates adjacent domains that mutually insulate each other.

Xiaohan Cui is lead author on a paper in Nature that describes the research. She explains that the underlying topological physics is similar to that in a traditional photonic topological insulator.

“The important difference lies in how the mode is spatially implemented,” she says, “In a conventional photonic topological-insulator waveguide, two gapped bulk domains meet at an interface, and the propagating mode is tightly localized to that interface. Most of the surrounding insulating material remains inert, serving only as cladding.”

In the present configuration, however, the researchers were able to use the blocked valley as topological protection for unidirectional propagation in the neighbouring domain, and utilize this to create a four-lane highway, with two lanes in each direction, that could guide signals around sharp bends and through constrictions without backscattering or inter-lane crosstalk:

No wasted space

“The architecture transforms the usual narrow interface state into a set of directly adjacent, large-area waveguiding lanes. Consequently, no region of the device is ‘wasted’ as inert cladding,” explains Cui.

The team’s current device works for microwave radiation but the team says that the design could be adapted and extended to operate at higher frequencies.

“The present experiment is a proof of principle demonstration at microwave frequencies, so one clear next step is to move the concept towards higher-frequency, chip-scale integrated photonics platforms, thereby paving the way toward ultra-compact topological photonic circuitry,” says Cui.

The researchers believe application in the terahertz regime should be possible using magnetized semiconductors such as indium antimonide. However, non-reciprocal applications at higher frequencies could be challenging owing to the weakness of magnetic effects.

“The major experimental challenges will be to realize these higher-frequency designs while managing geometric complexity, fabrication tolerances, and propagation loss, and ensuring efficient coupling with practical sources, detectors and other photonic components,” she explains.

Quantum optician Mahmoud Jalali Mehrabad of Massachusetts Institute of Technology believes the work brings an important issue into focus. “A paper doesn’t always have to have the perfect solution as long as it highlights and really streamlines a key problem…To me this paper does that,” he says. “Spatial efficiency has been a problem in topological physics and the question is why? Is there any other way to destroy this trade-off? It shouldn’t be a side problem in the supplementary material of a paper – this is a big problem.” Whether or not the researchers can make their own solution viable, he says, “time will tell”.

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A new measurement of the ground-state hyperfine splitting in antihydrogen shows that it is identical to that of normal hydrogen to within four parts per million – two orders of magnitude more precise than previous experiments. Although the measurement by CERN’s ALPHA collaboration did not reveal any asymmetries between matter and antimatter, the result is nevertheless a milestone in the search for reasons why the universe appears to be made up almost entirely of matter, with only minute amounts of antimatter.

According to the Standard Model of particle physics, all matter particles have a corresponding antimatter particle that is identical to them in every way apart from their charge and magnetic properties, which are reversed. If this model is correct, then the Big Bang that formed our universe nearly 14 billion years ago should have generated equal amounts of antimatter and matter. But in that case, neither we nor almost everything else we observe should exist, because pairs of antimatter and matter particles annihilate each other whenever they collide.

“This apparent lack of antimatter in the universe remains one of the biggest mysteries in modern physics and suggests there is something about antimatter and matter that we do not understand,” says Timothy Friesen of the University of Calgary, Canada, one of the lead authors of a Nature paper on the new measurement.

Measuring antihydrogen

To look for subtle asymmetries that might explain why matter triumphed and antimatter all but disappeared, ALPHA is performing precise measurements on the simplest antimatter atom: antihydrogen, which consists of an antiproton bound to an antielectron, or positron.

These measurements take place at the CERN Antiproton Decelerator Facility using the ALPHA-2 antihydrogen apparatus, which is designed to prevent antihydrogen from coming into contact with normal matter. It does this by confining the antimatter within a cylindrical Penning–Malmberg trap under an extremely high vacuum and surrounded by strong superconducting magnets. These magnets suspend the antimatter in the trap so that it does not touch the walls of the container it is held in, preventing it from annihilating before measurements can take place.

In the latest work, the ALPHA collaboration focused on a parameter known as hyperfine splitting. This splitting occurs because magnetic interactions between the spins of the antiproton and positron cause the positronic ground state in antihydrogen to split into four sublevels, which the researchers label |a⟩, |b⟩, |c⟩ and |d⟩.

In hydrogen, the magnitude of this hyperfine splitting has been measured extremely precisely – we know its value to within a few parts per trillion – and it is particularly sensitive to the structure of the proton. Measuring this splitting in antihydrogen with the same precision would therefore be an excellent way of searching for differences between matter and antimatter. Previously, however, the most sensitive measurements only managed a precision of 400 parts per million (ppm).

In pursuit of precision

To push beyond this level, the ALPHA researchers applied pulses of microwaves at frequencies between 28 GHz and 31 GHz to induce the positron spin flip transitions |c⟩ → |b⟩ and |d⟩ → |a⟩ between the hyperfine levels of ground-state (2S and 1S) antihydrogen atoms. By measuring the frequencies at which these transitions occurred, they could then calculate the hyperfine splitting energy.

“At a magnetic field of 1 Tesla, we measured the hyperfine splitting for antihydrogen to a precision of 4 ppm – a result that has allowed for one of the best comparisons of matter-antimatter symmetry in antihydrogen ever,” Friesen says.

While the new measurement is precise enough to push experiments into a regime that is sensitive to the structure of the antiproton, Friesen notes that it is still five orders of magnitude less precise than comparable measurements in ordinary hydrogen. “The comparisons at this level of precision with matter hydrogen are identical, and our current models of physics therefore still hold,” he says.

The team does have some ideas for further improvements. “To push the measurement to improved precisions we are aiming to induce antiproton spin flip transitions, since these can be less sensitive to magnetic field inhomogeneities, which are our biggest systematic uncertainty,” Friesen explains. “This, combined with laser cooling the antihydrogen samples to reduce the width of our spectroscopic line-shapes, could help improve the precision by at least another factor of 100.”

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At what point does a material become so viscous that it cannot flow? The question is a tricky one because some apparently solid objects are not as rigid as they seem. A glacier, for example, may look immobile, but when viewed over long-enough timescales, its slow flow becomes apparent.

Now, thanks to satellite observations of tectonic plate deformations as well as physical and geodynamic modelling, geophysicist Masaki Yoshida of Ritsumeikan University, Japan, claims to have found an answer. The upper limit for viscosity, he says, is 10²⁸ Pascal-seconds (Pa s), and the new boundary could yield insights into Earth’s geodynamics.

Viscosity is a measure of a material’s resistance to flow. Gases such as air and hydrogen have a viscosity of 10^-5 Pa s at room temperature; the viscosity of liquid water is 10^-3 Pa s; and glaciers have a viscosity of 10¹³–10¹⁷ Pa s depending on factors such as temperature, stress and microstructure. At the upper end, Yoshida says that the long-held view, based on rock deformation experiments, is that the viscosity of tectonic plates at the Earth’s surface (where temperatures are relatively low) is 10⁷⁰ Pa s.

This number is so high that for most purposes, it might as well be infinite, meaning that these plates should behave like rigid bodies. But this accepted wisdom poses a problem: “I realized that I was unable to explain to my students why plates with such high viscosity bend and subduct into the mantle,” Yoshida tells Physics World.

Observed flow and flow parameters

To determine the “effective viscosity” of rock under the temperature and pressure conditions on Earth, Yoshida began by analysing satellite data showing tectonic plate deformations over tens to hundreds of kilometres. Using these data, he could ascertain strain rates – deformations in the plate over a given distance and time – as small as 10^-9 per year.

By comparing regions under similar stress levels, Yoshida obtained an indication of comparative effective viscosity, which depends on factors such as temperature, composition, grain size, water content, stress state, deformation mechanism and structural heterogeneity. After accounting for assumed stresses, these observations suggested that observed viscosity maxes out at 10²⁸ Pa s.

Yoshida also considered empirical descriptions for the viscosity of various minerals under different types of deformation using parameters from the literature. These yielded a similar upper bound of 10^30+/-2 Pa s. Numerical simulations further corroborated this value as a viscosity maximum.

Importance of an upper bound

Taras Gerya, a geodynamicist at ETH Zürich in Switzerland who was not involved in the study, calls Yoshida’s work “an interesting discussion on the significance of viscous deformation for the lithosphere”. However, he notes that, given a realistic stress level of 30 MPa, the maximum viscosity identified gives a cumulative viscous deformation of just 8.5 m for the full 4.5 billion years of Earth’s history. That, he says, is “1000 times smaller than elastic deformation for the same deviatoric stress level”.

While pinning down an exact magnitude for such high viscosities may not greatly change models of deformation, Yoshida thinks that delineating an upper bound may nevertheless improve our understanding of the physical quantities that characterize the behaviour of matter. He also points out that thermal conductivity, which indicates how easily heat is transferred in materials, ranges over only about five orders of magnitude from water to diamond, making it “surprising that viscosity spans a range of about 35 orders of magnitude”.

Yoshida is keen to explore other implications of these results. During the first hundreds of millions of years of Earth’s existence, when it formed and rapidly cooled, he explains that it was covered by a single rigid lid known as the lithosphere. Plate boundaries and motion didn’t emerge until later, approximately 4 billion years ago. “I believe that the question of why plate motion began after the rigid lid formed is closely related to the results of this study,” he says.

The research is published in Physics of Fluids.

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Here’s how the game works:

1. 1. Enter a word guess – in this game the word has six letters.
   2. After submitting your guess, each letter in the guessed word is coloured to provide feedback:
      • Green: The letter is correct and is in the correct position in the target word.
      • Yellow: The letter is correct but is in the wrong position in the target word.
      • Grey: The letter is not in the target word at all.
   3. Using this colour feedback, refine your next guess.
   4. Continue guessing until you correctly identify the hidden word(s) or run out of attempts.

If you want a clue to the answer, read the article here.

Fancy some more? Check out our puzzles page.

The post Word wave puzzle no.6 appeared first on Physics World.

Researchers in China have cross-calibrated radiation detectors on 25 navigation satellites. Data from two decades of measurements have been combined to create a record of the flux of relativistic electrons that impinges on Earth’s atmosphere. The technique can be applied to other satellite data, and could boost our understanding of the threat that this radiation poses to satellites and shed light on the solar processes that generate the electron flux.

The Global Positioning System (GPS) uses signals from a constellation of satellites to locate the position of receivers on the Earth’s surface to within several metres. There are currently 32 GPS satellites orbiting about 20,000 km above the Earth and each of them carries a radiation detector. These detectors allow scientists to observe changes in radiation levels in space. Much of this radiation comes in the form of high-energy electrons from the Sun, which can disrupt the operation of satellites and even damage them.

The electron flux rises and falls with the solar cycle. This has a period of about 11 years and involves the waxing and waning of sunspots, solar flares and coronal mass ejections.

For those who design and operate satellites, it is crucial to understand this electron flux. However, it has proven difficult to make full use of the data generated by these detectors because the instruments had not been cross calibrated. Indeed, measurement values of high-energy electrons can vary between satellites by several orders of magnitude when the flux is low. One important issue is that not all satellites use the same detectors – with two different instruments having been deployed.

Cross calibration

Now, researchers in China have done a cross-calibration of the particle detectors on 25 GPS satellites. The result is a calibrated dataset of relativistic-electron flux that spans two complete solar cycles (2000–2020).

To do this, the team looked at two different measurements made by the detectors. One is the differential electron flux at 2 MeV arriving from one specific direction. The other is the integral electron flux electrons arriving from all directions at energies greater than 2 MeV.

Because electron flux is affected by Earth’s magnetic field, the team had to consider its effect on measurements. This was done using a concept called magnetic local time, which accounts for the fact that Earth’s magnetic poles are offset from our planet’s axis of rotation.

The team used a satellite called NS59 as the reference for their study because its detector has produced a consistent set of data from 2004 – overlapping in time all other satellites in the study. By doing several statistical analyses, the team was able incorporate data from 24 of the 25 satellites. One detector, however, remained problematic and the researchers recommend that data from this satellite not be used.

The team says that their technique can now be used to cross-calibrate the detectors at other energies – there are 14 differential and 29 integral channels that can be also be analysed. They have already used the same techniques to cross-calibrate the GPS data with measurements made by satellites in  China’s BeiDou positioning system  and observations made by NASA’s two Van Allen Probes.

The research is described in Satellite Navigation.

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Join us for an in‑depth conversation with Simon Cherry, former editor‑in‑chief of Physics in Medicine & Biology (PMB), as he shares his expert perspective on the evolving landscape of medical physics research, molecular imaging, and non-invasive imaging technologies. Drawing on decades of leadership in biomedical imaging and academic publishing, Simon will reflect on major advances shaping the field, define the characteristics of high‑impact imaging research, and highlight how PMB continues to support rigorous, influential scientific work through its editorial standards and peer‑review practices.

This session will additionally spotlight the research of Xinchen (Alison) Deng, a finalist of the PMB 2024 Early Career Award. Attendees will gain insights into her contributions to the advanced medical imaging community, such as photon-counting CT for clinical applications and how her work supports broader advances in medical physics and X-ray/CT imaging research.

Simon will also discuss what makes early‑career research stand out and share strategies for researchers aiming to increase the visibility, reach, and long‑term impact of their publications within competitive scientific journals.

Moderator

Carol Clark, Publisher, Physics in Medicine & Biology

Speakers

Simon R Cherry, PhD received his BSc (Hons) in physics with astronomy from University College London in 1986 and a PhD in medical physics from the Institute of Cancer Research, University of London in 1989. Simon is currently Distinguished Research Professor in the Departments of Biomedical Engineering and Radiology at UC Davis and Professor of Total-Body Imaging at King’s College London. Simon’s research interests centre around biomedical imaging. His major contributions have been in developing systems for positron emission tomography (PET), including designing the microPET scanner for small-animal imaging, the earliest examples of simultaneous PET and MRI studies and co-leading the EXPLORER consortium that developed the world’s first total-body PET scanner. Simon is a Fellow of the Royal Society and Member of the U.S. National Academy of Engineering and National Academy of Inventors. He has received several international awards including the Society of Nuclear Medicine and Molecular Imaging Cassen Prize in 2022. He served as editor-in-chief of the journal Physics in Medicine & Biology from 2011–2020. Simon is the author of more than 350 peer-reviewed journal articles, review articles and book chapters in the field of biomedical imaging. He is also lead author of the widely-used textbook Physics in Nuclear Medicine.

Xinchen (Alison) Deng, PhD, is a diagnostic imaging physics resident at The Ohio State University. Her research focuses on advancing photon-counting CT for clinical applications, including multi-contrast imaging, early disease detection, detector optimization, and AI-based improvements in image quality. Before beginning the residency, Xinchen (Alison) was a postdoctoral fellow in medical physics at the University of Victoria, where she worked with Magdalena Bazalova-Carter and collaborated with Redlen Technologies on the optimization of photon-counting detectors and the clinical applications of spectral CT. She received her PhD in medical physics from the University of British Columbia, where she applied Raman spectroscopy, machine learning, and explainable AI to study radiation treatment response in cancer cells and tissues. Her broader research background spans photon-counting CT, spectral X-ray imaging, Raman spectroscopy, radiotherapy response assessment, and AI-driven image and data analysis. Her photon-counting CT research has been featured in the Physics in Medicine & Biology Early Career Researcher Focus Collection. She is a finalist for the PMB Early Career Researcher Award.

About this journal

Physics in Medicine & Biology. The international journal of biomedical physics and engineering, published by IOP Publishing on behalf of the Institute of Physics and Engineering in Medicine (IPEM)

Editor-in-chief: Katia Parodi, Ludwig-Maximilians University, Munich, Germany

The post Shaping the field of medical imaging: a fireside chat with Simon R Cherry and Xinchen Deng appeared first on Physics World.

Simulating quantum systems is something that classical computers struggle with. Not surprisingly, quantum computers are expected to do a much better job – particularly when a quantum-computer’s architecture is designed to solve a specific type of physics problem.

My guest in this episode of the Physics World Weekly podcast is Ross Jenkinson of the UK’s University of Manchester. He talks about the challenges and rewards of using quantum computers in particle physics – a field where classical supercomputers can struggle to simulate simple systems.

We also explore how quantum information theory is being combined with Einstein’s general theory of relativity to shed light on the nature of space and time.

The post Quarks and qubits: how quantum computing could transform particle physics appeared first on Physics World.

German technology start-up Akhetonics is reimagining the future of high-performance computing (HPC), deploying its proprietary know-how in photonic-design automation and photonic integrated circuits (PICs) to realize the first all-optical digital computation devices. The end-game: an all-optical digital processor – what Akhetonics calls its reasoning processing unit (RPU) – that will fundamentally transform the way that data is processed, transmitted and stored at every level of the HPC stack.

While the anticipated upsides of photonic computing are compelling – think bandwidth scaling, energy-efficiency and reduced latency – the translation of Akhetonics’ R&D effort and early-stage PIC designs into at-scale implementation is still in its infancy. What’s evident even now, though, is that the start-up’s progress is being accelerated by collaboration, interdisciplinary expertise and innovation spanning photonic system design and precision-motion and control technologies.

Collaboration, co-development, customization

A case study in this regard is Akhetonics’ partnership with SmarAct, a German manufacturer and developer of specialist products for nano- and picometre-precise positioning, metrology and automated assembly. Both companies are shaping the future of photonics, albeit along complementary tracks: Akhetonics with its vision of a full-stack photonic computing architecture; SmarAct with a portfolio of enabling technologies that’s helping to make next-generation optical computing a practical proposition.

The two vendors began working together after an initial meeting four years ago at the European Conference on Optical Communication (ECOC 22) in Basel, Switzerland. Top of the Akhetonics shopping list: a versatile optical test system to characterize its advanced PICs.

“There are off-the-shelf PIC characterization systems on the market, but they all impose constraints on our design options,” explains Leonardo Del Bino, co-founder and chief technology officer (CTO) at Akhetonics. “Instead, we teamed up with SmarAct to co-develop a compact and modular test architecture built to our exacting specifications. The resulting set-up gives us the flexibility to evaluate and optimize all sorts of innovative PIC designs.”

At the heart of the Akhetonics optical testing workstation sit two discrete nanopositioning subsystems: an XY-Rz chip platform (itself comprising three nanopositioning stages offering horizontal translation along the X and Y axes and rotation limited to the Z axis) and a Z-Rx-Ry “pivot” for an optical probe (where translation occurs only along the Z axis, with simultaneous angular rotation around the X and Y axes). The test set-up (which also incorporates a digital microscope for PIC inspection and alignment) can be used without restriction in every degree of freedom, with the two subsystems working in tandem to ensure precise multi-axis positioning for optical coupling and electro-optic characterization tasks.

On a more granular level, each nanopositioning subsystem is based on SmarAct positioners equipped with integrated optical encoders (SmarAct’s METIRIO® sensors with a resolution of 1 nm) along all six axes of motion. The first subsystem provides three degrees of freedom for lateral alignment (with 49 mm travel in both X and Y, 360° rotation around Rz and a unidirectional positional repeatability of ±40 nm per linear axis). The second subsystem provides vertical and angular alignment (with 31 mm travel in Z, ±5° tilt around Ry, ±45° rotation around Rz and a unidirectional positional repeatability of ±40 nm for the linear Z axis).

To evaluate new PIC designs, Akhetonics’ optical test routines focus primarily on measuring and minimizing insertion losses between input/output fibres and on-chip planar waveguides. Typical measurements include wavelength- and polarization-dependent coupling losses (for example, when a fibre array couples laser light into a series of on-chip grating couplers or when light is coupled from a planar waveguide back into an optical fibre). The subsequent integration of electrical probes into the test system (using two separate XYZ probe towers) supports electro-optic characterization of key on-chip building blocks like optical modulators and photodetectors.

“The requirements for the electro-optical testing are nothing crazy,” says Del Bino. On-chip electrical contacts are in the ballpark of 100 μm x 100 μm, so Akhetonics engineers need positional and alignment precision an order-of-magnitude better than that for their electrical probes. “On-chip optical testing is a different story,” he adds. “A fibre-waveguide mismatch of 1 μm means significant coupling losses, so we need positional accuracy and repeatability of tens of nm or less.”

The rewards of reciprocity

Operationally, the custom test system is the result of ongoing collaboration between the engineering team at Akhetonics and the product development team at SmarAct. After firming up performance requirements, the two vendors iterated back-and-forth with 3D CAD drawings before converging on a final agreed system design.

“We supplied the nanopositioning stages that form the precision-motion core of the workstation,” explains Max Trippel, SmarAct’s business development manager for photonic applications. Akhetonics then integrated these modules into its own test environment, including the fibre and fibre-array-unit holders; the required optical and electrical measurement equipment; and the software routines for photonic characterization. “This approach gives Akhetonics the flexibility to build exactly the test workflow it needs, while relying on a stable and repeatable positioning platform,” Trippel adds.

Crucially, the SmarAct software “ecosystem” and Python interface make it easy to integrate the nanopositioning stages within Akhetonics’ PIC test routines. That software application platform, known as the SmarAct Control and Process Environment (SCoPE), also creates opportunities for continuous process improvement and product innovation (for example, the ability to develop custom routines for fast calibration and alignment on all axes).

In this way, SCoPE will be a natural fit as Akhetonics transitions its PIC testing programme from an R&D setting through small-batch production runs and, ultimately, to volume manufacturing capability (see “SCoPE in brief”, below). “Our goal with SCoPE is to provide customers with easy access for system development, whether that’s for the testing or assembly of photonic components,” says Trippel. “SCoPE is a living platform and we’re constantly integrating novel functionalities and application-specific plug-ins as well as features to facilitate control of third-party devices.”

Strategically, the SmarAct-Akhetonics partnership is shaping up as a win-win for the long term, with the latter’s growth trajectory and evolving platform technologies feeding into SmarAct’s product development roadmap. “Our customers’ success is our success,” Trippel concludes. “Working in this way with Akhetonics and its peers means we have line-of-sight on ‘what’s next’ in photonic computing. Watch this space: the last word has not been spoken.”

SCoPE in brief

The SmarAct Control and Process Environment (SCoPE) is a modular and extensible software application platform that combines visual process modelling, Python scripting and hardware integration. SCoPE enables customers to develop, control and run automated processes in a unified environment that offers…

• Process modelling and automation: visual drag-and-drop process editor enables intuitive creation, control and execution of automation workflows. Live process display gives users direct feedback during execution.
• Python scripting backend: integrated Python scripting allows developers to extend workflows with custom logic, algorithms and third-party devices to create advanced automation scenarios. Package and dependency management are built-in.
• Device control and hardware integration: native support for SmarAct hardware such as positioning systems, controllers, grippers and interferometers through specialized plug-ins.
• Custom user interfaces: flexible Qt widget integration makes it possible to build tailored graphical user interfaces for specific applications.
• Data visualization and imaging: configurable plotting widgets, real-time data visualization, process messaging and an integrated image processing pipeline support instant process feedback and image-based automation tasks.
• Plug-in architecture: the modular plug-in system enables SmarAct and third parties to extend SCoPE with additional functions, algorithms, hardware integrations or communication interfaces.
  

The post Nanopositioning, customization and control: opening new frontiers in optical computing appeared first on Physics World.

I am writing from Argentina as a researcher working within the country’s national scientific system. While discussions about science funding are often framed in terms of budgets and economic indicators, the reality is experienced in laboratories, offices and research facilities where scientific knowledge is produced.

Today, many of us in Argentina are witnessing a progressive deterioration of Argentine science, both in terms of infrastructure and human capital.

I am based at the Comisión Nacional de Energía Atómica (CNEA), where uncertainty has become routine. Hundreds of employees remain on temporary contracts that can be terminated without warning. On 1 July 2026, a total of 61 colleagues lost their jobs, with armed military police officers occupying the building to contain a peaceful employee protest. Beyond the immediate human cost, these dismissals are steadily dismantling scientific capabilities that have taken decades to build.

The impact became tangible when my colleague Paula Alderete, an experienced electron microscope specialist, lost her position. Alderete, who has published two papers with me, was responsible not only for operating a highly specialized instrument, but also for maintaining it and supporting dozens of research projects.

Without Paula Alderete’s expertise, our lab’s electron microscope has become largely unusable. It is a quiet reminder that scientific infrastructure depends as much on people as on expensive equipment.

Faramarz S Gard

Without her expertise, the microscope has become largely unusable. Every morning I pass her empty desk on my way to the laboratory. It has become a quiet reminder that scientific infrastructure depends as much on people as on expensive equipment.

The deterioration extends beyond personnel. In my laboratory, an X-ray photoelectron spectroscopy (XPS) instrument worth more than $1m must sometimes be protected with plastic sheets because rainwater leaks through the roof.

Equipment designed to operate under tightly controlled environmental conditions is now exposed to circumstances that threaten its long-term reliability. Similar situations are becoming increasingly common across Argentina’s universities and research institutes as maintenance budgets shrink and infrastructure ages.

Argentina has a scientific tradition that reaches far beyond its borders. The country has produced five Nobel laureates, including three in the sciences, and has made internationally recognized contributions to nuclear technology, medicine, agriculture, astronomy and materials science. Institutions such as CNEA, CONICET (Argentina’s national research council) and the national universities have trained generations of researchers whose work has strengthened international collaborations and advanced scientific knowledge worldwide.

Scientific systems rarely collapse through a single dramatic event. They decline incrementally: one technician dismissed, one laboratory left unrepaired, one instrument taken out of service, one young scientist deciding to build a career elsewhere. These individual losses accumulate into a weakening of scientific capacity that may take decades to rebuild.

When a country loses the expertise required to operate advanced laboratories or maintain unique scientific infrastructure, the consequences extend beyond national borders.

Faramarz S Gard

This should concern more than Argentina. Modern science depends on international networks of researchers, shared facilities and long-term collaboration. When a country loses the expertise required to operate advanced laboratories or maintain unique scientific infrastructure, the consequences extend beyond national borders.

Knowledge is lost, collaborations weaken, and opportunities for discovery diminish.scientific infrastructure is more than buildings and instruments; it is the people whose expertise gives those resources value. Once that expertise disappears, replacing it is far more difficult than preserving it.

The empty desk of a single scientist may seem insignificant, but multiplied across laboratories and institutions, it becomes a warning of how a research system is quietly dismantled. Argentina’s experience is therefore not only a national concern but also a reminder that scientific capacity, wherever it exists, is a global resource that is remarkably difficult to rebuild once lost.

I write this letter not only to describe a difficult situation but also to call attention to the broader consequences of sustained disinvestment in science. The international scientific community should recognize that the erosion of research systems in countries such as Argentina represents a loss not only for those nations but for global science itself.

Science is built by people, sustained by institutions, and enabled by infrastructure. Today, all three are under increasing strain in Argentina.

The post Letter from Argentina: ‘an empty desk and an idle electron microscope signal the erosion of the country’s science’ appeared first on Physics World.

A possible “exosatellite” has been discovered 73 light years away. Bizarrely, it is roughly the size of Jupiter and orbiting a failed star called a brown dwarf, which in turn is orbiting the red dwarf star CD-35 2722.

This huge alien “moon” was found by the Very Large Telescope’s CRIRES+ spectroscopic instrument, which measured the Doppler shift in the brown dwarf’s light as the exosatellite gravitationally tugged on it. This is the same method used to discover the first known exoplanet around a Sun-like star, namely 51 Pegasi b, in 1995.

Only a handful of exosatellite candidates have been discovered thus far, with none being particularly convincing. This newly detected satellite, reported in Nature, is possibly the best of the bunch. The brown dwarf, known as CD-35 2722b, has a mass about 37 times greater than Jupiter and its exosatellite has a minimum mass of 90% that of Jupiter.

Moon, satellite or planet?

Planetary mass objects around brown dwarfs have been discovered before. Take the example of 2M1207b, which is an object up to six times more massive than Jupiter orbiting a brown dwarf, discovered in 2005 by the Very Large Telescope. Such objects have not been referred to previously as moons or satellites, so why now?

“This system is meaningfully different from 2M1207 because of the mass ratios and separations involved in CD-35 2722,” says Kevin Hoy, a PhD candidate at the European Southern Observatory and the Instituto de Estudios Astrofísicos in Chile, who led the discovery.

Whereas 2M1207b is approximately a quarter of the mass of its host brown dwarf and on a very wide orbit, possibly as long as 20,000 years, CD-35 2722b’s satellite has about 2.5% of the mass of its host brown dwarf and is on a much closer 170-day orbit.

There’s also the hierarchy of the system to consider. In the 2M1207 system, the brown dwarf doesn’t orbit anything, but in CD-35 2722 the brown dwarf is on a 5000-year-long orbit around its companion star. The candidate exosatellite therefore orbits something that orbits a star, just as a given moon in our Solar System orbits a planet that orbits a star. Since our Solar System has nothing like this brown dwarf–satellite combination, the language that we use to describe such objects is seemingly inadequate.

Mary Anne Limbach of the University of Michigan, who was not involved in this study, agrees that our nomenclature is increasingly ill-suited to the bizarre objects that we are discovering beyond our Solar System.

“Most people in the astronomical community would probably hesitate to call this an exomoon,” she tells Physics World. “But I think ‘exosatellite’ is appropriate. The field needs language for companions that do not neatly fit into the traditional categories of planets and moons, and ‘satellite’ seems to be the broader term that the field is gravitating towards.”

Forming exosatellites

Definitions are important, adds Limbach, because they allow us to distinguish between how otherwise similar objects formed.

The moons in our Solar System formed from debris discs encircling their parent planets. Material in the discs clumped together, forming cores that were then able to sweep up the remainder of the material. Astronomers refer to this as core accretion formation.

“If I had to put money on it, I would doubt that the CD-35 2722b satellite formed via core accretion for several reasons,” says Hoy. These reasons include the size of the disc required to build such a massive satellite, the speed with which it would have done so (it is only 150 million years old) and its eccentric orbit. Moons born in situ around their parent typically adopt a more circular orbit.

Instead, Hoy suspects that the brown dwarf and its satellite collapsed directly out of a gas cloud in much the same way that stars do. “That would be my best guess,” he says.

The formation mechanism makes all the difference to Limbach, who opines that, “an object can reasonably be called a moon if it formed through a process analogous to the formation of the moons around the Solar System’s planets.”

Limbach cautions that since we only know the satellite’s minimum mass, we cannot yet rule out this being a binary system of two brown dwarfs. Either way, Limbach sees the system as being close to that of a binary giant planet. Our understanding of how giant planetary bodies and low-mass brown dwarfs form tells us that binary giant planets should be rare, “but the first emerging examples hint that they may not be,” says Limbach. These include about 40 pairs of rogue binary giant planets, called Jupiter Mass Binary Objects (JuMBOs), found by the James Webb Space Telescope in the Orion Nebula’s Trapezium star cluster.

Tip of the iceberg

Another unanswered question is how far down does CD-35 2722’s hierarchy go? Could the exosatellite have moons of its own?

“I think it’s definitely possible,” says Hoy, so long as they are on tight orbits so that gravitational tides cannot destabilize them. “Unfortunately such an object is likely impossible to detect with our current methods.”

However, our current methods could soon learn that CD-35 2722 is just the tip of the iceberg.

“Looking at directly imaged planets and brown dwarfs is the most likely way to yield more exosatellites,” says Hoy, while also citing astrometry (looking for deviations in the motion of a star through space) and microlensing (where the gravity of an otherwise unseen exosatellite creates a temporary gravitational lens) as key techniques that could bring dividends.

Meanwhile, it is hoped that the European Space Agency’s PLATO mission, which will discover exoplanets via transits, will detect significantly large terrestrial moons once the mission launches at the beginning of 2027. All in all, we could be on the cusp of a new era of exomoon and exosatellite discovery.

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To play, click or drag one or more tiles to move them into the empty space. Repeat until you have reconstructed the image.

Image courtesy: iStock/vasantytf; iStock/extravagantni

Fancy some more? Check out our puzzles page.

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As I was strolling through Belfast’s Titanic Quarter last summer, I discovered with delight a road called Bell’s Theorem Crescent. It’s named in honour of the Belfast-born physicist John Bell, best known for his eponymous theorem. Despite not being as embedded in popular culture as Schrödinger’s cat, his theorem will certainly ring a bell (forgive the pun) with most physicists.

The story goes back to 1935 when Albert Einstein, Boris Podolsky and Nathan Rosen (EPR) came up with their now-famous thought experiment, which was designed to show that quantum mechanics was, as a description of nature, incomplete. In the EPR scenario, non-local influences can affect the measurement outcomes performed on spatially separated particles.

Given how odd that seemed, some physicists invoked what are known as “hidden variables” to get rid of these non-local correlations and restore local realism. It was in 1964, while working at the CERN particle-physics lab, that Bell showed that no local hidden-variable theory can be compatible with the predictions of quantum mechanics.

This result – Bell’s theorem – is something I was familiar with but I had paid little attention to where it had originally appeared. As I discovered, it was published in a paper called “On the Einstein Podolsky Rosen paradox” in the journal Physics (3 195) in 1964. Also known as Physics Physique Физика, this little-known publication existed only from 1964 to 1968. In fact, Bell’s theorem is the most important result published in it.

The journal was set up by two physicists at Bell Laboratories in the US – Bernd Matthias and future Nobel laureate Philip Anderson. According to A Mind Over Matter – Andrew Zangwill’s 2021 biography of Anderson – they were not too happy with conventional physics journals. “The referees,” Anderson said, “often did a bad job, the editors took too long to make decisions, and too much wrong physics got published.”

Those are complaints you’ll still hear in coffee breaks at most physics conferences today, and they prompted Matthias to contact the media magnate Robert Maxwell, who’d founded Oxford-based publishing house Pergamon Press. Maxwell had figured out that scientific publishing could be a very lucrative business so he helped the two physicists to set up the journal.

A publishing experiment

In their first editorial, Anderson and Matthias called Physics an “experimental journal”, which they hoped would solve the problem of there being “far more good physics written than any physicist can read”. Their solution was to pick only those papers worth the attention of all physicists, which the editors did by reviewing – then accepting or rejecting – every submission themselves. They even paid authors 10 cents a word if their paper appeared in print.

Anderson and Matthias admitted that many physicists had already written to them, criticizing their proposed selection model. They’d been told that their “judgements will be fallible”, that they might be “overimpressed by showiness”, and that they’d end up rejecting excellent work. In response, the pair promised to try their best, accepting they would make mistakes and that their “criteria will be, not better, but different”.

The journal’s criteria clearly succeeded, in that Anderson and Matthias identified the merits of Bell’s paper, which was far from mainstream

These criteria clearly succeeded, in that they identified the merits of Bell’s paper, which was far from mainstream. Keen to find out more about the events surrounding its publication, I contacted Zangwill, who had interviewed Anderson several times for his book. Zangwill shared the following quote, published here for the first time.

“One day,” Anderson recalled, “a paper came in from a guy neither of us had heard of – John Bell. It was about hidden variables in quantum mechanics. Bernd had no clue, but I accepted it with the hope that its publication would spell the death of Bohmian trajectory quantum mechanics. It’s a very famous paper today.”

In 1967 the quantum physicist John Clauser found Bell’s paper after stumbling upon Physics Physique Физика, attracted by its unusual title. Clauser, who shared the 2022 Nobel Prize in Physics, carried out the first Bell test in 1972 with Stuart Friedmann. Their work triggered a long series of experiments that would deepen our understanding of quantum mechanics and catalyse the development of quantum technologies.

Over its short life, Physics did publish work from other notable physicists including Murray Gell-Mann, Leonard Susskind and Leo Kadanoff. In fact, the journal was ahead of its time, with the model of in-house editorial selection for broad interest returning in the 2000s with the Nature series of journals. The inclusive, multi-language title was also well ahead of its day.

Sadly, Physics Physique Физика was discontinued in 1968 after just three volumes

Sadly, Physics Physique Физика was discontinued in 1968 after just three volumes. According to what Anderson told Zangwill, it stopped “not because it lacked submissions, but because they had promised contributors rapid publication and Maxwell kept increasing the time between the appearances of successive issues”. Maxwell’s aggressive pursuit of profit might also have played a role.

The journal has since been archived by the American Physical Society and is freely accessible online. One can only wonder what might have happened if Anderson and Matthias had picked a different name for their journal.

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Intrinsically disordered proteins (IDPs) do not form stable 3D structures. Instead, they remain flexible, adopt many conformations, and can interact with multiple molecules. Although proteins were once thought to require a fixed structure to function, many IDPs play essential cellular roles. Some IDPs can assemble into biomolecular condensates, membrane-less compartments that help organise processes such as gene expression and stress responses.

Many IDPs contain prion-like low complexity domains (PLCDs), which have defined sequence features known as molecular grammas. These IDPs are multivalent and can form hierarchies of interactions with one another. These interactions promote clustering and, under the right conditions, phase separation into a protein-rich condensate and a surrounding dilute phase. Dysregulation of condensates has been linked to disease.

In this study, researchers used computer simulations to investigate the PLCD known as A1-LCD. Their aims were to accurately identify the critical point where phase separation ceases, map the full phase diagram, and assess methods used to estimate the theta temperature (Tθ), a measure related to solvent quality and protein interactions.

The simulations revealed three distinct phase-separation regimes: a dilute phase containing mostly isolated proteins, an intermediate regime where clusters form before large condensates appear, and a regime near the critical point characterised by system-spanning networks. The study also showed that condensates behave as percolated networks of interconnected proteins. Importantly, the authors found that commonly used methods for estimating theta temperature may be inaccurate for these systems.

Overall, this work provides new insights into the phase behaviour of condensate-forming proteins and highlights the need for more reliable approaches to assessing solvent quality. These findings could improve future studies of biomolecular condensates and their roles in health and disease.

“Comparative assessments of driving forces for phase separation requires knowledge of IDP-specific critical points. Our application of rigorous finite size scaling methods pioneered by Kurt Binder helped us delineate the critical and mean field regimes and demonstrate how the critical point can be converged upon for realistic approximations of IDPs. This revealed several surprises regarding the complex nature of the coexisting dilute phase. Additionally, we found that calculation of the two-body interaction coefficient provides a computationally tractable approach to compute comparative, sequence-encoded driving forces for phase separation of IDPs. This is directly relevant to inferring how changes to molecular grammars influence phase behaviors driven by homotypic associations.” – Rohit V. Pappu, Washington University in St. Louis

Do you want to learn more about this topic?

Biomolecular dynamics: order–disorder transitions and energy landscapes by Paul C Whitford, Karissa Y Sanbonmatsu and José N Onuchic (2012)

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According to band theory, materials with partially filled energy bands and unpaired electrons should conduct electricity, but in Mott insulators this rule is broken. In these materials, the repulsion between electrons is so strong that they cannot move freely and become localized. When sufficient energy is supplied (for example by light), electrons can form a doublon (two electrons on one site) and a hole (an empty site). These excitations can move, enabling electrical conductivity.

A key question for Mott insulators is how these charge carriers are created and what controls their production. Traditionally, two regimes were known: multiphoton absorption, where several photons combine their energy, and tunnelling, where a strong electric field drives electrons across the gap.

In this work, the authors show that there are actually four regimes: multiphoton, tunnelling, a cooperative regime where the two processes work together, and an incoherent regime where weak fields and scattering dominate. They also show that the energy gap (the cost to create a doubloon-hole pair) is not fixed, but changes during the process because the generated carriers modify the system. This creates a feedback loop, making the dynamics nonlinear and time-dependent. As a result, carrier production can either slow down or suddenly speed up, even making the system more efficient without changing the driving field.

The behaviour depends on field strength, frequency, dissipation, and time, and each mechanism can be identified by its distinct momentum pattern. By tuning laser parameters, the system’s properties can be controlled in real time. Overall, this work shows that light can be used to dynamically reshape and control strongly interacting materials, opening possibilities for ultrafast, light-driven technologies.

Do you want to learn more about this topic?

PLP-Logo-2.png, find out more. Quantum frustration in organic Mott insulators: from spin liquids to unconventional superconductors by B J Powell and Ross H McKenzie (2011)

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A new study has revealed that sensitive health information about individual patients can be extracted from medical artificial intelligence (AI) models more effectively than previous research had indicated.

Diagnostic AI models are used to determine whether some given health data belong to a specific class – for example if an X-ray image shows evidence of pneumonia – and offer huge promise for improving patient outcomes. Earlier studies showed that membership inference attacks (MIAs), which determine whether a particular person’s data was used to train an AI model, yielded results no better than random chance. But these previous studies only evaluated the average risk across all patients in a training dataset.

By contrast, in this latest work doctoral student Moritz Knolle and his supervisor Daniel Rückert at the Technical University of Munich (TUM), together with collaborators at Imperial College London and Georg Kaissis from the Hasso Plattner Institute (HPI), examined the privacy risk for an individual patient. “Privacy that only works on average has little meaning. So I asked myself: would I contribute my data to train a medical AI model?” says Knolle.

As detailed in their recent Nature paper, the researchers attacked AI models based on seven different types of real-life medical datasets, including one comprising 21,799 electrocardiograms and another of 377,110 chest radiographs.

“If a model sees a specific data point during training, it usually becomes more confident at predicting it. So in these MIA attacks I compare the predictive probability number for this data point outputted by the medical AI model with the predictive probability number obtained from my model which has not seen that data point,” explains Knolle, adding that the attack is essentially a statistical test to distinguish between the two models.

Their results revealed that the privacy risk for an individual was far greater than the average risk. The team also found that privacy risk is not equally distributed among subgroups.

“We found that patients from minority groups that are under-represented in the training dataset tend to be over-represented among the 99 percentile of extreme [privacy] risk,” Knolle tells Physics World, warning that as medical AI models become larger and more sophisticated the privacy risk is amplified because their deep analysis creates the small changes in predictive probability that MIAs are good at finding.

While an MIA that reveals someone is a UK citizen poses little security risk, discovering that an individual has received a specific type of cancer treatment reveals personal information that could, for instance, adversely affect their medical insurance premiums. “The more specific the training cohort is, the larger the privacy risk,” states Knolle, crediting his medical doctor parents with inspiring his desire to improve healthcare AI.

Countermeasures include differential privacy (DP), in which a small amount of Gaussian random white noise is added in alongside the data during training, thereby reducing the effectiveness of MIAs while maintaining the model’s diagnostic accuracy. “This gives a mathematically provable upper bound for how much privacy risk any individual in this dataset could face, by limiting the information content that flows to the AI model,” explains Knolle.

He notes that, unfortunately, such DP tools have not been widely adopted by hospitals or clinics. This, he fears, could undermine patients’ confidence in sharing their data, and thereby not only reduce AI’s ability to help combat rare diseases, but also compound AI discrimination that occurs when there is too little data from minority groups included in training datasets.

“So we are hoping to inspire the medical AI community to do risk assessments before deploying AI models, and use verifiable strategies such as DP or limiting access to the AI model, so that as an individual you have a statistical guarantee that no harm would come to you by being part of a dataset,” concludes Knolle, who now plans to investigate the privacy risks posed by generative AI models for healthcare.

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Environmental Research: Climate was launched in 2022, with the aim of uniting multidisciplinary communities. With a scope that is intentionally broad, the mission of the journal is to publish innovative research examining the causes, consequences, and solutions of climate variability and change. Since our launch, we have published more than 270 articles covering physical and biogeochemical processes that shape Earth’s climate across spatial and temporal scales; the human and ecological dimensions that shape climate-related risks and impacts; and the design, analysis and evaluation of climate mitigation, adaptation, and risk-management strategies and solutions. This webinar will explore the current state of climate research, including changes in the field over the last five years since the launch of the journal, and direct us toward the future.

Moderator: Noah Diffenbaugh, Stanford University
Noah Diffenbaugh is the William Wrigley Professor and Kimmelman Family Senior Fellow in Stanford’s Doerr School of Sustainability, and the Olivier Nomellini Family University Fellow in Undergraduate Education. His research is focused on understanding what aspects of the climate system most directly and acutely impact people and ecosystems. Noah has served as a Lead Author for the Intergovernmental Panel on Climate Change (IPCC), and as editor-in-chief of the peer-review journals Geophysical Research Letters and Environmental Research: Climate. He has provided testimony and scientific expertise to federal, state and local officials. Noah is an elected Fellow of the American Geophysical Union (AGU), a recipient of the James R. Holton Award and William Kaula Award from the AGU, and has been recognized as a Kavli Fellow by the U.S. National Academy of Sciences.

Katharine Mach, University of Miami
Katharine Mach is professor and chair of the Department of Environmental Science and Policy at the University of Miami Rosenstiel School of Marine, Atmospheric, & Earth Science. During spring 2025, she was the Coleman P. Burke Distinguished Visiting Professor at the Yale School of Environment. Her research assesses climate-related risks and response options to address increased flooding, extreme heat, wildfire and other hazards. Through innovative approaches to integrating evidence, she informs effective adaptations to the risks.

Katharine was the 2020 recipient of the Piers Sellers Prize for world-leading contribution to solution-focused climate research. She has served as a chapter author or lead in the Fourth through Sixth US National Climate Assessments and the IPCC Sixth Assessment Report and as a member of the National Academies Climate Security Roundtable. She serves as co-editor-in-chief for Climate Risk Management, an editorial board member for Oxford Open Climate Change and Environmental Research: Climate, and an advisory committee member for the Aspen Global Change Institute. Across all of her research projects, she engages in relevant policy processes and explores and discusses climate risk and adaptation with the media, the private sector, nongovernmental organizations and communities.

Andrew Pershing, Climate Central
As chief programme officer, Andrew Pershing, PhD, leads Climate Central’s climate science activity. His role includes bridging primary research and media analysis to amplify critical work on climate change and climate impacts and make it accessible to audiences around the world. As the director of attribution science and climate fingerprinting, Andrew is developing tools like the Climate Shift Index to quantify how climate change has increased the likelihood or severity of conditions in the atmosphere and ocean. He works closely with communications experts at Climate Central and our partners to help the media and others to incorporate this information into their content.

Andrew has led interdisciplinary research teams to study the impact of global warming on marine ecosystems in the northwest Atlantic. More recently, his work has focused on how climate trends interact with decisions that people make and on how marine ecosystems store and process carbon. As a communicator, Andrew has deep experience working with journalists to present climate science on air and in print.

Inês Azevedo, Stanford University
Inês M Lima Azevedo is a professor in the Energy Science & Engineering department at Stanford University. She is a senior fellow at both Stanford Woods Institute for the Environment and for Precourt Institute for Energy. She has a BSc in environmental engineering (2004) and a MSc in engineering policy and management of technology from IST-Portugal, and a PhD in engineering and public policy from Carnegie Mellon University (2009). Inês is passionate about solving problems that include environmental, technical, economic and policy issues, where traditional engineering approaches play an important role but cannot provide a complete answer. In particular, she is interested in assessing how energy systems are likely to evolve, which requires comprehensive knowledge of the technologies that can address future energy needs and the decision-making process followed by various agents in the economy.

About this journal

Environmental Research: Climate explores the causes, consequences, and solutions of climate variability and change, by uniting research communities across the entire spectrum of the climate system.

Editor-in-chief: Noah Diffenbaugh Stanford University, USA

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Sugars are a vital ingredient in the recipe for life, responsible for a range of biological processes and a key component of nucleic acids such as DNA and RNA. The question of how these essential biomolecules were produced on primitive Earth is a pressing concern for origin-of-life researchers, with laboratory experiments suggesting that primordial conditions would not yield sufficient quantities.

In a study led by Izaskun Jiménez-Serra at the Centro de Astrobiología (CAB, CSIC-INTA) in Spain, researchers have observed a four-carbon sugar, erythrulose, in the interstellar medium for the first time. Such sugar could have contributed to the resources available for early biological processes, providing insight into how life began on Earth.

Sugars in space

Based on studies of asteroid samples, researchers suggest that key building blocks for life may have had an extraterrestrial origin. Previous analysis of samples from the asteroid Bennu has demonstrated the presence of the sugar glucose, a primary energy source for biological processes, and ribose, a sugar that contributes to the development of nucleic acids.

The idea is that meteorites and comets containing these important chemical components impacted Earth and contributed to the resources available to develop life. This latest research looks backwards in this process to question whether these molecules may have formed in the clouds of dust and gas that parent these astronomical bodies.

Detailed in Nature Astronomy, this first observation of sugar in the interstellar medium suggests that the ingredients for life may indeed form in dust clouds as previously proposed.

Detecting erythrulose

To detect these molecules, Jiménez-Serra and colleagues used the Yebes 40 m and IRAM 30 m telescopes in Spain. Ultrasensitive, broadband spectral surveys allowed them to identify the signature of erythrulose inside G+0.693−0.027, a cloud of gas close to the centre of the Milky Way.

The team had to overcome various challenges, including the spectral signatures of different molecules overlapping and blending into one another. To ensure the validity of their observations, they identified over 180 molecular species to better understand any possible interference with the emission of erythrulose. This extensive characterization allowed the researchers to obtain very high levels of confidence in their observations, they say.

The team also analysed how the erythrulose may have been formed in the extreme low temperatures and vacuum conditions of interstellar space. The abundance of erythrulose is eight times that of three-carbon sugars which are currently undetected by these incredibly sensitive observations. This led the team to model the formation of erythrulose from simpler and more readily available two-carbon aldehydes and alcohols – a process that occurs on the surface of grains of dust in space, with the potential to then contribute to chemical systems on Earth.

Extraterrestrial building blocks

On Earth, erythrulose is found in fruits such as melons and raspberries. In aqueous environments, such as bodies of water on Earth, erythrulose easily changes its configuration into the sugar threose. Similar to ribose in RNA, threose appears in threose nucleic acid (TNA). One of the simplest nucleic acids, TNA may be one of the first involved in the early development of life.

According to Jiménez-Serra: “The discovery of erythrulose in the interstellar medium opens up the possibility for these key organic compounds to form in other molecular clouds in the Galaxy where stars and planets are forming”.

The team’s future plans include searching for larger sugars such as the five-carbon ribose found in RNA. “By combining astronomical observations with laboratory experiments and theoretical calculations, we will explore the chemistry of these sugars and of their related compounds, which could have played a key role in the origin of life,” shared Jiménez-Serra.

The work is being completed as part of the ERC consolidator grant OPENS. This highly interdisciplinary project draws from a range of research methods and scientific fields to approach the question of how life begun on earth. By continuing this research, the team hopes to learn more about the very earliest stage of our journey on this planet.

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By controlling a type of polarized light widely used in quantum optics, researchers have transformed subtle optical patterns in our peripheral vision into vibrant, easily perceptible shapes. Led by Dusan Sarenac at the University of Waterloo, Canada, the team showed for the first time that the “Boehm’s brushes” perceived by participants can be altered by adjusting the topology of spin-orbit coupled light. Their results, reported in Proceedings of the National Academy of Sciences, could lead to promising new techniques for checking our eye health.

For the most part, human eyes are incapable of detecting polarization in visible light. But in some rare cases, structures inside the eye itself can scatter light in different ways depending on its polarization, creating subtle yet perceivable “entoptic” patterns. Perhaps the best-known examples of these are “Haidinger’s brushes”: hourglass-shaped patterns that can form in our central vision, but only when viewing linearly polarized light at blue wavelengths.

In 1940, Swiss biophysicist Gundo Boehm discovered another example: a two-lobed, bowtie-shaped entoptic pattern that forms when viewing linearly polarized light in the peripheral vision as it scatters from subcellular structures in the inner retina. Unlike Haidinger’s brushes, this lesser-known effect is driven by angular variations in scattering strength relative to the polarization direction.

But as Sarenac explains, these ethereal shapes are more than just a curiosity. “Because retinal disease may alter a person’s ability to perceive the pattern, researchers have long considered whether Boehm’s brushes could serve as a biomarker of retinal health,” he says. “However, their weak visibility has limited practical use.”

Whereas previous studies simply asked participants to passively observe the effect, Sarenac’s team considered what would happen if the light’s polarization was constantly varied. To explore this possibility, the researchers created a beam of spin-orbit coupled light, in which polarization is linked to the light’s orbital angular momentum – a property describing how the wavefront twists as the beam travels – so that the polarization direction rotates steadily across the beam.

In quantum optics, these structured waveforms are already being widely explored for their possibilities in imaging, communication and information processing. But for the first time, Sarenac’s team considered how our eyes could actually perceive this light. “We engineered the spatial polarization of the light to match the symmetry of the retinal scattering response,” Sarenac describes. “This allowed many weak local contributions to reinforce one another.”

The researchers then projected this structured light through a ring-shaped aperture, targeting specific regions in the periphery of participants’ retinas, which could also be adjusted to target varying distances from the centre of vision. Using an automated test, they measured how much contrast participants needed to reliably distinguish a Boehm’s brush from the background at these varying distances.

Based on the subject’s responses, Sarenac’s team determined that the use of spin-orbit coupled light not only made Boehm’s brushes appear far more vivid to the participants, it also transformed the bowtie shape into a multi-lobed pattern, with the number of lobes varying depending on the topology of the light’s twisting polarization.

“Across 11 participants, detection thresholds improved exponentially away from the centre of vision, and the pattern became robustly visible at approximately one degree of retinal angular distance,” Sarenac describes. These results reveal a fascinating link between human vision and quantum mechanics, which the team hope could be harnessed in practical healthcare. With further studies involving patients with retinal disease, they now envisage eye tests where retinal conditions could be diagnosed in people who can’t clearly perceive vibrant, multi-lobed Boehm’s brushes in their peripheral vision.

“In the longer term, these patterns may provide a non-invasive functional probe of retinal integrity because their shape and visibility can be measured across different retinal locations,” Sarenac says.

The post Structured light could deliver a new method for diagnosing eye disease appeared first on Physics World.

What happens when a cosmologist points their tools at the dinner plate instead of the night sky? One person who has done just that is Sarah Bridle, who studied natural sciences at the University of Cambridge in the UK and then stayed on to do a PhD in cosmology, graduating in 2000. Having spent two decades mapping dark matter and building large collaborations around open data, Bridle is now chair in food, climate and society at the University of York, applying that same quantitative, physics based mindset to food.

Food manufacturing is a huge sector: in the UK, it employs 400,000 people and contributes £28bn to the economy. Physics underpins much in the field – everything from productivity, food safety and food security to health and nutrition, waste reduction and environmental impact. Bridle talks to Gleb Yakubov, a food physicist at the University of Leeds, about what inspired their switch from cosmology to food physics and tips for those looking to follow suit. Yakubov is a committee member of the food physics group of the Institute of Physics (IOP), which bridges industry and academia, raises the profile of physics in food, and represents the community to policymakers.

What attracted you to food physics?

It began when I heard that the late David MacKay, who was working at the University of Cambridge, was ill. He worked on error-correction codes, education and artificial intelligence, before pivoting to sustainability and became chief scientific adviser to the UK energy department. I started thinking hard about why we do what we do, and what would happen without him doing the fantastic work he led on energy and climate.

I began watching his talks and learning about climate change – something I hadn’t really engaged with while immersed in astrophysics. In one of his penultimate presentations, he highlighted food as having huge potential to influence climate change through diets and how we produce food. From that moment on I wanted to understand this area – it was compelling, timely and I got obsessed.

You’ve called land use the “dark matter” of climate solutions – what do you mean by this?

Most people aren’t aware that food is responsible for up to a third of global greenhouse gas emissions and, in the UK, about 70% of land is used for agriculture. Many climate solutions involve land – forests for sequestration, biofuels, solar – and people often say “we can’t spare land, we need it for food”. But the way we use land for food can be extremely inefficient, which blocks those climate solutions. That’s a huge, underappreciated lever. 

When you started working in food, what surprised you most?

As a data geek, I expected it to be all about technical solutions but what surprised me was how dominant social and cultural factors are too. You see versions of the so-called “Jevons paradox”: introduce an efficient technology and people just use more of it, cancelling the gains. Unless, that is, you pair it with social and cultural change. Food systems aren’t just complicated; they’re a complex mix of people, incentives, norms and feedback loops.

How did you shift that approach, given that people don’t always behave rationally?

I don’t think people are random; they just use different decision criteria than many models assume. For example, if you raise the price of meat to reduce consumption, some people may see it as more of a luxury and desire it more. You can get perverse responses unless you understand the social context. On top of that, my recent work looks at the potential for civil unrest and even societal collapse – uncertainties we wouldn’t have anticipated five years ago. It pushes us to combine quantitative modelling with deeper social insight.

Can you share an example where astrophysics tools didn’t work in a food context?

Early on I tried to repurpose multispectral satellite-imaging techniques to detect blackgrass in UK wheat fields. Blackgrass is a serious weed that hits yields and this felt like a neat transfer – I’d been analysing astronomical imaging, so why not fields? But it turned out to be too difficult with satellite data alone. Variables like soil moisture, rockiness and other field conditions confounded the signals. That experience nudged me away from a pure imaging approach toward broader system modelling – and, later, back to data with more contextual integration.

Tell us about your “future food calculator”?

About five years ago we started building a quantitative model of the food system to compare interventions on a common footing: on-farm practices such as fertiliser, irrigation, crop management; consumer dietary shifts; and land-use choices. We turned it into a web-based dashboard inspired by MacKay’s energy calculator. Users can move sliders, explore UK production and consumption, greenhouse gas emissions, self-sufficiency and land use, and ask, “Do these choices get us to net zero, and with what trade-offs?”

How do you handle the “people” side – demographics and messaging – in such models and outreach?

You have to meet people where they are. Older generations, on average, are more focused on health than climate. Children and younger people tend to feel invincible about health but are very concerned about climate. If you’re trying to encourage dietary change, those differences matter for messaging and for assumptions in models.

What have you learned about information versus behaviour change?

From obesity research we know that giving people information often doesn’t change behaviour. But it does increase receptiveness to policy. You couldn’t have a sugary drinks tax without enough people accepting that sugary drinks contribute to type 2 diabetes and put pressure on the National Health Service.

I think the same is true for climate and food: we need systemic changes that make sustainable choices easy by default, and public understanding helps make those changes legitimate. Reformulation and choice architecture are good examples – you can reduce beef content in a lasagne by adding pulses, or put low-impact options first in canteens. Many people won’t even notice, but outcomes improve.

While space has an intrinsic “wow” factor, how do you create that for the food industry?

For many people there’s a complete disconnect between food and how it’s produced. Experience helps more than pictures so community garden projects, for example, let people see how hard it is to grow food and how weather drives yields. That fosters respect for food, reduces waste, increases interest in the natural world and builds practical resilience.

You’ve also advised on environmental labelling – what should a good label do?

People already face a lot of labels, and shopping may not be when they’re most receptive. Studies show labels don’t shift individual purchasing as much as you might expect. But labels do change production. In pilot programmes, adding climate labels led operators to change what they offered once they saw the differences. In Canada, when authorities announced a tighter threshold for “red” sugar labels, manufacturers reformulated to avoid red. So the big impact is upstream – on what gets produced.

What’s inside the “digital twin” of UK food you’re building and what can it tell policymakers?

We take UK production and consumption, feed use and losses, and then we test interventions and see how they affect greenhouse-gas emissions and self-sufficiency. An example is soil carbon management practices such as how to reduce tillage – the mechanical manipulation of soil to prepare seedbeds – manage crop residues and control weeds. Another is dietary and consumer preference shifts, such as reducing red meat consumption. The twin helps interrogate trade-offs and unintended consequences, and assess whether a bundle of changes can hit net-zero targets while maintaining resilience.

Herbicides like glyphosate illustrate those trade-offs. How do you manage that complexity?

Exactly. No-till – an agricultural technique that plants crops without disturbing the soil through traditional ploughing or tilling – can reduce emissions but may increase reliance on herbicides if weed pressure rises. The point is to quantify those interactions at the system level and compare pathways transparently, rather than assuming any single intervention is universally better in isolation.

How do the field’s data practices compare with astrophysics – and what would you change tomorrow?

Food physics feels like astrophysics did 20–30 years ago. In astrophysics today everybody codes, collaborations are large and data and code are open. When we released Python code on GitHub for food-system models and invited contributions, basically no-one engaged because the skills weren’t there. Many models live in Excel rather than in transparent, version-controlled code.

We need standards, shared datasets, open code and co-ordinated efforts

Sarah Bridle

Even at the policy interface there are gaps: you might get a major report with spreadsheets but not the underlying code or assumptions, which we then have to reverse-engineer. With a problem as urgent as climate change, that level of opacity isn’t defensible. We need standards, shared datasets, open code and co-ordinated efforts.

What advice do you have for physicists or mathematicians who want to follow in your footsteps?

Quantitative modelling, open-source practices and Python-based tooling are highly sought after right now. Help build transparent models and shared datasets, and join or create collaborative efforts that mirror modern astrophysics consortia. Also, find your people. The best advice I got was to “adopt your own mentors”. I worked with a career coach and asked people for 30-minute calls. Many were lukewarm, but a few were transformative and became long-term collaborators. It was painful but made all the difference.

What is a concrete step someone could take now?

One is to bring open-science habits to food-system work: publish code and assumptions, contribute quantitative skills to cross-disciplinary teams, help build shared datasets and reproducible models, and translate findings into accessible tools – like interactive calculators – for policymakers and the public.

What motivates you now?

My motivation is about doing what I can to help with the crisis we’re walking into. It’s a way to channel worries about the future into practical improvements.

Looking a decade ahead, what would success look like for the UK food system?

Success would mean that UK production and consumption are aligned with net-zero targets and that land is used more efficiently so other climate solutions can scale. Through product reformulation and choice, I hope we can make low-impact diets easy by default. I also hope that self-sufficiency and resilience improve – and that open, quantitative modelling with transparent code and assumptions is embedded in policymaking.

The post From galaxies to groceries: how Sarah Bridle made the switch from cosmology to food appeared first on Physics World.

“Solar towers” that convert sunlight into heat could play a useful role in the renewable energy transition, but high installation costs and complex requirements limit their attractiveness to commercial operators. A team of researchers from Germany’s Karlsruher Institut für Technologie (KIT) and the German Aerospace Center (DLR) is now taking steps to change that. By creating a freely accessible database of information about how these plants work, they aim to accelerate research on solar thermal energy and drive improvements that could allow the technology to be more widely deployed in the future.

Unlike photovoltaic panels, concentrating solar power (CSP) plants do not convert sunlight directly into electricity. Instead, they generate heat by using an array of movable mirrors called heliostats to funnel sunlight onto a receiver located at the top of a tower. This heat can be used to drive a turbine to produce electricity immediately, but it can also be stored and used to generate electricity at night or on cloudy days. Depending on the plant’s location and setup, the heat could even be used directly for industrial applications and district heating.

The problem, explains study leader Kaleb Phipps, is that operating solar power tower plants safely and efficiently is a complex and expensive task. “CSP technologies have the potential to help the transition to a renewable energy system,” says Phipps, a research fellow at KIT’s Scientific Computing Center. “However, they are still not financially viable and there are operating challenges associated with them.”

Before researchers can develop and reliably test new, improved processes, Phipps explains that they need access to real-world operational CSP data. “We believe that modern data-driven machine learning methods like ours can help solve a lot of these problems,” he says.

849 gigabytes of operational data

To construct their database, which is known as PAINT, researchers collected data from the CSP tower near Jülich, Germany. These data include the exact positions of the tower’s 2014 mirrors, their dimensions, how they are warped and the way they rotate and tilt. The team also obtained fine-grained weather data for the entire 2021-2024 period under study, plus a further 218 000 images to help determine whether the mirrors were efficiently directing sunlight precisely to the top of the tower.

All in all, the PAINT database contains 849 gigabytes of operational data organized using the SpatioTemporal Asset Catalog (STAC) standard. To make these data FAIR (findable, accessible, interoperable and reusable), the researchers developed software to simplify access to the database and then published the data in a way that is freely available to all users.

Their goal, they say, is for other researchers to use this FAIR database to develop “digital twins”, or virtual replicas, of real-world CSP plants. When combined with machine-learning models, such twins can be used to answer questions such as whether the mirrors are aligned for maximal light absorption (one of the most important parameters for efficient operation) in near real time.

Community reaction

“The fact that we are receiving many positive responses regarding the data and that people seem to appreciate it is our biggest success,” Phipps says. Such responses are especially gratifying, he adds, because constructing databases like PAINT can be an arduous task.

“The main difficulties were about collecting the data, cleaning and unifying it into standard formats and parsing and organising all the metadata, which was originally complete chaos,” Phipps recalls. “We therefore put a lot of time and effort into creating standardized and automated workflows so that the process is as transparent as possible and can be reused for future data.”

The team also faced challenges when trying to convince peers that this work counted as “research”, he adds. “The fact that the data itself didn’t directly result in a new algorithm or method meant that lots of people didn’t believe we would be able to publish the results or achieve anything with them,” says Phipps. “Luckily, we were able to prove the doubters wrong.”

While the PAINT database currently contains data from only one CSP, the KIT researchers, who report their work in Nature Energy, are hoping to expand it. “We really need contributions from other CSP power plants around the world to transform the database into a truly international and diverse source for researchers,” Phipps says. “As data from different facilities is added in the future, it will be possible to develop a common standard for open operational data in solar tower research. This would speed up the development and promote a widespread adoption of this technology.”

The post Solar tower power plants get a data boost appeared first on Physics World.

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The post Quiz of the week: what makes strange metals so strange? appeared first on Physics World.

Astronomers have raised concerns over a decision by the Federal Communications Commission (FCC) to permit the launch of a private satellite that can reflect sunlight onto the Earth’s surface after dark. Astronomers, however, fear that the mirror, and the several thousand that could follow it, will negatively impact both optical and radio astronomy.

The proposal by the Californian company Reflect Orbital involves putting a mirror-carrying-satellite – Eärendil-1 – into low-Earth orbit. Reflect Orbital aims to use the craft to test technology intended to deliver sunlight to solar farms after sunset, thus expanding the production of solar power at a time of peak demand for electricity.

In orbit, the satellite will unfold an 18 × 18 m aluminiumized Mylar reflector that can deliver a roughly 5 km circular spot of light to the ground with about the brightness of a full Moon.

In addition to providing solar power after dark, the company sees its technology as potentially effective for response to disasters, construction work and outdoor events at night.

Assuming Eärendil-1’s flight proves successful, the company plans to launch 1000 larger satellites in 2028, which would be able to reflect as much light as 100 full Moons with 5000 more satellites two years later.

The FCC has approved only the radio operations of “a single demonstration satellite [that is] an example of a potentially groundbreaking technology”. Other aspects of Eärendil-1, however, do not require official authorization.

Ben Nowak, chief executive and co-founder of Reflect Orbital, sees the licence as “the first step toward rigorously testing our technology’s efficacy and the safeguards we have developed”.

Flash points

Orbiting satellites’ impact on astronomy is hardly a new phenomenon. Their burgeoning number has already reduced observing times for optical astronomers, particularly after sunset.

Following the approval, the American Astronomical Society (AAS) has expressed “dismay” at the FCC’s decision. [Eärendil-1] carries the potential for significant harm to our members and the broader community of those who depend on a dark night sky,” the association says in a statement. “[This] could include damage to sensitive research equipment, potential flash-blinding of pilots and drivers, and potential permanent eye damage to anyone looking through a mid-sized telescope.”

While some satellite owners have been open to working with astronomers to reduce the impact on astronomy, astronomer Marcel Agüeros from Columbia University, who is also president of the AAS, told Physics World that Reflect Orbital “has been far less open” to discussing its plans. “We know nothing about the satellite’s orbit, for example,” adds Agüeros.

DarkSky International, a nonprofit organization that aims to preserve and protect the nighttime environment, has now called on the company to commission a “comprehensive, independent environmental impact assessment conducted by qualified experts”.

“The burden of proof rests with the operator to demonstrate that their system will not cause environmental or public harm, and a full, independent assessment is the necessary first step,” notes DarkSky International.

That move is backed by Agüeros, who adds that there doesn’t seem to have been much thought about the consequences of the FCC’s decision. “When you start to mess with the nighttime, there should be a very high bar you have to clear,” he adds. “We’re losing our ability to experience a dark sky – an experience that gives you a sense of your place in the universe that is pretty much unmatched.”

Reflect Orbital spokesperson Christopher Buscombe told Physics World that the company “care deeply” about the night sky and that they “want to preserve astronomical observation”.

“We’re also working with the National Science Foundation to develop a coordination agreement on these questions and look forward to their input,” adds Buscombe.

The post Astronomers express outrage after regulators approve ‘space mirror’ permit appeared first on Physics World.

New insights into the “reverse sprinkler” problem popularized by Richard Feynman have been provided by US researchers using modified rotary sprinklers. The results, which indicate that the reverse sprinkler is driven by the angular momentum induced at its centre by water being drawn in, could shed light on the fluid dynamics of open systems.

Rotary lawn sprinklers are ubiquitous devices that eject water at an angle to the head, thereby generating the torque to rotate and water a 360° area. The puzzle is how – or whether – sprinklers rotate if the problem is inverted and they suck the fluid in rather than blowing it out. A lawn sprinkler will, of course, draw in air, but Feynman conducted experiments with a submerged sprinkler that sucked water in and arrived at conflicting results.

Applied mathematician Leif Ristroph of New York University says that the asymmetry of the problem is not in itself surprising. “You can blow out a candle but you can’t suck it out,” he points out. “When you blow out a fluid through an orifice at a high enough flow rate, it forms a concentrated jet…When you reverse the system and pull in fluid at the same flow rate, the flow does not reverse – it pulls in fluid from all directions. That comes from the irreversibility of the Navier-Stokes equation.”

The correct way to model the system, however, is less clear. Some researchers have argued that the problem should be best solved by considering the total angular momentum of the system. Others focused on the torque exerted on the outside of the structure as fluid enters the nozzles, or the angular momentum that builds up at the centre due to the fluid that flows in from the outside of the arms.

Attempting to disentangle these explanations, Ristroph and colleagues constructed a set of specially designed sprinklers. They submerged the devices before either drawing water out of the centre of each one or feeding it in. Each device’s geometry was designed either to amplify or nullify one of the effects previously proposed to determine the torque and thereby the rotation rate. For example, they tested the impact of the overall angular momentum by comparing devices with “spiral” arms (in which water travelled 360° before escaping) to those with S-shaped “hookback” arms (in which it doubled back). This did not explain the observed results.

There was one factor, however, that correlated with torque and rotation rate irrespective of the geometry of the arms. “If you measure the angular momentum flux from any one of these designs it’s quantitatively one-to-one with the torque on the solid [in the forward case],” says Ristroph. “The beautiful thing is the same thing works in the reverse case, except now you should look at the centre where these arms begin, and there are very subtle asymmetries that inject angular momentum to the core of the device…That’s the common unifying principle: in all cases there are jets generated, but in the reverse case those jets are pointing in.” The lower torque at the centre makes the sprinkler much slower in reverse.

Mechanical engineer Earl Dowell of Duke University says that “the study in the paper is largely experimental,” although he acknowledges that “the experiments appear to have been carried out competently and the results presented in a well-organized manner”.

“What the authors call theories are notional ideas based upon highly simplified concepts that tend to be favoured by some physicists,” Dowell adds. “An expert in fluid mechanics…would attack this problem with well-established computational models for the flow field and rigid body dynamics for the sprinkler per se.” He believes that this is not, to his knowledge, being done because neither experiments nor computational simulations are expected to reveal any fundamental new concepts in fluid mechanics.

“I have a hard time thinking this going to generate a practical device,” concedes Ristroph. However, he says that entirely new methods were needed to conduct these experiments and the researchers are now developing new computer simulations of fluid dynamics, in which fluids enter and escape from the system, to apply to it. “This is a beautiful problem to test your experimental methods, your computational methods, modelling, theory…This is a place to give it the best test it can possibly have.”

The research is published in Proceedings of the National Academy of Sciences.

The post Experiments provide new insights into the reverse sprinkler problem appeared first on Physics World.

“Strange” metals owe at least some of their peculiar properties to the quantum entanglement of their electrons. This finding comes from physicists at the Vienna University of Technology in Austria, who used a concept from quantum information science to guide their experiments. A similar approach, they say, could also yield a better understanding of certain high-temperature superconductors and other correlated quantum materials.

Electrons travel relatively unimpeded through most metals, but in the 1980s, scientists identified puzzling exceptions in certain cuprate high-temperature superconductors. Further examples of this “strange” metal behaviour subsequently turned up in other classes of materials, including heavy-fermion materials, pnictides and organic compounds. This resistive behaviour cannot be explained by theories that treat electrons as independent, non-interacting particles, nor by theories that include interactions while treating electrons as quasiparticles. And although multiple recent theoretical works suggested a possible role for entanglement, experimental evidence was lacking.

A novel statistical tool

To investigate further, a team led by solid-state physicist Silke Bühler-Paschen used facilities at the Institut Laue-Langevin (ILL) in Grenoble, France to perform inelastic neutron scattering measurements on a heavy-fermion metal with the chemical formula Ce₃Pd₂₀Si₆. According to team member Federico Mazza, who conducted this part of the study, the scattered neutrons would normally each transfer their energy to individual particles.

However, when the researchers analysed their data using a concept called quantum Fisher information – roughly, a measure of how sensitively a quantum state depends on a given parameter – they found that they could not explain what they were seeing in terms of particles behaving independently. Instead, the data indicated that groups of at least nine quantum-entangled entities were acting collectively. Mazza says this provides direct evidence of highly multipartite quantum entanglement in the material – and, in turn, a new way of understanding why strange metals are so strange.

The parent state of high-temperature superconductivity

The strange metal state is of great interest because physicists consider it the “parent” state of high-temperature superconductivity, though it also occurs across other materials platforms. “We had suspected that some of the intriguing properties of this state might be related to entanglement but were not able to pin it down until now,” Bühler-Paschen explains. “The results are a great success for us. They confirm that our unusual approach of using methods from quantum information science for solid-state physics studies of novel materials can reveal fundamentally new insight.”

The experiments, which are detailed in Nature Physics, were not without challenges. For starters, the researchers needed to identify an ideal material to study the effect they were looking for and then grow it as a large, high-quality single crystal. Once they secured inelastic neutron scattering beamtime at the ILL’s powerful high-resolution triple-axis spectrometer – a difficult feat in itself – Bühler-Paschen notes that they had to obtain and analyse the data at the highest standards and support it with simulations. “Last but not least, [we had to] communicate with our peers that multipartite entanglement contains valuable information beyond correlation functions and scaling analyses,” Bühler-Paschen recalls.

Rather than being a “detail” of one particular material, Bühler-Paschen says the team’s result suggests that enhanced multipartite entanglement might be an integral part of the strange metal state. Verifying this, however, will require studies on other strange metals across materials classes, she says.

“Looking further ahead, we can envision that this aspect of strange metals finds application in quantum devices,” she tells Physics World. “It could also help us better understand high-temperature superconductors and other materials in which electrons are so strongly correlated that they lose their (quasi)particle nature.”

The post Quantum entanglement explains why strange metals are so strange appeared first on Physics World.

This episode of the Physics World Weekly podcast explores how artificial intelligence can be used to improve the aerodynamics of passenger cars and other vehicles. My guest is David Wheater, who is vice president automotive at UK and US-based PhysicsX.

An aeronautical engineer by training, Wheater spent much of his career using aerodynamics to improve the performance of Formula 1 racing cars for several F1 constructors.

Now, his focus is on using AI-based “large physics models” to improve the performance of mass-produced vehicles. This involves combining computational fluid dynamics simulations with wind-tunnel experiments and real-world testing. In this wide-ranging conversation, Wheater explains the need for high-quality training data and we also explore career opportunities for physicists in this multidisciplinary industry.

The post Large physics models boost the performance of passenger cars appeared first on Physics World.

An exceptionally loud gravitational wave signal has offered an unprecedented glimpse into the region of space near a black hole’s event horizon – the “surface of no return” beyond which nothing, not even light, can escape the pull of gravity. Denoted GW250114, the signal originated from the merger of two black holes, and its unusual strength and clarity meant that astrophysicists could extract information from it that was previously only accessible via theoretical modelling.

Physicists describe a black hole’s event horizon in terms of two parameters: the black hole’s rotation frequency Ω_H and its surface gravity κ. When an object falls into a black hole, it appears to orbit at Ω_H because of a phenomenon known as frame dragging in which the black hole literally drags nearby spacetime along with it as it rotates. This means that objects near a black hole’s edge are constantly in motion relative to observers on Earth.

Regions of space near an event horizon can be described very well theoretically, but observational data has been hard to come by – at least until recently. “Gravitational waves are changing that,” says Sizheng Ma, a postdoctoral researcher at Canada’s Perimeter Institute who led the new study alongside astrophysicist Ling Sun and PhD student Neil Lu from the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) and the Australian National University.

Gravitational waves are ripples in spacetime produced whenever dense astronomical objects such as black holes and neutron stars collide. With facilities such as the Laser Interferometer Gravitational-Wave Observatory (LIGO), Virgo and KAGRA (Kamioka Gravitational Wave Detector) now routinely recording these ripples, Ma says, “something that once sounded almost like science fiction – learning about black-hole horizons through observations – is now becoming a real scientific programme”.

From prediction to observation

In earlier theoretical work, Ma and colleagues in Japan, China and the US predicted that if Einstein’s general theory of relativity is correct, the gravitational waves produced when two black holes merge should carry information about the near-horizon region during the final stage of the merger. This information takes the form of a gravitational-wave component known as a direct wave that oscillates around a value that is twice that of Ω_H. “The big question was whether such a signal could actually be seen in real gravitational-wave data,” Ma says.

The main challenge, he explains, is that gravitational-wave data are hard to interpret. “Interesting features can appear for many reasons, so we had to be very cautious,” he says. “We needed to separate this possible direct-wave signature from the much stronger and better-known ‘ringdown’ signal of the final black hole, and then check whether the remaining pattern behaved as the theory predicted.”

When the LIGO-Virgo-KAGRA network detected GW250114 last year, the astrophysicists realized they were in luck. With a network signal-to-noise ratio of approximately 80, this event was around three times louder than LIGO’s first gravitational-wave signal in 2016, and it gave the team a rare opportunity to test their prediction against data. “Our new analyses have allowed us to decrypt the signal and measure Ω_H and κ for the first time,” Ma says.

“A new way of studying black holes”

Even with an unusually clear signal, Ma acknowledges that the work required “careful modelling and many double-checks to make sure we were not overinterpreting a feature in the noise”. But if the team’s interpretation holds up, Ma tells Physics World that their method could become a new way of studying black holes. Gravitational-wave observations have already enabled scientists to study how black holes orbit, merge and settle down, Ma notes. The present work extends this by offering access to the near-event-horizon region during the merger’s final stage.

“That gives us a new observational handle on some of the most extreme predictions of Einstein’s theory, allowing us to perform sharper tests of this theory and better understand how black holes form and relax after a merger,” he says. “It also allows us to explore whether the near-horizon region behaves exactly as Einstein predicted.”

The researchers’ next step will be to improve their direct-wave model so that it describes realistic black hole mergers in greater detail. “On the observational side, we want to apply the analysis to more gravitational-wave events,” Ma says. “The result detailed in this study comes from one exceptionally loud and clean event, so the most convincing confirmation would be to see the same kind of near-horizon signature in other black-hole mergers.”

The good news is that as gravitational-wave detectors continue to improve, the researchers hope to collect more such high-quality events. “These will allow us to test whether this pattern appears consistently in the way general relativity predicts and eventually turn this first result into a more systematic way of studying the regions near black hole horizons,” Ma says.

The research is published in Nature.

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How did you get on?

9 words Warming up nicely

13 words Getting hot, hot, hot

17 words Top dog!

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Patient-specific quality assurance (PSQA) plays an essential role in the safe and effective delivery of radiotherapy to cancer patients. Enabling a “dry run” in which the treatment plan is delivered to a physical device before the patient enters the room, PSQA provides a final safety net before treatment. The aim: to ensure that the correct dose is delivered to the correct location for every patient and every single fraction.

That said, measurement-based PSQA is not sensitive enough to catch all errors – some still slip through. What’s more, pre-treatment measurements are not feasible in online adaptive radiotherapy, where treatment is re-planned and delivered within minutes. There’s simply no time to deliver the new plan to a phantom while the patient waits on the couch

And as clinics increasingly adopt adaptive workflows, incorporate artificial intelligence (AI) into the treatment chain and deliver more complex, more automated and faster radiotherapy than ever before – is it time to rethink radiotherapy QA? Could properly commissioned delivery techniques render routine measurement-based PSQA obsolete?

This was the question discussed at the QA & Dosimetry Symposium (QADS) hosted earlier this year by Sun Nuclear. In an animated debate, Victor Hernandez of Hospital Universitari Sant Joan de Reus in Spain and Dirk Verellen of the University of Antwerp and Iridium Netwerk in Belgium, considered the options.

Far fewer PSQA measurements

“We are debating today because we have a problem,” said Hernandez. “Measurement-based PSQA is not sensitive, not efficient and just not working.” The good news, however, is that a simple independent dose calculation – as provided by software-based PSQA – is an order of magnitude better at detecting failures than measurements.

Hernandez emphasized that to make this shift, it’s essential to commission and standardize the whole radiotherapy process, including not just the linac and treatment planning system (TPS) but the PSQA system itself, to optimize how it is used and understand its limitations. Perhaps the most important step is commissioning the treatment planning process – or “QAing” the plan characteristics. “Less complex plans tend to be more accurate and more robust to uncertainties,” Hernandez explained. “So you need to evaluate and minimize plan complexity during treatment planning.”

He proposed a simple process for QA of treatment planning, based on class solutions (pre-defined dosimetric objectives and geometric parameters) that incorporate complexity metrics in their definition. These class solutions are validated using measurements and used to standardize treatment planning. If a final plan falls outside of the class solution, it will require verification using both measurements and software. But most clinical plans will be within a class solution, where software-based verification will suffice.

Hernandez noted that if you’re performing less PSQA, then machine QA becomes more important and must be reinforced. This could, for example, involve measurements of a fixed set of complex plans every few weeks to make sure that the linac is stable. “But that’s no longer PSQA – it’s part of your machine QA programme,” he emphasized.

“You can perform treatment planning without controlling or evaluating the plan parameters, but then there’s no consistency in your plans and you need pre-treatment measurements of all plans because you’re not in control,” he explained. “Or you can control the plan parameters. Then you reduce variability, improve robustness and quality, and you don’t really need PSQA measurements anymore because that’s part of QA, which is of course, much more efficient.”

“That’s my vision for enhancing safety and advancing QA,” Hernandez concluded.

The unknown errors

Verellen was less convinced that measurement-based PSQA is obsolete. Contemplating Hernandez’s arguments, he agreed that phantom-based pre-treatment PSQA is “just recommissioning over and over again”, noting that “you won’t see any errors in your PSQA unless you have done your commissioning wrong.”

He concurred that accurate commissioning should pick up any mechanical or dosimetric errors, dose tracking can account for anatomical variations, and surface- and image-guided radiotherapy can address positioning errors. “And we also have in vivo dosimetry,” he added. “So in principle, we are covered.”

But sometimes, the things that go wrong are the things nobody thought to look for. “You might have a very good plan, but are you really sure that everything is covered?” he said.

One obstacle is knowing which metrics to use to define a complex plan. Another problem lies in the onslaught of new technologies such as online adaptive that create and deliver a plan in minutes. Verellen pointed out that companies are selling complex adaptive systems as a plug-and-play option that can be commissioned and treating patients in just a few weeks. “Your department is not ready for that. You don’t have the procedures. People are not trained for that,” he emphasized.

And as software is updated, hardware is upgraded and AI is rapidly becoming inherent in ever more stages of the radiotherapy workflow, it becomes challenging to rely on existing procedures. “With this large-scale introduction of AI and automation, we really start to rethink our role as humans in monitoring that process,” said Verellen.

The big challenge is to anticipate each and every kind of error that could possibly occur. And as Verellen pointed out, radiotherapy is much more than just the treatment machine. “There are a lot of people [involved] and they may make mistakes,” he said. “The interactions of the different system components make things so complicated that it’s very difficult to really anticipate all the things that might go wrong.”

What’s needed is a way to evaluate, validate and monitor the entire treatment chain, and a way to detect and avoid catastrophic events. Currently, pre-treatment PSQA is still an important safety barrier in this respect, he emphasized, by detecting the small, unexpected errors that could add up to create a catastrophic event. Moreover, in vivo dosimetry (IVD) will become even more important as a final safeguard of quality that, in the case of online adaptive radiotherapy, will need to evolve into real-time IVD.

“We need rigorous commissioning, but we need to realise that this cannot predict every situation,” said Verellen. “That’s my main point: as my father used to say, ‘don’t throw away your old shoes before you have the new pair’  – this is why we still need pre-treatment patient-specific QA at this stage … until we’ve figured out how to deal with the new developments.”

Near agreement

Remarkably for a conference debate, Hernandez and Verellen agreed on many points – in particular, that the field requires a redefinition of radiotherapy QA. “AI and automation are like a tsunami coming over us and we are not prepared for it,” said Verellen. “We have to step back and rethink the QA of the process.”

Where they differed, however, was on whether it is safe to abandon current PSQA measurement practices right now. “We know where we want to go, but we’re not there yet,” said Verellen.

“I agree with Dirk about many things,” said Hernandez. “But pre-treatment verification to a phantom is not patient safety. That’s why we need to make sure that our plans are accurate and robust, then you can verify it in every single fraction.”

“That works if the flow goes according to plan,” Verellen countered. “But unpredictable things happen.” He likened the risk to that of skydiving, where sky divers spend much time meticulously folding the parachute to guarantee that it will open. “But I’ve never seen a sky diver jumping without a reserve parachute,” he said. “For me, pre-treatment PSQA is my backup, until we have a solution that’s more or less watertight. And at this moment, it is not.”

Both agreed that the way forward is to focus, not just on the machine or the plan, but on understanding and verifying the entire treatment process – particularly the treatment planning and delivery processes. Treatment verifications such as real-time beam monitoring systems and IVD are also crucial for patient safety. “We need to think about how to better monitor all these processes to really advance QA and improve safety for patients,” said Hernandez.

The next frontier

While the QADS debate was framed as “measurement versus calculation”, Greg Robinson from Sun Nuclear reiterates that the real evolution is the shift from checking a device to monitoring the entire process, driven by the introduction of automation and AI.

“The debate was interesting because they were arguing for both extremes, but I think the field is going to land somewhere in the middle,” Robinson tells Physics World. “It’s not that physical measurements are going away, but the frequency by which clinics are doing these measurements is dropping.”

Verellen pointed out that to enable the uptake of software-only PSQA, “we need QA tools that monitor the process”. One option for completely virtual pre-treatment QA is the DoseCHECK secondary 3D dose calculation algorithm and PerFRACTION, both part of SunCHECK from Sun Nuclear.

“SunCHECK brings machine and patient QA together in a single platform,” explains Robinson. “[This] lets a clinic see relationships that isolated tools miss; for instance, when a change in machine performance begins to show up in patient results.” Meanwhile, for adaptive online radiotherapy, AdaptCHECK provides an independent secondary check of the adapted plan within the session time frame.

Looking further ahead, Robinson predicts that the next frontier will be “turning connected QA data into understanding”. In other words, ensuring that errors are not just detected, but can be understood and prevented. “It isn’t enough to tell a physicist that a result passed or failed – the value is in the why: what’s trending, what’s related, what’s likely to drift next,” he explains. “Sun Nuclear is developing new solutions to help physicists untangle the meaning behind all of this data, and make connections across machine and patient data much more seamless.”

Robinson concludes that measurement-based PSQA is not obsolete, but can no longer stand alone. “The future is an independent, connected, insight-driven QA layer that spans machine and patient, works where measurement can’t, and explains the results it produces,” he says. “Quality first, delivered by automation and intelligence rather than replaced by them. That’s exactly where Sun Nuclear is investing.”

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The New York Times recently published a 124-page special issue of its Style Magazine entitled “How to be cultured”. According to the cover of this glossy, ad-driven supplement, the contents were “idiosyncratic” but amounted to a “compendium of what you need to know right now”. The material had been “chosen by experts” for the purpose of “teaching readers how to be more cultured”.

Curious as to what would be included, my hopes were raised by the magazine’s lead editorial. It said that the issue “celebrates expertise, a quality ever less valued in our culture today, where learnedness and firsthand research can be overshadowed by slick presentation and dumb certainty”.

Now, I’m not naïve. I know that the New York Times Style Magazine caters to advertisers, who in turn cater to wealthy readers who feel the need to spend gobs of money to get culture. It didn’t therefore surprise me to have to leaf through 40 pages of adverts for jewellery, champagne, watches and home furnishings before finally coming across the table of contents.

I saw headings for film, food, music, theatre, fashion and the visual arts. Shakespeare showed up several times: over half a dozen plays, sonnet #94 and one of his monologues. There were entries for 1930s movies, animated videos and films from Brazil. One page on food and drink covered porridge from Norway, meat from Mexico, lemonade from Vietnam and wine from Austria.

There was no mention of science in “How to be cultured”, nothing at all

Novels from the US, UK, France, Japan, India and Brazil made the list, as did selections of music from medieval times to opera and hip-hop. Samples of theatre, puppetry and architecture made it in too. But there was no mention of science, nothing at all. The closest I found were architectural materials such as plaster, glass, steel and textiles.

Snow’s lament

The absence of anything scientific should not have shocked me; in fact, it reminded me of the British scientist and novelist C P Snow’s 1959 essay The Two Cultures and the Scientific Revolution. Even back then, Snow lamented that humanists and scientists were living in two separate cultures divided by a “gulf of mutual incomprehension”.

In the essay’s most famous passage, Snow wrote that “a good many times I have been present at gatherings of people who, by the standards of the traditional culture, are thought highly educated and who have with considerable gusto been expressing their incredulity at the illiteracy of scientists”.

“Once or twice,” he went on, “I have been provoked and have asked the company how many of them could describe the Second Law of Thermodynamics. The response was cold: it was also negative. Yet I was asking something which is about the scientific equivalent of ‘Have you read a work of Shakespeare’s?’”

Snow did not stop there. “I now believe,” he continued, “that if I had asked an even simpler question – such as, ‘What do you mean by mass, or acceleration’, which is the scientific equivalent of saying, Can you read? – not more than one in ten of the highly educated would have felt that I was speaking the same language.”

“So the great edifice of modern physics goes up,” he concluded, “and the majority of the cleverest people in the western world have about as much insight into it as their neolithic ancestors would have had.”

Culture club

Snow’s tone was snobby and arrogant, but he was on to something. Can someone who knows nothing about, say, Einstein’s equation E = mc² or about Heisenberg’s uncertainty principle really be called cultured? Sure, cultured individuals don’t need to know much about these topics. But they ought at least to realize that those equations concern how mass and energy work and the inherent limitations to what humans can know.

I’d say those are principles fundamental to the formation, maintenance and fate of the universe – and ones that a cultured person ought to know something about. Indeed, references to them are routinely found in arts and popular culture. Einstein’s equation has made the cover of Time magazine, while the uncertainty principle has been taken up by novelists, theologians and comedians.

Shouldn’t a cultured person be acquainted in some way with the existential threats facing the world?

Further, shouldn’t a cultured person be acquainted in some way with the existential threats facing the world? Wouldn’t such a person have to have an inkling of the way a carbon molecule absorbs and emits heat, of how vaccines work, and of safe and unsafe levels of substances toxic in high doses? How cultivated can an ostrich be?

Of course, there was nothing about the second law in “How to be cultured”, or about any other science of the sort Snow had in mind.

Nothing about scientific equations, experiments, theories or facts that a cultured person ought to know.

No discussion of dark matter, dark energy or of quantum physics, genes or vaccines. Nor about the Pythagorean Theorem or the double-slit experiment.

The critical point

Culture refers to the influences and values that are embedded in the way we live. Judging such influences and values – deciding which influences and values ought to be so embedded – is a tempting but arrogant game.

So let’s play. Imagine that you are among the experts charged with compiling a “compendium of what you need to know right now”. What would you include of science – and why? Send me your contributions, and tell me why they are what we need to know, and I’ll write about them in a future column.

The post Tell us what science you need to know to be ‘cultured’ appeared first on Physics World.

The free-to-read Physics World Instrumentation and Vacuum and Briefing 2026 is now available. It includes R&D updates, interviews that explore technology commercialization, and a fun look at the quirky side of SI units.

One topic covered in the briefing is the world of quantum sensors. Over the years, physicists have developed some amazing quantum sensors, but many of the technologies have stayed in the lab because of the challenges of miniaturizing key components. With ultrahigh vacuum (UHV) playing an important role in quantum sensors based on cold atoms, Florence Concepcion of the UK-based firm Aquark talks about her mission to reduce the size and energy consumption of UHV systems.

Elsewhere in the issue, we look at how manipulating individual living cells plays an important role in biology and medicine. Trouble is, cells tend to stick together when grown in vitro and separating them often involves using harsh chemicals that can damage cells or modify their properties. In a special interview, Luke Cox, who co-founded the UK-based firm Impulsonics, discusses its system that uses ultrasound to gently separate living cells.

Another entrepreneur featured in this briefing is Brian Pogue, co-founder of DoseOptics. The US-based company has developed a system that detects the extremely faint Cherenkov light that is emitted when a radiotherapy beam strikes a patient’s skin. This allows the radiotherapy to be monitored in real time, ensuring that the beam passes through the target tissue and avoids healthy areas of the body.

Also included is a look at the use of intense laser light to accelerate particles. Find out how researchers in the US have created a compact, free electron laser that is driven by a laser plasma accelerator (LPA) – and it has also been used to create a beam of muons.

Finally, you can explore some of the curiosities of the International System of Units (SI), which is the bedrock of metrology. Although SI and its predecessors have been honed and re-defined over the centuries, it still has some surprising quirks. Ben Stein from the US National Institute of Standards and Technology explores some of these oddities including how the candela was derived from the brightness of a candle made from whale fat and beeswax – and the ongoing debate about using the dimensionless radian as the SI derived unit for planar angle.

• Read the Briefing now.
• You can also watch our Physics World Live Quantum metrology panel discussion.

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A collaboration of researchers in North America has reported their findings from the first diagnostic X-ray imaging performed in space. X-ray images recorded during an orbital spaceflight exhibited similar overall quality to those taken preflight on Earth, demonstrating the feasibility of adding radiography as a diagnostic tool for crew health.

With humans venturing further into space and spending more time in this harsh environment, the risk of adverse medical events increases. Accurate and timely diagnosis and treatment is a must-have. Currently, the only reliable medical imaging modality available to astronauts in spaceflight is ultrasonography – which is operator dependent, requires substantial training and relies on limited acoustic windows.

X-ray imaging, on the other hand, benefits from low operator dependence, rapid acquisition and typically higher spatial resolution than ultrasound. Digital radiography could also offer superior diagnostic capabilities for many medical conditions of concern during spaceflight, including dental disease, musculoskeletal trauma, inhalational injury, collapsed lung and arthritis.

Traditional X-ray scanning systems are bulky, produce a lot of radiation and are sensitive to motion – making them less than ideal for sending into space. But a new generation of portable X-ray scanners shows potential to survive the spaceflight and be operated by crew members with minimal training.

“It’s been a dream for aerospace medicine to have more than one imaging modality for diagnosing illnesses and injuries in space,” says lead researcher Sheyna Gifford, an assistant professor of aerospace medicine at the Mayo Clinic in Rochester, MN, in a press statement.

Scanning in space

In a study led by co-author David Lerner, the researchers first demonstrated the feasibility of X-ray imaging in simulated microgravity in 2022. During a parabolic flight, they used a commercial off-the-shelf digital radiography system to successfully capture radiographs of a human subject and a phantom during lunar gravity (1/6g), Martian gravity (1/3g) and microgravity.

In this latest project, reported in in Radiology, Gifford and her team investigated the performance of a similar portable digital radiography system aboard the Dragon spacecraft, during the Fram2 spaceflight mission, a 3.5-day polar orbital flight launched on 31 March 2025 on a SpaceX Falcon 9 rocket. The imaging system comprised a commercial off-the-shelf, FDA-cleared, portable, digital X-ray generator (Impact Wireless; MinXray) along with an FDA-cleared flat-panel detector.

Prior to the mission, three crew members received 4 hr of training on the portable X-ray system and acquired preflight X-ray images of the hand, forearm, abdomen, pelvis, chest and a quality control phantom. They then recorded the same anatomic and phantom images whilst in space, and also imaged a smartwatch to investigate the potential for non-destructive testing.

During anatomic imaging, the devices were handheld by the crew members, while the phantom and smartwatch were secured to the detector for imaging. The crew reported that they found it easy to use the X-ray system and follow the imaging protocols.

Back on Earth

To assess the quality of the seven X-ray images acquired by the crew, three independent radiologists evaluated and compared the preflight and in-flight anatomic radiographs, finding no differences in overall image quality, contrast resolution or spatial resolution. For central-body radiographs (chest, abdomen and pelvis), image positioning was worse in-flight than preflight. Despite this, all X-rays achieved good or near-excellent diagnostic quality (rated on a  5-point Likert scale).

Phantom radiographs recorded in space exhibited good spatial and contrast resolution, imaging low-contrast targets down to the smallest 2-mm target and easily visualizing high-contrast meshes ranging from 20 to 60 lines per inch, with 80 lines per inch remaining visible. The smartwatch radiograph clearly showed the watch’s internal components at the submillimetre scale.

The research team found that the X-ray generator had sustained minor re-entry damage, but its internal components and X-ray output were not affected. Similarly, the detector passed visual inspection and quality control tests. The researchers also recorded a set of postflight X-rays (on non-crewmembers) following the same in-flight protocols. These showed no qualitative differences from the preflight or in-flight radiographs.

“By acquiring the first human and equipment X-rays in space, our study demonstrates the feasibility of in-orbit radiography and expanded diagnostic capabilities for crew health and hardware evaluation,” says Gifford. “Acquiring diagnostically useful X-rays in space is something that anyone can do. Three very talented nonmedical people with four hours of training in one of the harshest environments did it right and did it well.”

Gifford points out that a spaceflight-ready radiography system could also prove indispensable for mission-critical non-medical tasks. “For sustained human presence in space, X-rays are critical not just for crew members but also for other mission components like electronics and spacesuits. The only way to look inside these objects without taking them apart is to X-ray them,” she explains.

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Quantum mechanics has two seemingly competing rules. Firstly, a system evolving without measurement follows a continuous, deterministic evolution governed by the Schrödinger equation, with dynamics determined by a Hamiltonian. Secondly, when a measurement occurs, the wavefunction collapses, producing a sudden, discontinuous change that is not derived from a Hamiltonian. Several approaches attempt to reconcile these behaviours, including the Copenhagen interpretation (which does not explain the mechanism of collapse), decoherence theory (which does not provide a single definite outcome), stochastic collapse models, and continuous measurement theory.

In this work, measurement is not treated as fundamentally different. Instead, it is described using stochastic (random) Hamiltonians that generate continuous evolution of the quantum state. In this picture, collapse emerges from noisy dynamics. The authors show that these dynamics can be understood as double-bracket gradient flows, where the system is driven to align with a measured observable, steadily reducing uncertainty until it reaches a definite outcome. Thus, wavefunction collapse can be viewed as coarse-grained continuous dynamics that minimise the variance of the observable. By interpreting this as a gradient flow, the same mechanism can be exploited using feedback to drive a system into desired states, including entangled ones.

This approach provides a continuous and physically interpretable picture of wavefunction collapse. Compared to decoherence theory, it explains the emergence of a single outcome but does not specify when measurement dynamics begin. More broadly, it replaces the notion of collapse with a dynamical process, making the theory more internally consistent, while also offering practical tools for controlling quantum systems, which is important for quantum computing and experiments.

“These geometric connections between Hamiltonian dynamics and quantum measurements open the door to exciting new approaches to quantum algorithm design.” – Aaron Villanueva, Radboud University

Do you want to learn more about this topic?

Genuine quantum correlations in quantum many-body systems: a review of recent progress by Gabriele De Chiara and Anna Sanpera (2018)

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Percolation studies how small connections can group together to form a larger connected system, known as a cluster. In a grid where sites can be turned on or off, turning on more sites leads to the formation of clusters, and at a certain point a giant cluster spanning the system emerges. This behaviour is relevant to many real-world systems where local interactions lead to global effects, such as power grids, disease spreading, forest fires, and brain activity. While percolation is often studied using theoretical models or simulations, real systems are more complex. Nonlinear effects, noise, imperfect connections, and time-dependent dynamics can all shift the tipping point and change how clusters form.

In this work, the researchers built a physical system using a 2D array of 100 coupled lasers to study percolation experimentally. Each laser acts as a site that can be turned on and interacts with its neighbours, making the system a controllable realisation of a percolation grid. They found that when a large connected cluster forms, the lasers also begin to phase-lock, meaning that connectivity and synchronisation emerge together. Normally, these effects are studied separately.

At high pump power (the energy supplied to the lasers), the system behaves like an ideal percolation model, with a clear critical threshold and a smooth (second-order) transition, consistent with theory. However, at low pump power, nonlinear effects become important. The lasers compete more strongly, meaning more active sites are needed to form a spanning cluster, and weaker clusters are suppressed. This shifts the percolation threshold and alters the cluster size distribution, contrary to the usual expectation that nonlinear effects are stronger at higher power.

To explain this, the researchers introduced a simple model where a site only remains active if it has enough active neighbours, effectively modifying the connectivity rules. This reproduces the observed behaviour and shows how nonlinear effects can reshape percolation. Overall, the work demonstrates that real physical systems can significantly modify ideal percolation behaviour, and provides a controllable platform for studying how connectivity, competition, and synchronisation interact in complex networks.

Do you want to learn more about this topic?

Percolation theory by J W Essam (2018)

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Private fusion companies have raised almost $4.5bn in funding over the past year – a 70% increase year-on-year. That is according to a report on the state of the fusion industry, which was published yesterday by the Fusion Industry Association (FIA). The report – The Global Fusion Industry in 2026 – also finds that private fusion endeavours now employ over 16,000 people worldwide.

The report surveyed 56 private fusion companies around the world – most of which are based in the US and Europe. Some of the biggest players in private fusion include Commonwealth Fusion Systems (CFS), General Fusion, TAE Technologies and Tokamak Energy.

Magnetic confinement, in which magnetic fields are used to contain a high-temperature plasma, is the most popular fusion technique, being used by 48% of firms according to the report. Inertial confinement, which uses rapid compression, usually by lasers, to create a confined plasma for a short period of time, is employed by 21% of firms – with other techniques such as magneto-inertial making up the remainder.

While electricity generation is a main target for private fusion companies, many also see the technology being applied to space propulsion, with other markets including marine propulsion, hydrogen fuel and industrial heat.

The funding boost for this year’s figures has come from major funding rounds, with CFS raising $863m in August 2025 while Inertia Enterprises, Helion Energy and Proxima Fusion have raised about $1.5bn in total this year.

Ambitious goals

The first FIA report on the fusion industry was published in 2021, where it found that private fusion endeavours had received over $1.8bn of funding since the 1990s.

The 2021 report discovered that over two-thirds of the 35 companies surveyed thought that electricity generated from fusion would enter the grid in the 2030s, with a further 20% thinking it would more likely come in later decades.

That confidence, however, has grown – with this year’s report finding that 71% expect the first fusion plant to deliver commercial electricity by the 2030s.

Indeed, FIA chief executive Andrew Holland says he is “confident” that commercial fusion will be delivered in the 2030s.

“Alongside private investment, fusion companies still need the support of governments to address common challenges including the availability of resilient materials and the fusion fuel cycle,” he says. “The governments that update their programmes and funding priorities to meet the sector’s needs today will be the ones to capitalize on this vital emerging industry.”

The report comes as General Fusion has become the first fusion company to be publicly listed. It joined the Nasdaq exchange with $150m in fresh funding, which is expected to go towards the firm’s Lawson tokamak programme that is expected to be complete in 2028.

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In The Hitchhiker’s Guide to the Galaxy, Douglas Adams imagined a supercomputer called Deep Thought, built by a race of hyper-intelligent beings to calculate the Answer to the Ultimate Question of Life, the Universe and Everything. After a mere seven and a half million years of computation, the machine finally revealed its answer: 42.

There was just one problem. Despite their hyper-intelligence, none of those beings understood what the question had been. The joke was that any answer – no matter how precise – is meaningless without a thorough understanding of both the question and the route taken to obtain the answer.

Yet what was once purely science fiction is beginning to sound unexpectedly relevant to modern research. From structural biology to particle physics, artificial intelligence (AI) systems are increasingly involved in research, providing results of remarkable power and accuracy. They are being used to identify hidden patterns in vast datasets, to generate hypotheses, to accelerate simulations and to guide experiments.

As AI becomes increasingly embedded in the scientific process, could we be entering an era of discoveries without understanding?

But in some cases, even the creators of those AI systems are struggling to explain exactly how the AI arrives at its  conclusions. All of which raises an uncomfortable possibility. As AI becomes increasingly embedded in the scientific process, could we be entering an era of discoveries without understanding? And if so, what happens when science starts producing its own versions of the answer “42”?

AI and accelerated particle searches

For particle physicists, this question is no longer hypothetical. At CERN, the home of the Large Hadron Collider (LHC), AI is already woven into day-to-day research, subtly reshaping how physics research is carried out. Indeed, machine learning (ML) – one of the main pathways through which AI is achieved – has long played a role at the LHC.

Back in the early 2010s physicists working at the CMS and ATLAS experiments, routinely used ML in their search for the Higgs boson. The ML algorithms separated rare signals – a Higgs boson decaying either into two photons or into four leptons via Z bosons – from far more common Standard Model processes that produced similar signatures in the detector.

Machine learning did not discover the Higgs boson by itself, but it accelerated the search by making analyses more sensitive. In fact, achieving the same sensitivity without ML would have required between 15% and 125% more data, according to a review of Higgs-decay measurements (Nature 560 41). Some measurements would even have needed more than double the data.

But the scope of AI in particle physics has been expanding rapidly since then. Neural networks are now used to compress enormous datasets, accelerate simulations, and identify unusual events hidden among billions of particle collisions. By learning directly from examples, neural networks can uncover complex correlations in detector data that would be difficult for physicists to unravel using conventional analysis techniques.

Caterina Doglioni, an experimental particle physicist from the University of Manchester, UK, who uses ML for data compression as part of the ATLAS collaboration, says that deployment of AI is becoming difficult to separate from particle-physics research itself. “It’s pretty much everywhere,” she says, especially when it comes to experimental high-energy physics. “It’s critical at the LHC where far more data is created than can realistically be stored.”

When it comes to compressing detector data, for example, one option is to use neural networks to force information through a computational “bottleneck” that preserves the most important features while dramatically reducing the storage required. The original data can then be reconstructed from this compressed summary, either exactly or approximately depending on the application (Rep. Prog. Phys. 84 124201).

This is different from the ML techniques used during the Higgs search. Whereas Higgs analyses relied on supervised algorithms that had been trained to distinguish known signals from background noise, these data-compression methods typically use “self-supervised” learning. They identify and preserve important patterns – without requiring labelled examples.

Algorithms learn what ordinary collisions look like and then flag events that deviate from those expectations

More recently, researchers have begun applying ML to a very different challenge. In the Higgs search, algorithms were trained to recognize signatures predicted by theory and distinguish them from background processes. But now, instead of having algorithms that search for a specific predicted signal, those algorithms learn what ordinary collisions look like and then flag events that deviate from those expectations.

In what is essentially a clever form of anomaly detection, the hope is that new physics might reveal itself as something unusual, even if physicists do not yet know exactly what form it will take. In a nutshell, ML used to be applied to problems where physicists knew what they were looking for; now it is applied to problems where we don’t know what we’re looking for just yet.

While no new particles have yet been spotted with these anomaly-detection techniques, they have progressed from theoretical proposals to real experimental searches. In 2024, for example, the ATLAS collaboration reported the results of an unsupervised anomaly-detection search using Run 2 data. No significant deviation from Standard Model expectations was observed, but the study proved that such methods can be deployed successfully on real collider data (Phys. Rev. Lett. 132 081801).

The black box problem

Yet the very feature that makes these systems so powerful – their ability to rapidly identify patterns humans may miss – also raises one of the most persistent concerns surrounding AI in research: the black box problem. Modern ML systems can uncover complex relationships in data, but researchers may struggle to understand exactly how a model arrived at a particular result. In particle physics, where extraordinary claims require extraordinary evidence, that lack of transparency can create unease.

For David Sutherland, a theoretical physicist at the University of Glasgow, the greater concern is not necessarily whether researchers can interpret every internal feature of a model – but whether they can trust and reproduce its outputs. “I would certainly say reproducibility [is more important] than interpretability,” he says.

That distinction matters. Science has always relied on the principle that results should survive scrutiny, be independently verified, and withstand repeated testing. A model does not need to reveal every detail of its inner workings – but researchers must be able to demonstrate that it behaves robustly across datasets and conditions.

Particle physics, in particular, has built extensive safeguards around that process. “We have very large review committees that check basically everything that goes on,” Doglioni says, with those structures providing an additional layer of protection against over-reliance on opaque systems.

Reliability and reproducibility

Yet as AI systems become increasingly embedded in research workflows, ensuring that reliability may become more difficult. Reproducing results may require not only access to data and code, but also to model architectures, training conditions and computational environments.

Unlike many commercial AI systems, the ML tools used in particle physics are often developed by particle physicists and shared openly with the scientific community. Even so, reproducing results may require access not only to data and code, but also to model architectures, training conditions and computational environments, all of which can influence an AI system’s behaviour.

The growing use of AI could also begin to change how physicists work and even how scientific value is measured. Christoph Weniger, a physicist at the University of Amsterdam who applies ML and AI techniques to particle physics and cosmology, argues that AI systems are likely to take on an increasingly active role in navigating complex analyses. Researchers, he believes, will shift into “a supervisory role in steering these different agents”, fundamentally changing how scientists interact with data.

AI and materials science

Particle physics is far from the only field exploring how AI might reshape scientific discovery. Researchers at Argonne National Laboratory in Illinois, US, recently developed what they describe as an AI adviser for designing advanced electronic materials.

Normally, materials discovery proceeds through a slow cycle of trial and error. Scientists propose a candidate material, synthesize it in the laboratory, test its properties and then refine the design. Each iteration can take days or weeks.

The Argonne system closes that loop. AI proposes candidate materials, robotic laboratories create and test them, and the results are fed back into the system to guide the next round of experiments.

Rather than analysing data after experiments are complete, AI becomes involved in deciding which experiments to perform in the first place, an early glimpse of what future “AI scientist” systems might look like.

The approach has already demonstrated its potential. In 2023 researchers at Argonne and collaborators reported that their autonomous A-Lab platform conducted 355 experiments in just 17 days and successfully synthesized 41 novel materials (Nature 624 86). The work provided one of the clearest demonstrations that AI systems can help guide experimental discovery rather than simply analyse data after the fact.

Creative impact

Such changes could extend beyond day-to-day workflows. Traditionally, the currency of academic research has been publications. But Weniger suggests that AI may shift the emphasis away from productivity alone and towards something harder to quantify: originality.

Scientific value may increasingly depend not on how many papers a researcher produces, but on the creativity and impact of the questions they ask

As routine technical barriers to experiments and theoretical work become easier to overcome, he argues that scientific value may increasingly depend not on how many papers a researcher produces, but on the creativity and impact of the questions they ask.

The effects may also extend to how scientific knowledge is communicated. The scientific literature has long been criticized for being difficult to navigate, not simply because of its volume, but also because of the way researchers write. Nichol Furey, a mathematical physicist at Humboldt University of Berlin whose work explores whether there is an underlying algebraic logic to the structure of the Standard Model, believes AI could help bridge that gap.

“Authors in maths and physics often write in ways that are overly opaque,” she says. “AI systems write with their audience in mind, whereas human authors often don’t.” Yet that possibility creates a tension. The same tools that can make research more accessible can also make scientific text dramatically easier to produce.

Communities are already beginning to grapple with the unintended consequences of widespread AI adoption. Recently, arXiv, one of the world’s largest repositories for physics and mathematics preprints, announced a crackdown on unchecked AI-generated submissions. It said it was introducing one-year bans for authors who upload papers containing obvious signs of unverified AI content, such as hallucinated references or leftover chatbot instructions.

The move reflects growing concern about the quality of AI-assisted scientific writing. Although arXiv’s new policy is too recent for its impact to be fully assessed, the threat of a one-year ban marks one of the strongest responses yet by a major scientific repository to unchecked AI-generated content.

The concern is not simply that AI can generate poor research. Now that producing scientific text is an almost frictionless exercise, the burden of judgement shifts increasingly onto readers, reviewers and future researchers trying to separate genuine insight from noise.

Training future physicists

Another potential problem with AI’s infiltration in many areas of research is training the next generation of physicists. This is generally a long process, where expertise is built gradually through years of practice and failure. If AI automates many of those steps, researchers may eventually face an uncomfortable question: how do you train future experts if the work that once trained them disappears?

This challenge extends far beyond physics. Across the education sector, schools and universities are already grappling with the ease with which generative AI can produce essays, solve problem sheets and complete programming assignments in seconds.

In fact, Wrishik Naskar, a particle theory postdoc at the DESY laboratory in Germany, wonders if research habits are also beginning to change. “When I get stuck, I go to my supervisor,” he says, “[but] many people, the first thing they ask is ChatGPT.” That approach might speed things up, but does it really help a researcher learn and grow? As Naskar puts it: “Focus on the learning. Results will follow if you have skills.”

Despite the many concerns, not everyone sees the transition to AI as a threat, and framing AI as a competitor to researchers may miss the point entirely. For example, Admir Greljo, a particle theorist at the University of Basel, believes the real shift is not replacement but collaboration. “It’s not that they will compete against AI. Entering into theoretical physics is still going to be very interesting and very important. AI is not competition, it’s a new tool.”

That perspective echoes a broader historical pattern. Physicists once calculated by hand, then with slide rules, then with computers. Each technological leap changed how research was done and prompted fears about what skills might be lost along the way. Yet rather than eliminating physicists, those tools expanded what physicists could ask.

Towards an AI scientist?

AI may simply be the next step in that progression. But it also presents something new. Unlike previous tools, AI can suggest ideas, identify patterns and increasingly participate in parts of the scientific process that once seemed uniquely human. So might that participation one day become independence? Could AI move beyond assisting physicists and begin carrying out the entire research process itself?

For Sutherland, a future in which AI systems perform the entire research cycle, from generating hypotheses to collecting data and even writing papers, is not difficult to imagine. But he still envisages a human “steering it” and acting as a “sanity check”, much like the relationship between a senior researcher and a PhD student.

Others go further. Greljo believes that fully autonomous scientific systems may not arrive in the near future, but sees no fundamental reason why they could not emerge eventually. Because science ultimately depends on reproducible results, he argues, humans could simply repeat calculations and test predictions to verify whether the AI had reached the right answer. Such a future, he says, is “not something that is impossible”.

We may be entering a world where machines help us uncover truths about the universe faster than we can fully understand them

We may be entering a world where machines help us uncover truths about the universe faster than we can fully understand them. But that need not signal the end of scientific inquiry. It is important to remember that AI models, much like many of the models used throughout scientific research, are imperfect and may always remain so. But perhaps they do not need to be perfect.

Science has always involved navigating uncertainty, constructing incomplete models and refining them over time. AI may help us discover things faster than ever before. It may reshape how future generations of physicists learn, work and think. But science has never simply been about generating results. It has also been about explanation, curiosity and deciding which questions are worth asking in the first place.

We should not treat AI as an oracle that bypasses the scientific method. Instead, we should view it as another tool in the physicist’s arsenal – a powerful one, certainly, but still a tool, helping researchers explore possibilities, test ideas and refine their models of reality.

After all, the problem with Deep Thought was never that it gave the wrong answer. It was that nobody knew what question they had asked.

The challenge for the next generation of physicists may not be deciding whether AI can discover new truths about nature. It may be making sure we still know which questions are worth asking.

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A compact optical technology that has already proved its worth in Earth-bound applications could be on its way to space after researchers at the University of California San Diego, US showed that it can map the Sun’s magnetic field just as well as traditional instruments. By making polarization gratings from specially engineered metasurfaces rather than a complex assembly of optics, the researchers say that future solar-observing missions could benefit from reduced complexity and cost as well as size.

“Our work makes use of recent advancements in nanoscale optical technologies to help improve the hardware for making astronomical observations of the Sun,” says study leader Noah Rubin of UC San Diego’s Jacobs School of Engineering. “We believe this is one of the first times that metasurface optics – which have been a subject of intense interest in both academic research and industry for about a decade – have been used to improve scientific instrumentation of any kind outside of a lab/academic proof-of-concept.”

Polarized light and solar magnetic fields

Although light emitted by the Sun is generally unpolarized – that is, the light waves do not vibrate along a particular axis – strong magnetic fields that develop near sunspots can polarize this light via the quantum mechanical Zeeman effect. These magnetic fields are closely associated with space weather events such as solar storms that can damage electronic infrastructure both on Earth and in orbit. Studying the Sun’s magnetic activity by monitoring areas of polarized light is thus an important step towards detecting or predicting such storms in time to take protective action.

Usually, measuring the polarization state of light means analysing different polarization directions using a device such as a waveplate that mechanically rotates between exposures. Rubin compares this process to taking several photographs through polarized sunglasses held at different angles, then combining them to obtain a fuller picture of what’s going on.

While this technique works, and instruments that use it have already been sent into space, the image analysis process is very time-consuming. It also requires an external power source, and the need to mechanically rotate the waveplate introduces extra complexity and cost, says Rubin.

“In space-based applications, a satellite itself can be moving while this component reorients, causing a highly undesirable blurring effect,” he explains. “As a result, designers of these systems often invest considerable resources into mechanical remediation and engineering to correct the motion of the telescope on the satellite, and this frequently ends up being substantially more expensive than the telescope optics themselves.”

A metasurface solution

In the new study, which is detailed in Science Advances, Rubin and colleagues solved this problem by creating a polarization-sensitive metasurface that splits light into its different polarization components. A camera-like system containing this metasurface polarization grating can then form multiple images of a scene in parallel. Rubin explains that each image in this scene is analysed with respect to a different polarization state, meaning that the system can measure the polarization of light simultaneously and passively in a single camera frame.

Rubin notes that this technique of condensing an instrument that would ordinarily involve a complex assembly of optics into a single, flat surface has previously made its way into applications as diverse as facial recognition in mobile phones and the preparation of complex photon states in quantum optics experiments. “In this work, we show that these advantages translate to polarization imaging in astronomy,” he tells Physics World.

Comparable results

Working with industrial partners at BAE Systems Space & Mission Systems in Colorado, US (formerly known as Ball Aerospace, which Rubin describes as “well-known for its involvement in the development of the James Webb Space Telescope, Hubble and countless other NASA missions”), the team designed a specialized telescope built around such a metasurface polarization grating. They also deployed their instrument on the Dunn Solar Telescope in New Mexico, US, and showed that they could quantitatively map the magnetic fields in sunspots by capturing simultaneous polarization images of these spots.

The researchers report that their results were comparable to those obtained by the state-of-the-art NASA Solar Dynamics Observatory mission in-orbit, highlighting what Rubin calls “the significant advantages that these metasurface components can offer when designed in conjunction with more traditional optical systems”. The UC San Diego team is now exploring ways of integrating its technology into future NASA solar-observing space missions.

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For decades, the Outer Space Treaty (OST) has prevented any nation from placing nuclear weapons in space. To date, however, no mechanisms have been put in place to determine whether a signing member’s satellite may be violating this treaty, or even developing other nuclear capabilities that the original treaty never considered.

Through new analysis of the problem, Areg Danagoulian at MIT suggests a safe and feasible approach to monitoring suspicious satellites, using neutrons emitted as radioactive material is impacted by naturally occurring protons in the Van Allen radiation belt.

At the height of the Cold War in the 1960s, there seemed a growing possibility that space could be used as a platform for developing nuclear weapons. With the prospect of nuclear strikes being launched from orbit with practically no warning, both the US and Soviet governments recognised the possibility of miscalculations by either side leading to a catastrophic nuclear conflict.

In 1967, this led to the signing of the OST: which in part, demands that no signing member should ever deploy nuclear weapons in orbit, on celestial bodies or in outer space. Today, it has been signed by 117 countries, including the US, Russia and China. However, in the decades since the treaty’s origins, both political and technological landscapes have profoundly transformed, creating entirely new concerns that nobody could have conceived in the 1960s.

“In 2022, Russia launched the Kosmos 2553 satellite, which the US has determined is a platform for testing components for a future nuclear anti-satellite weapon,” Danagoulian says. With the ability to target orbiting satellites, such a programme could ultimately destroy vital communication and navigation systems – bringing society to a standstill without any direct strike on the ground.

Despite this threat, no robust mechanism has ever been developed for verifying whether a country is violating the OST, and to date, very little research has even considered the problem.

To Danagoulian’s knowledge, the only related study was an undergraduate thesis by Stanford University student Isobel Portenous – who proposed that suspicious satellites could be probed for nuclear material by measuring radioactivity in the vicinity. However, not only is space already highly radioactive, likely drowning out the signal from a single satellite; it would also require spacecraft to closely approach the satellite, which could be interpreted as a hostile act.

To address this challenge, Danagoulian considered how satellites could instead by probed by naturally occurring, highly energetic protons in the Van Allen radiation belt: which mostly originate from the solar wind, and become trapped by Earth’s magnetosphere.

When interacting with nuclear material in a suspect satellite, “these protons would trigger a process known as spallation in the uranium radiation case of the thermonuclear weapon,” Danagoulian explains. “This would produce a large flux of neutrons that can be detected and used as a fairly specific signature of a nuclear weapon.”

Crucially, the kind of device needed to detect these neutrons wouldn’t need to be too close to the satellite. From a distance of 4 km, Danagoulian calculated that a standard CubeSat detection platform could accurately determine the composition of the nuclear payload of a satellite like Kosmos 2553, within just a week of measurement time.

For now, much more work will be needed before this kind of mechanism can be realistically applied. “Uncertainty remains regarding whether this approach will be practical, so much work is still needed,” Danagoulian says. “Can one build a reliable detector array to perform this measurement? That’s to be determined.”

Yet if these hurdles can be overcome, they could provide a valuable new layer of security in a fast-changing world, and could potentially guide new international policy decisions. “The required physics and basic technology are available to solve this problem,” Danagoulian continues. “If an inspector satellite can be built, it will finally create a mechanism for verifying the OST.”

The study is reported in Nature.

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In 2008 the US author Neal Stephenson published a speculative fiction novel called Anathem. Set on the fictional planet of Arbre, the story follows an order of monks, mostly isolated from the rest of the world, who every so often open up their doors to receive information on the state of the outside world.

In the book, Stephenson explores a Dark Age of the Internet, in which companies flood the network with plausible-sounding-but-false information in a ploy to force consumers to buy the firms’ own tools for distinguishing truth from falsehood.

Initially, this “crap”, as Stephenson calls it, had to be made by humans, but eventually the process is run by a so-called “Artificial Inanity”, which is able to create hundreds or thousands of bogus versions, or “bogons”, for every legitimate document.

Today, we face our own version of Stephenson’s Dark Age as our information landscape increasingly fills with AI slop, now going beyond AI-generated videos of uncanny kittens or images depicting politicians and celebrities in outlandish situations.

With the rise of chatbots powered by large language models (LLMs), our search results, social-media feeds and even scientific journals are getting polluted with data that, at first glance, appears relevant and plausible but contains no value beneath its gilded veneer.

As LLM-generated slop infects our previously trusted knowledge base, we face an information landscape that is quickly rotting beneath us.

As scientists, we must position our work in relation to other recent research. Yet that task gets harder when we have to sort out the real from the hallucinated. As LLM-generated slop infects our previously trusted knowledge base, we face an information landscape that is quickly rotting beneath us.

Where we could once track an idea to a paper with human authors (who bore consequences for acts of fraud), we face a future where we have to question whether an article’s authors, institutions or experiments ever existed, on top of evaluating its scientific merits.

This is not a hypothetical danger. In 2024 a team led by medical researcher Almira Osmanovic Thunström at the University of Gothenburg invented a fictitious medical condition called “bixonimania” and publicized it through posts on Medium and two pre-print papers.

Their goal was to test whether AI chatbots would pick up and propagate word of the fake disease, which they duly did. The researchers even tried to insert information that made the work obviously fake. This included acknowledging a colleague from Starfleet Academy, thanking the University of Fellowship of the Ring for funding, and even writing early on in the article that “this entire paper is made up”.

Trapped in a bog

As physicists, we are not immune to the dangers of information rot. A flood of LLM-generated articles prompted arXiv in May to announce consequences for authors whose submissions have “incontrovertible evidence that the authors did not check the results of LLM generation”, including having “hallucinated references”. Those consequences include a one-year ban from arXiv and the requirement, thereafter, that any submitted paper must already be accepted at a “reputable peer-reviewed venue”.

I initially welcomed the news. Harsh consequences are one way to discourage LLM usage, especially for sloppy shortcuts. But the more I reflect on it, the more I realize that arXiv’s consequences could eventually fall even on those who are not using LLMs to write their papers.

Relying on shortcuts is easy. Say you’re writing a literature review and paper A, which you’ve read and trust, has a fact you want to cite – but you notice that paper A cites paper B for this fact. It’s simple to scroll down to the reference section and copy paper B’s citation into your own citations (I would be lying if I said I’ve never done this myself).

But as the information landscape rots, this shortcut could run you afoul of policies like arXiv’s. What appears to be a valid citation – maybe even containing the names of authors you know personally – can be hallucinated.

We must double down on the skills that make us experts – our scientific judgement, information literacy, communication skills and careful scholarship.

Or it could be entirely fake, as a team of researchers who cited one of the “bixonimania” pre-prints in a peer-reviewed article discovered. Their paper was justifiably retracted by the journal editor, over their objections. By simply copying a reference without double-checking it, you can unintentionally join ranks alongside LLM users. Worse, you open yourself and all of your co-authors to being banned from arXiv.

I am not suggesting that arXiv’s policy is flawed. Rather, I argue that those who intend their writing to be AI-free must be vigilant. We must double down on the skills that make us experts – our scientific judgement, information literacy, communication skills and careful scholarship. We should lean into practising these skills – and teaching them – even though they are precisely the skills that AI companies claim LLMs can replace.

In Anathem, a character simply hand-waves away their Internet full of bogons, but we have no such solution. Instead, as our information landscape rots, we find ourselves trapped in a bog. To get out, we must plan each step carefully and take none for granted. What appears to be solid ground may well prove treacherous. Moving safely is a slow process, full of checking and double-checking as we painstakingly build out paths and tools we can trust.

Simply choosing not to use an LLM when writing is no longer enough. We have only our own scholarly skills to sort the bogons from the ground truth. We will all have to slow down if we want out of the bog.

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Specially engineered materials known as metamaterials can boost heat transfer over nanoscale distances compared with conventional materials, thanks to the coupling of quasiparticles known as surface phonon polaritons. This new result, from researchers at Carnegie Mellon University, Stanford University and Purdue University, all in the US, could help improve technologies such as on-chip cooling and thermophotovoltaic systems.

The maximum radiative heat transfer between two macroscopic-sized objects at different temperatures can be estimated by assuming that the objects are “black bodies”. These are ideal entities that absorb all the radiation falling on them and emit thermal radiation according to Planck’s law. This approximation breaks down, however, when the objects are placed within a few hundred nanometres of each other. In this case, they begin to exchange heat much more strongly thanks to a phenomenon known as near-field enhancement, which can exceed the far-field black body limit by several orders of magnitude. This effect is already put to good use in technologies such as heat extraction and thermophotovoltaic systems.

Until now, near-field enhancement had only been observed and studied in naturally occurring materials, such as polar dielectrics, doped semiconductors and metals, explain the study leaders, mechanical engineer Sheng Shen at Carnegie Mellon and electrical engineer Shanhui Fan from Stanford. Although theoretical studies have predicted that metamaterials could surpass the performance limits of naturally occurring materials, there had not previously been any experimental demonstration of metamaterial-enhanced near-field radiative heat transfer. Identifying such metamaterials would be of great use as it would allow the effect to be exploited more widely.

Heat transfer increased by up to four times

Shen, Fan and colleagues observed enhanced near-field radiative heat transfer in a nanodevice platform comprising metamaterials based on arrays of gold split-ring resonators patterned on silicon nitride membranes. The researchers positioned the metamaterials so that they faced each other across a nanoscale gap, observing that heat transfer between them increased by as much as four times compared with similar setups using ordinary materials.

As well as confirming that radiative heat transfer is enhanced over short distances for these metamaterials, the results suggest that the interaction between metamaterials and surface phonon polaritons is responsible for the increase. These quasiparticles are produced by phonons, which are vibrations of the crystalline lattice, as they interact with oscillating electromagnetic fields at the material surface – in this case, those at the surface of the gold metamaterial structures. This coupling allows heat to tunnel across the gap between them and the silicon nitride membranes more efficiently – something that increases the energy flow between the two, explains Shen.

Heat management applications

According to the researchers, the effect could help enhance and manipulate heat exchange at the nanoscale and could find applications in next-generation cooling for high-performance microelectronics, thermophotovoltaic systems for waste-heat harvesting and high-sensitivity infrared detection.

There are still a number of challenges to overcome before such applications see the light of day, however. On the theoretical side, notes Fan, the complex interactions between the metamaterial units and their supporting substrate make numerical calculations and analyses exceptionally difficult. “To address this difficulty, we have developed a numerical tool based on fluctuational electrodynamics to design the structures, alongside a coupled-mode theory model to fully elucidate the underlying physics,” he says.

Experimentally, measuring nanowatt-level radiative heat exchange across a sub-micron gap also demands extreme precision. The researchers tackled this challenge by designing an on-chip device using a “suspended thermal bridge” method that transforms the minute heat exchange into a measurable temperature rise. Indeed, they succeeded in detecting heat flow of less than 1 nW in these nanodevices.

They report their work in Nature.

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Fancy some more? Check out our puzzles page.

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It is one of the most extraordinary feats of military history – how the Carthaginian general Hannibal managed to cross the Alps with an army of 46,000 men, 7000 horses and 37 war elephants in 218 BCE.

Hannibal’s method was to catch the Romans by surprise by starting from what is present-day France and crossing the Alps into what is now northern Italy.

Yet the exact route that Hannibal’s army took remains a mystery and has been debated for decades given that no records by contemporary historians have survived.

Now theoretical ecologist Emilio Berti from the German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig and Fritz Vollrath at the University of Oxford, UK, have calculated the metabolic cost that the army would have incurred via several possible mountain passes.

The route crossing Col du Clapier – passing first through Grenoble and Aiton before descending into the Po Valley – appeared to be the likely candidate, but recent analysis has suggested an alternative southerly route via the Col de la Traversette.

Using route modelling and elevation data, the team found that the Col du Clapier route would have required 6.28 × 10¹² joules of energy, while Col de la Traversette, however, would have needed 5.42 × 10¹² J.

Yet even on that route, the 15-day crossing would have required 230 tonnes of food and supplies.

The authors calculate that the army would still have lost about a fifth of their body fat reserves during the crossing, which explains the high mortality rate among men.

Yet on the Col de la Traversette route, the war elephants would have fared better, losing just 4% of their reserves. This may explain why some 30 elephants are estimated to have made it through to fight in the Battle of the Trebia – the first major battle of the Second Punic War.

“The new analysis does not eliminate all ambiguity, but it does strengthen the case for the Traversette route by demonstrating that it would better accommodate the demands of moving a large army that included elephants through extremely difficult alpine terrain,” notes Berti.

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A galaxy that formed around a billion years after the Big Bang is in its death throes thanks to a powerful galactic wind that is blasting its gas into space, say astronomers at Australia’s Swinburne University of Technology. The discovery, which is based on data from the James Webb Space Telescope (JWST) and the Atacama Large Millimeter/submillimeter Array (ALMA) in Chile, could help explain why some of the universe’s earliest massive galaxies ceased to form new stars.

One of the JWST’s most surprising discoveries is that when the universe was between one and two billion years old, it already contained large numbers of massive galaxies. Astronomers think these galaxies may have acquired most of their mass in intense bursts of star formation. But at some point, that process stopped: in technical terms, the galaxies became quiescent.

“These galaxies seemed to have formed all their stars very quickly and then they suddenly died, all within the first two billion years of the universe being formed,” says Rebecca Davies, who led the new research.

The CRISTAL-02 galaxy

One possible explanation for the onset of quiescence is that when galaxies collide with each other, the resulting winds “blow away” the hydrogen fuel required for new stars to form. To investigate this hypothesis, Davies and colleagues focused on a galaxy called CRISTAL-02, which was one of 20 galaxies in the recent ALMA-CRISTAL survey of early star-forming galaxies.

“When we looked at the data, it stood out because it was the only one that showed strong evidence for a galaxy wind,” Davies explains. “We saw this as an excellent opportunity to study how winds impacted the evolution of galaxies in the early universe.”

The light from CRISTAL-02 travelled for approximately 12.7 billion years to reach us, meaning that we see it as it was one billion years after the Big Bang. Because the universe has been expanding since then, the galaxy’s spectra appear highly red-shifted. This meant the Swinburne astronomers needed the JWST’s infrared-sensing capabilities to analyse a spectral feature known as the hydrogen-alpha (Hα) line that is normally red. They also used ALMA to analyse CRISTAL-02’s C II line, which comes from ionized carbon and has a (non-redshifted) wavelength of 158 mm. Both emission lines can yield important information about the properties of early galaxies.

Living fast and dying young

From the ALMA-CRISTAL survey’s measurements of Hα luminosity, astronomers knew that CRISTAL-02 forms stars at a rate of around 260 M_☉ per year. This is about three times the average value for “main-sequence” star-forming galaxies at similar mass and redshifts.

The latest observations, however, suggest that it won’t maintain this pace for long. Davies and colleagues identified a huge plume of C II emissions that extends as far as 7 kiloparsecs (kpc) to the north-east of CRISTAL-02, making it almost as long as the galaxy itself. This is a telltale sign that gas is being driven out of the galaxy. The fact that the gas in this plume is blue-shifted by 100 km s^-1 lends further support to this explanation.

If this rapid blowout continues, Davies says that CRISTAL-02 will cease to exist in less than 50 million years. But the team’s findings may have implications beyond the fate of this single galaxy. “Our results could help to explain how some of the earliest massive quiescent galaxies in the universe behave,” she tells Physics World. “When the JWST started observing distant galaxies in 2022, it found far more evolved galaxies in the early universe than models predicted. These galaxies seemed to have formed all their stars very quickly and then suddenly died, all within the first two billion years of the universe. The galaxy we discovered seems to be following this path.”

Learning about the early universe

Davies explains that because the early universe was much more compact than it is now, collisions between galaxies were common. During such collisions, gas funnels towards the galactic centres, triggering strong bursts of star formation but also producing strong winds that eventually drive the gas away. “If many early galaxies collide and experience rapid growth, then it may not be surprising at all that we see so many dead galaxies in the early universe,” she says.

The researchers stress that the present work, which is detailed in the Monthly Notices of the Royal Astronomical Society, is based on a case study of just one galaxy. They now need to observe other early, massive galaxies caught during periods of intense growth to determine whether they, too, experience powerful winds that could rapidly expel their gas and stop them from forming stars.

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Static electricity is one of those everyday phenomena that turns out to be much more complicated than you might expect. Indeed, our guest in this episode of the Physics World Weekly podcast has devoted much of his career to understanding how objects exchange electrical charge – a process that he says scientists are mostly “clueless” about.

Based at the Institute of Science and Technology Austria, Scott Waitukaitis is in conversation with Physics World’s Margaret Harris. He explains how his early work in granular physics opened his eyes to the many unsolved problems related to static electricity. They also chat about some of Waitukaitis’s current research projects including his quest to understand the role that adsorbed molecules play in how an object is charged.

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Frost can spread not only along surfaces but also via suspended “ice bridges” that form above them. The discovery of this previously unknown frost-propagation pathway could lead to new ways of making surfaces that resist frost growth, thereby improving the performance of devices that operate in cold, humid environments.

Frost accumulation is a major problem in refrigerators, aeroplanes and heat pumps, to name just a few. On the microscale, it primarily spreads from one individual freezing water droplet to the next via two-dimensional bridges, or causeways, that temporarily form on the surface of an object. Although the wettability of the surface is known to affect the spreading process, the mechanism behind this effect was poorly understood.

Ice bridges can grow in two distinct spatial modes

To learn more, a team led by physicist Nenad Miljkovic at the University of Illinois Urbana-Champaign, US imaged the channel-forming process using high-speed high-resolution optical microscopy combined with a profilometry technique called focal plane shift imaging (FPSI). They found that frost can spread in two distinct ways. On hydrophilic surfaces, causeways form along the substrate, in line with current theoretical models. On superhydrophobic surfaces, however, the situation is quite different. Here, frost spreads via ice bridges that are suspended above the surface in three-dimensional space.

This suspended or “out-of-plane” growth mode represents a fundamentally different pathway for frost propagation, says team member Siyan Yang, the first author of a Nature Physics  paper about the work. Previous studies likely overlooked this mechanism, Yang adds, because of limitations in experimental observations.

Superhydrophobic coatings nearly double the frost propagation time

The researchers also studied the growth rate of the different bridge types. They found that suspended bridges grew slower than bridges on the surface due to the reduced thermal coupling between the bridges and the cold substrate.  This reduced coupling correspondingly reduces the vapour pressure difference between ice and water droplets (which depends on surface droplet geometry, itself controlled by wettability) and drives down ice growth. Indeed, the team found that the speed at which frost spreads fell more than 80% in this mode.

To test the practical relevance of their findings, the researchers applied superhydrophobic coatings to metre-sized structures such as the finned-tube aluminium heat exchangers commonly found in air conditioners, refrigerators and automotive systems. Condensation frosting on such systems poses a major efficiency challenge because frost has an inherently low thermal conductivity. When it accumulates on heat exchangers, it therefore severely impedes heat being exchanged with the surrounding air.

On uncoated commercial heat exchangers that are inherently hydrophilic, the team found that frost rapidly forms and spreads across the fins. “In the superhydrophobic counterparts, however, the onset of frost formation is delayed, and it propagates much more slowly,” Yang says. In the two kinds of commercial systems they tested, she adds, applying superhydrophobic coatings nearly doubled the frost propagation time.

The results suggest that designers of anti-frost surfaces could benefit from trying this new strategy, Yang says. “Rather than focusing solely on delaying initial ice nucleation, surfaces could be engineered to control the geometry of ice-bridge growth and interrupt frost spreading, thereby improving the performance and energy efficiency of a host of equipment operating in cold and humid environments,” she tells Physics World.

The team is now investigating how surface chemistry and surface structures influence suspended ice-bridge formation and frost propagation. “We are also exploring ways to translate the fundamental mechanism into scalable anti-frost coatings and heat-exchanger technologies,” Yang reveals. “Ultimately, our goal is to establish predictive design rules that connect microscale ice-bridge dynamics with real-world frost management performance.”

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The Bullet Cluster of galaxies might only have half as much dark matter than scientists thought, or perhaps even none at all, according to a new look at observations of this immense collision of galaxies from the James Webb Space Telescope (JWST).

“Our results indicate that the required amount of additional unseen mass – dark matter – is reduced,” astrophysicist Dong Zhang of the University of Bonn, who led the study, tells Physics World.

The Bullet Cluster is a central battleground for proponents of alternative models of gravity seeking to usurp dark-matter theory. The cluster itself is actually two clusters of hundreds of galaxies that have collided head-on. In 2006 the Hubble Space Telescope mapped how the Bullet Cluster’s mass was warping space and creating gravitational lensing, and from this it was possible to infer where the dark matter in the cluster was relative to the galaxies themselves and the hot, X-ray emitting gas. While the galaxies and hot gas remained in the middle, the dark matter from both colliding clusters had passed through unhindered and is now on opposite sides – exactly as dark-matter theory predicted.

In 2025 the JWST observed the Bullet Cluster and the initial analysis, led by Sangjun Cha of Yonsei University, found that while the distribution of mass in the cluster is more complex than expected, it still supports the dark-matter model.

“Those JWST observations of the Bullet Cluster have sparked a lot of interest,” says astrophysicist Richard Massey of Durham University, who was not involved in the new study.

Counting stellar remnants

Astrophysicists led by Zhang have now made their own analysis of the JWST data and arrived at a very different conclusion, as they report in Physical Review D.

Zhang’s team aimed to precisely measure the total mass of not just the stars, but also of dark stellar remnants – white dwarfs, neutron stars and black holes formed when stars die – to see if these objects could account for the extra gravity attributed to dark matter. They found that there would be enough stellar remnants to reduce the amount of dark matter required by half, at least. Furthermore, applying MOND (modified Newtonian dynamics) to the cluster potentially removes the need for dark matter entirely.

They utilized a model called the integrated galaxy-wide initial mass function (IGIMF), which is a variation on the standard IMF that describes how a collapsing molecular cloud fragments into clumps that produce stars. The standard IMF favours low-mass over high-mass stars.

However, variations in chemical compositions, stellar radiation fields and the rate at which gas cools in a given environment mean that the IMF varies from galaxy to galaxy. The IGIMF is designed to get around this by integrating over the full stellar population of a galaxy, or in this case, an entire cluster of galaxies.

“The IGIMF framework was developed independently of MOND and is motivated by observational constraints related to star formation and stellar populations,” says Zhang.

One of the quirks of the IGIMF is that it predicts that in the early universe, more massive stars formed in giant elliptical galaxies than form in galaxies today, consequently producing more stellar remnants than what the standard IMF predicts. Such giant galaxies exist in the core of clusters such as the Bullet. Since massive stars leave behind massive remnants when they go supernova, the gravity of these remnants could account for a large amount of the dark matter. This is supported, says Zhang, by the abundance of heavy elements in some galaxies that’s hard to explain without invoking an early population of very massive stars.

When the quantity of stellar remnants predicted by the IGIMF is applied to the standard model of cosmology “it does not appear sufficient to account for the strong lensing mass in the central regions of the Bullet Cluster,” says Zhang. It is only when applying MOND that things begin to align, he adds.

Questioning the mass function

However, not everyone is convinced by the choice to use the IGIMF over the standard IMF.

“It’s kind of a neat theoretical framework, in which aspects that could produce a total IMF are broken down into separate mathematical terms that can be modelled individually,” says Massey. “But it’s also kind of irrelevant for this sort of empirical analysis, since mainstream analyses already assume that the IMF varies between galaxies, and even in different regions of a galaxy.”

Traditionally, estimating the total stellar mass of a galaxy is accomplished by taking spectra or multi-band photometry and employing a technique called “stellar population synthesis” that best-fits a galaxy’s light to a particular distribution of stellar masses, Massey explains.

“However, the emitted light can be dominated by the brightest, most massive stars,” he says, meaning that the far greater number of less massive stars has to be extrapolated from a galaxy’s stellar mass function, which is derived from the IMF while factoring in the galaxy’s age.

Stellar remnants are even more difficult to detect directly, hence the dependency on the IMF or IGIMF.

“Stellar remnants cannot generally be detected in external galaxies beyond the Milky Way and its satellites,” says Kathy Romer, an astrophysicist at the University of Sussex who studies galaxy clusters. “Exceptions would be via gravitational-wave events or ultra-luminous X-ray binaries, but those are only the tip of the iceberg, so estimates of the total contribution of stellar remnants will always be an extrapolation of what we measure in the Milky Way and Magellanic Clouds.”

Like Massey, who describes IGIMF as being “less mainstream”, Romer is also sceptical about the new results, but acknowledges that “there are some strong aspects to their paper” and that “bringing fresh perspectives and challenging the orthodoxy is essential to keep science moving forward”.

Massey also highlights recent work from a team led by Gregor Rihtarŝiĉ and including Douglas Clowe of Ohio University who led the original Hubble observations of the Bullet Cluster, and who are running simulations to try and refine their maps of dark matter in the cluster.

The post Does the Bullet Cluster contain a lot less dark matter than we thought? appeared first on Physics World.

Radioactive materials have become a vital tool in our modern society, enabling the delivery of powerful medical treatments, the detection of toxic substances, and the generation of energy on a massive scale. But they also pose significant risks to human health, which means that organizations handling radioactive isotopes must have robust procedures in place to manage and monitor the dose received by their workforce and the wider public.

Dosimetry badges provide a visible and straightforward way to measure external exposure to radiation, but they are unable to determine the amount of radioactive particulates that have entered the body. Quantifying these intakes requires internal dosimetry, which typically uses measurements of urine or faecal samples – or less commonly in vivo radiological counts – to estimate the intake of specific radioisotopes. While the internal dose cannot be measured directly, monitoring data from these bioassays can be combined with biokinetic models to assess the likely impact of an individual inhaling, ingesting or being injected with a radioactive substance.

But internal dosimetry is not an exact science, and organizations with limited experience of radiation safety can struggle to translate regulatory requirements and the associated guidance into monitoring programmes that provide appropriate protection for their employees. Luckily, help is at hand. Dade Moeller & Associates, a wholly owned subsidiary of NV5, is a consultancy company specializing in radiation safety and dosimetry monitoring. Dade Moeller’s team of senior and certified health physicists can help organizations to balance worker protection with regulatory compliance.

Fit for purpose

“We encourage people to think about what they are monitoring for,” says Dr Brett Rosenberg, a certified health physicist at Dade Moeller with expertise in internal dosimetry. “The dosimetry programme must be tailored to the activity and half-life of the materials being handled, how those particular radionuclides interact with the body, and the maximum dose that an individual is likely to receive.” All of these considerations are important for prescribing a monitoring programme that does not become too onerous in costs and implementation while still providing an accurate assessment of occupational exposures.

In low-dose environments, for example, Rosenberg would advise organizations to run a confirmatory programme, in which samples from a subset of the workforce are used to check for any unexpected intake that would warrant further investigation. In contrast, routine internal dosimetry becomes a necessary requirement when there is a greater risk of workers receiving doses that exceed monitoring criteria – or even limits – set by the regulations.

Such situations are likely to arise, for example, in facilities that develop and manufacture medical radioisotopes, such as highly volatile iodine-131 for treating thyroid conditions. Radionuclides with the potential to generate higher doses are also produced throughout the fuel cycle for nuclear power generation, from extracting and refining the uranium – which creates radioactive dust that is easily inhaled – through to the management of nuclear waste.

In the US, such commercial operations are overseen by the Nuclear Regulatory Commission (NRC), which sets maximum limits both for the total radiation dose and the intake that a worker can receive. Companies must demonstrate compliance with these limits, but the NRC does not dictate the methodologies that are used for internal monitoring, or for estimating the intake from lab-based measurements. “Programme development and design is not based on regulation, it’s based on guidance,” says Rosenberg.

Flexibility leads to variability

That leaves organizations with significant flexibility in how they design their monitoring strategies, which allows programmes to be tailored to operational realities rather than forced into a rigid template. However, it also leads to variability in monitoring approaches and in the interpretation of results. Annual audits required by the NRC offer an opportunity for experts like Rosenberg not just to verify compliance, but also to identify opportunities for improvement. “I look for technical shortfalls in internal dosimetry, and check that the measures in place are effective and appropriate,” he says.

Many companies value the input they receive through these regular evaluations. Dan Sowers, for example, is the Global Radiation Protection Manager for Westinghouse, a nuclear services company that, among other things, fabricates uranium fuel and maintains the inner workings of nuclear reactors when they are not being operated. “My priority is the health of our workers,” he says. “Ultimately, we want our internal dosimetry programme to demonstrate that workplace controls are effective.”

Regular input from external advisors helps Sowers to ensure that robust procedures are in place for contamination control, and for assigning a dose to an employee when there is an intake of radioactivity. “The experts at Dade Moeller have enough real-world experience to know what’s right, which can go beyond the guidance we get from the regulators,” says Sowers. “They bring a fresh set of eyes to our operation and share best practice from other sites.”

The team at Dade Moeller also provides expert input to the US Department of Energy (DOE), which runs the national labs as well as facilities for nuclear security. Unlike the NRC, the DOE prescribes structured programmes for internal dosimetry that are tailored to the radioactive materials being handled at each site. It mandates lower dose thresholds than specified by the NRC for workers to undergo routine internal dosimetry checks, and uses a newer set of recommendations for assessing intake and estimating the dose received by different parts of the body. (However, notes Rosenberg, neither the NRC nor DOE use the latest set of recommendations, which are being adopted internationally.)

Creating consistency

Many of those recommendations come from the International Commission on Radiological Protection (ICRP), an independent body that provides guidance on dose limits and monitoring methodologies. The ICRP also develops and publishes the biokinetic models that are used by dosimetrists to translate the radiation counts from bioassays into estimates of intake and effective dose. Specific models have been developed to assess the impact of inhaling or ingesting different radioactive species, but the results are open to interpretation and depend on the version of the model being used.

To avoid these ambiguities, national regulators in Europe have combined forces to create a unified framework for internal dosimetry. Based on the outcomes from a co-ordinated research project in the early 2000s, this framework defines a standard set of methods and assumptions to ensure that different organizations calculate similar dose estimates from the same monitoring data. However, no such consistency exists in the US, where the NRC does not specify the details of the monitoring programme or the modelling methods a company should use, or between regulators in other parts of the world.

That lack of consistency can create difficulties for international companies like Westinghouse, which operates across 21 countries in different geographic regions. “Our internal dosimetry programmes are slightly different in each location,” says Sowers. “Those differences don’t affect the fundamentals of how we protect the health and safety of the worker, but the fine print of the regulations often requires us to do things slightly differently to make sure we are compliant.”

Dealing with uncertainty

To improve consistency, Rosenberg is involved in both national and international standards initiatives that aim to define best practice. However, he says, even the most carefully designed monitoring programme cannot eliminate the inherent uncertainty in estimating the effective dose from lab-based measurements of excreted samples.

“Even the most up-to-date models may not be very accurate,” says Rosenberg. “While the bioassay results are taken from a real individual, the model assigns the dose to a reference person who weighs 70 kg, excretes 135 g of faeces per day, and has both ovaries and a prostate.” As a result, the effective dose calculations based on excreted samples can carry errors of 300% when considering the anatomy and physiology of an “average worker”, and the practical limitations around counting statistics and sampling. “For practitioners, the challenge is not to remove uncertainty, but to understand and manage it,” says Rosenberg.

Given these intrinsic uncertainties, Rosenberg’s mission is to help regulators and commercial organizations to deploy the most effective methodologies for improving the standard of care. As part of these efforts, he has developed a week-long training course that aims to demystify the process of internal dosimetry for managers and regulators who need to understand the guidance from regulatory and international bodies like the ICRP.

“We do see uncertainty associated with inappropriate dosimetry practices, and to advance the field both the regulators and the practitioners need to stay current with the latest recommendations and models,” he says. “It’s easy to follow NRC regulations, but putting structured monitoring programmes in place and using the most appropriate models will help companies to produce more accurate evaluations and improve the safety of their workers.”

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The fast-charging performance of lithium-ion batteries is strongly influenced by the structure of porous electrodes and its evolution during battery operation. In such electrodes, ionic transport is governed by the electrolyte conductivity as well as by the porosity, tortuosity and thickness of the electrode. The latter parameters undergo both reversible and irreversible changes, induced by the lithiation and delithiation of graphite particles and by the formation of the solid–electrolyte interphase (SEI).

We will discuss how SEI formation alters electrode thickness, porosity and tortuosity. Particular emphasis will be placed on how these structural changes depend on the initial electrode porosity and how SEI formation can be quantitatively linked to the evolution of transport properties.

Second, we will address state-of-charge–dependent effects. Graphite particle expansion during lithiation changes the pore structure, influencing electrode porosity, thickness and pore volume. It will be shown how these changes affect ionic resistance and electrolyte transport, and how they connect to macroscopic effects such as the recently described electrolyte-motion–induced salt inhomogeneity (EMSI).

Together, these insights provide a coherent picture of how SEI formation and state-of-charge-dependent expansion alter ionic transport in porous graphite anodes, offering guidance for electrode design and improved methodologies for realistic parameter determination used in battery modelling and fast-charging optimisation.

Lennart Reuter received his PhD from the Technical University of Munich (TUM) in June 2025 under the supervision of Hubert Gasteiger and is now a postdoctoral researcher at Uppsala University. His research centres on identifying and quantifying material and electrolyte decomposition processes in lithium-ion batteries. He implemented OEMS for gas analysis in the presence of volatile commercial electrolytes and developed a novel three-electrode cell for the operando detection of parasitic side reactions. In addition, he investigated structural and transport changes in porous electrodes during operation, including the characterisation of porous transport properties by electrochemical impedance spectroscopy (EIS).

Jonas Dickmanns is a PhD candidate at the Chair of Technical Electrochemistry, supervised by Hubert Gasteiger at the Technical University of Munich (TUM), focusing on advanced lithium-ion battery cell chemistry and anode materials. He received his MSc in chemistry from TUM, where he worked on the electrochemical characterisation of graphite. He later expanded his research to other anode materials, including microscale silicon and silicon/carbon composites. His work investigates key electrode processes such as solid–electrolyte interphase (SEI) formation, structural evolution of anodes, and electrolyte interactions. The goal of his research is to enhance the performance, stability and lifetime of next-generation lithium-ion batteries.

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Artificial vision is employed in applications ranging from self-driving cars to advanced robotics. However, most “artificial eyes” do not work well in complex real-world conditions, such as sudden strong glare, dimness or uneven light levels. Such devices also rely on complex and rigid electronic circuitry to adjust their sensitivity to light and on post-algorithmic processing for accurate image recognition. A research team headed up at the University of Electronic Science and Technology of China and Penn State in the US has now developed a new adaptive photomemristor structure that does not suffer from any of these problems, allowing for machine vision that truly adapts to natural and complex light fluctuations, just like human eyes.

Sight is one of our most important senses: we acquire over 80% of the information from our environment through our eyes. Indeed, the human eye is so sensitive that it can process visual information under varied lighting levels with a photodetection dynamic range of more than 160 dB. This allows us to watch a film in a dark room or drive in the glare of oncoming headlights. Until now, however, artificial eyes have lacked this so-called dynamic self-adaptation.

Memristors for improving light adaptation

In recent years, researchers have been looking into neuromorphic devices that mimic the way biological structures work. These devices can be engineered to behave very much like neurons in the human brain, which learn by reconfiguring the strengths of the connections (synapses) between neurons. Memristors (or memory resistors) are excellent in this respect because they can bring this learning functionality to the connections in electronic circuits.

Rather than being fixed, the resistance of memristors changes depending on the current or voltage previously applied to them. This means that specific resistances can be programmed into the devices and subsequently stored. Importantly, the “remembered” value of the resistive state persists even when the power is switched off, making it a non-volatile form of electronic memory.

Photomemristors are a type of memristor that can change their resistance in response to both voltage/current and light and could therefore be used in advanced optical systems.

Reversible water absorption and desorption

In the new work, reported in Nature Communications, a team led by materials scientist Jia Zhu made a highly adaptive optoelectronic synapse from the composite material TiO₂/PEDOT:PSS. The TiO₂ absorbs light, converting it into a photocurrent that then passes through the conductive surface of the PEDOT:PSS polymer. This intrinsic photothermal effect, explains Zhu, triggers reversible water absorption and desorption on the polymer surface, which in turn impacts the device’s conductivity.

“This process allows the device to automatically suppress the photoresponse under intense bright light and amplify its sensitivity under dim weak light,” he says. “In extreme strong-light conditions, its photocurrent can even drop below the dark current level, allowing for an ultralow-sensitivity state similar to human eye pupil constriction.”

A high image recognition accuracy

Zhu tells Physics World that when integrated with artificial neural networks, the new adaptive vision system achieves a high image recognition accuracy of 91.3% in dynamically changing mixed-light scenarios, including glare, dim shadow and alternating brightness. It also eliminates the need for bulky auxiliary circuits and complex real-time computing algorithms,  reducing power consumption and hardware volume.

The new work is a first step towards making next-generation neuromorphic vision systems that could be used in practical applications. “Our adaptive photomemristor vision system can effectively resist strong glare from oncoming vehicle headlights, accurately identify pedestrians, lane lines and traffic signals in complex day–night alternating light environments, so greatly improving the safety of autonomous driving,” Zhu explains.

The technology could also be widely applied to humanoid robots, outdoor intelligent monitoring equipment, aerial reconnaissance and portable intelligent vision terminals, he adds.

Looking ahead, the researchers will now focus on optimizing the material formula of the compound studied in this work and improve its fabrication. They will also be working on complete system-level integration, including array device packaging, signal readout modules and adaptive control units, with the aim of constructing a fully functional bionic artificial eye prototype. “We will then verify whether this biomimetic dynamic regulation strategy can be extended to other oxide/polymer composite memristor systems to develop a universal design principle for high-performance light-adaptive neuromorphic devices,” says Zhu.

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When electrons are placed in a strong magnetic field and cooled to very low temperatures, they stop behaving independently and instead act as a collective fluid. This is known as a fractional quantum Hall (FQH) system. In this regime, the electrons lose their individual behaviour and act as one correlated system. The strong interactions between them produce quasiparticles called anyons. These are not real particles but effective ones that emerge from the collective behaviour, and they have unusual properties that do not occur in ordinary systems.

Anyons exhibit braiding behaviour: when they are moved around each other, the system remembers the path taken. In Abelian braiding, this only adds a simple phase, so the quantum state is effectively unchanged. In contrast, non-Abelian braiding transforms the quantum state into a different one, which can be measured and used to encode information.

To study these systems, physicists must compute measurable properties from complicated wave functions, which is computationally challenging, especially for large systems. The traditional method, Metropolis Monte Carlo, is slow and struggles with large numbers of electrons, limiting system size, accuracy, and the ability to test advanced theories.

In this work, the researchers developed a new simulation method, Hybrid Monte Carlo (HMC), for FQH wave functions. It includes global updates (updating many electrons at once) and double stereographic projection to more accurately sample particle positions, making it much faster and more efficient than the Metropolis method.

Using this improved method, they accurately computed edge properties that reveal the system’s topology, as well as high-quality braiding matrices of non-Abelian quasiholes, which are crucial because such braiding underpins topological quantum computing. Overall, this work enables fast, large-scale simulations, allowing more accurate study of exotic quantum states and their anyon behaviour, advancing both fundamental physics and topological quantum computing.

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A review of the quantum Hall effects in MgZnO/ZnO heterostructures by Joseph Falson and Masashi Kawasaki (2018)

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Physical properties and atomic arrangements in crystals by W A Wooster (1953)

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Telltale patterns of antineutrino emissions could reveal whether fusion reactors have been reconfigured to produce material for nuclear weapons, say physicists in the US. Although commercial fusion power plants are still some years away, members of the team at Virginia Tech and Princeton University argue that it is nevertheless useful to develop robust ways of monitoring their output now, to ensure the technology is not misused.

“Neutrinos cannot be shielded, their signatures cannot be spoofed and they can be detected from a distance, either onsite or offsite, allowing for nonintrusive monitoring of reactor operation,” says team member Patrick Huber, a physicist at Virginia Tech’s Center for Neutrino Physics. Better still, the team’s calculations show that existing antineutrino detectors such as Virginia Tech’s mobile MiniCHANDLER are sensitive enough to spot these signatures.

The DT process and nuclear proliferation

Most fusion technologies rely on the deuterium-tritium (DT) fusion process, which occurs when a deuterium nucleus (a proton bound to a neutron) and a tritium nucleus (one proton and two neutrons) fuse to produce helium-4, a free neutron and large amounts of energy. Because fissile materials are not directly involved in this reaction, the nuclear proliferation risk of fusion reactors is widely regarded as being much lower than that of fission power plants.

That said, if neutrons released in the DT process were combined with small amounts of material such as uranium-238 or thorium-232 in the “blanket” that surrounds the DT fuel in the fusion reactor, it would, in principle, be possible to use the reactor to produce plutonium-239 or uranium-233. Both materials are used in nuclear weapons, and a gigawatt-scale fusion reactor operating in this mode could produce tens of kilograms per week – enough for several first-generation bombs.

Checking for nuclear fingerprints

Crucially, though, this clandestine production would not necessarily go unnoticed. Whenever radioisotopes in the blanket absorb neutrons during the fusion process, they give off a distinctive pattern of antineutrinos. And according to the Princeton-Virginia Tech team’s simulations, the current generation of antineutrino detectors is already capable of distinguishing this pattern from the one produced during normal reactor operations.

In the current study, which appears in Phys. Rev. Applied, the researchers focused on the plutonium antineutrino signal. Using a Monte Carlo particle transport code called MCNP6, they modelled the output of a simplified toroidal fusion reactor with an outer radius of 6.2 m and an inner radius of 2.0 m. This reference reactor would operate at a typical power density, and Huber explains that it would produce a total of 1500 MW of power through plasma fusion via the DT reaction. The team also analysed two designs for the “blanket”: one featuring a molten salt (LiF-BeF2 or FLiBe) and one that relied on dual-coolant lead-lithium (DCLL).

Next, the two Princeton members of the team, Alexander Glaser and Robert James Goldston, defined and evaluated a reference fissile material production scenario. As part of this, they estimated both the plutonium production rate and the energy release that occurs as some of the covertly introduced nuclear material undergoes fission. Huber explains that this evaluation provided the first part of the antineutrino background signal.

Glaser and Goldston then analysed the neutron activation and antineutrino signatures driven by neutrons emanating from the fusion plasma. These provided the second part of the background. Finally, the team used these signatures to assess the detectability of covert fissile material production against the combined background from neutron activation and cosmogenic antineutrinos.

Based on these simulations, the team concluded that a detector like MiniCHANDLER could pick up on the production of a few kg of plutonium over 30 days – a result that Huber says should be applicable to any fusion power system that relies on DT fusion. Importantly, he points out that unlike some alternatives, antineutrino-based monitoring does not require inspectors to have access to reactor buildings and could allow plants to be monitored around the clock.

Practical advantages

The idea of using antineutrinos to detect illicit nuclear material production is not new. It dates back to the 1970s, and the two Princeton team members have previously worked on nuclear monitoring and verification for a variety of nuclear reactors and nuclear fuel-cycle facilities (including some in Iran). Given the rapid development of fusion energy systems, Hubner tells Physics World it was “a natural next step” to consider non-intrusive, antineutrino-based monitoring options for them, too. He adds that the group has been studying possible safeguards for fusion reactors since the early 2010s and was part of an IAEA consultancy on the topic in 2013.

As well as optimizing the design of detector systems, Huber says he and his colleagues are also interested in studying thorium as an alternative “fertile” material. “Even though the fission signature would be weaker compared with the uranium reference case analysed in this study, the results we have reported on already suggest that such an effort is well justified,” he says.

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How do we make good, well-informed decisions? This is the central question of author Helen Pearson’s new book Beyond Belief: How Evidence Shows What Really Works. It examines evidence-based decision-making and compares it with “conventional wisdom and questionable opinion”. Pearson is interested in how we can use scientific reasoning to empower decision-making using empirical evidence, rather than choices based on opinion or public sentiment.

Pearson uses human stories and historical narratives to outline “the evidence revolution”, in which academics, policy-makers and civilians have tried to embed evidence into decision-making. She tackles disciplines where evidence is seldom used, such as people management, or where its absence is surprising, like environmental conservation. Throughout Beyond Belief, Pearson asks us to understand what makes for good evidence, and how evidence can be better used in daily life.

An award-winning science journalist and editor at the journal Nature, Pearson is particularly good at establishing clear narratives based on a host of different scientific studies. She begins with the field of medicine, focusing on Iain Chalmers, one of the founders of the Cochrane Collaboration. Formed in 1993, it is considered to be a trailblazer in evaluating evidence-based healthcare. Indeed, the institution has influenced important changes to treatment, including the use of corticosteroids to save the lives of premature babies.

It seems obvious, Pearson suggests, that doctors would choose treatments based on rigorous evidence. Instead, she shows us that evidence-based medicine is a young field that only emerged in the 1970s. One particularly personal example she gives is the standard practice of shaving knee cartilage in meniscal tears – a procedure I nearly underwent in 2015 – which was shown to be no better than exercise therapy after a landmark trial in 2016. Beyond Belief offers a glimpse into how recent, and as-yet fragile, our reliance on evidence-based treatment is; as well as how much opposition it has faced from institutional inertia and scepticism.

The book is not just about medicine. It includes examples ranging from the roll-out of the pioneering Mexican social welfare scheme, PROGRESA, which helped to decrease poverty and improve health and education in the country; to the ineffective use of bat bridges over the UK’s A11 dual-carriageway. She also discusses using evidence to make management decisions, as opposed to relying on corporate wisdom or management consultancy. The examples are often surprising, underscoring Pearson’s central argument that evidence allows for better decisions, but getting people to use good evidence consistently is challenging.

Throughout the book, Pearson is engaging and often witty, while still discussing the complexities of implementing evidence-based best practice. Beyond Belief is highly readable too – even when navigating difficult concepts in meta-analyses. Pearson outlines the difficulties of teaching people how to use evidence, how to design studies well, and how studies can easily be misleading. She presents the enormous challenge of encouraging institutions to use evidence correctly, while remaining hopeful about our direction of travel.

There are places where tensions arise, one being in the chapter on policing. Pearson describes how evidence can be used in effective policing, for example, to support increasing patrols or stop-and-search in crime hot-spots. This reveals an interesting question about what the role of successful policing is – crime reduction, retributive justice or rehabilitation – and whose definition of justice that evidence is being used to support.

In these cases, the author’s arguments would have been strengthened if she had engaged more with the central premise of the book: that evidence always makes for better decisions. There are nuances that arise between evidence-based policy and harm reduction, and broader questions of trust that cause people to rebuke evidence entirely. A more serious conversation about these reservations might have deepened the argument in favour of empirical evidence, particularly in questions of social policy.

This discussion is not entirely absent. One particular strength of Beyond Belief is Pearson’s examination of COVID, drawn from her experience as a Nature editor during the pandemic. In this chapter, close to the book’s end, Pearson presents the difficulties of using evidence-based trials in acutely developing crises, in which scientists and public-health bodies have to adapt quickly to minimize harm. At a time when discussions about public health responses to COVID are so polarized, Beyond Belief provides a nuanced analysis of how we can arrive at a scientific conclusion under immense pressure.

At the heart of this book is Pearson’s passion and advocacy for a scientific approach to decision-making. She includes a call to action, empowering readers to be champions of evidence in their lives. Although only present in the short chapters towards the book’s end, her anecdotes about childcare, artificial intelligence and using your vote to support evidence through democracy, are useful reference tools. She also succeeds in her goal of starting a conversation about how we can best use evidence.

Ultimately, Beyond Belief sets out to demonstrate the ways in which evidence enters our lives and improves them. Pearson asks us to advocate for science in a world of increasing misinformation, and to challenge conventional wisdom while equipping us with the tools to do so. For that alone, her book is well worth reading.

• 2026 Princeton University Press 368pp £25 hb

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The frequency of extreme weather events can be predicted more accurately than presently possible by combining artificial intelligence (AI) with physical climate modelling, using a protocol called rare-event sampling. That’s the conclusion of a study from researchers in the US and France. The researchers used the approach to model extreme heat events such as the one currently roasting Europe, but they believe it could also be applicable to many other extreme events in climate science.

As the global climate warms, extreme weather is becomingly increasingly deadly and difficult to predict, and quantifying the risks of such events is important for climate change adaptation and mitigation. “Very often the rarest events carry the largest impacts,” says climate physicist Amaury Lancelin of France’s Laboratory of Dynamic Meteorology.

Full global climate model simulations will need to run for an infeasibly long time to produce sufficient data for an estimate of the precise frequencies of rare events. Alexander Wikner of the University of Chicago in Illinois gives the example of an event that, on average, occurs once every century: “Each year you’re going to flip a coin that has a one-in-a-hundred chance of coming up heads,” he says. “On average, once every hundred years, you’ll get one head, but you could very easily get no heads or two or three heads.” A meaningful estimation of the frequency therefore would traditionally require around a thousand years’ worth of simulation – which is not computationally feasible in a physical model.

Deep-learning algorithms, which ignore the underlying climate physics and simply train themselves using pattern recognition, require up to 10,000 times less computing power. However, the reliability of these in modelling extremely rare events is questionable. For example, there is evidence that an AI model will not predict more extreme cyclones than it has seen in its training data, “which is a quite unnerving idea if we imagine that tropical cyclones will be getting more extreme in the future and we want to use an AI model to forecast them,” Wikner explains. They also produce no insight into the physics of the events.

Rare-event sampling (RES) refers to techniques that preferentially allocate computing resources to specific rare events of interest, thereby avoiding modelling long periods of time in which none of those events occur. The problem, of course, is that one has to have some idea what kinds of conditions increase the probability of a rare event occurring in order to know which periods to model in more detail.

In the new research, scheduled for publication in Physical Review Letters, Lancelin, Wikner and colleagues developed the AI+RES framework. An AI algorithm runs climatic simulations repeatedly and selects those that it predicts are most likely to lead to the rare event. A full climate model then simulates only these. The researchers used this protocol to compare the frequency of heatwaves at mid-latitudes, using the predictions of a relatively coarse-grained direct numerical simulation called PlaSim as the ground truth.

They found that their technique produced similar results to PlaSim with up to 1000 times lower computational resources. The researchers now hope to apply the technique to predict other types of extreme events and apply it to more sophisticated models.

“The reason we used PlaSim is that it is computationally quite cheap compared to state-of-the-art climate models so that we can actually verify that our methodology works,” says Lancelin. “Otherwise there is no way to know whether we have made a garbage prediction or not without the ground truth.” Knowing that the AI+RES model reproduces the PlaSim results correctly, however, the researchers now hope to apply computationally expensive models in situations where it was previously impossible, with confidence that the results are likely correct.

Climate scientist Robin Noyelle of ETH Zurich believes the work marks a significant contribution to ideas that were already “floating out there”. He says that, although RES has been in use for nearly ten years, selecting the best candidates for full modelling has always proved challenging: “People were using things that we thought were reasonable – I did that during my PhD – so if I want to look at hot summers, then I select on temperature.”

This approach fails for short-term extreme events, however, because of the dynamic nature of the atmosphere. The AI model itself also failed to produce good accuracy when emulating the events, but it was “basically free” in terms of the computing power required, and provided a good starting point for the physical models. “This coupling between the two ideas is really new,” Noyelle says.

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