Physics Around the Clock: Adventures in the Science of Everyday Living
By Michael Banks

Why do Cheerios tend to stick together while floating in a bowl of milk? Why does a runner’s ponytail swing side to side? These might not be the most pressing questions in physics, but getting to the answers is both fun and provides insights into important scientific concepts. These are just two examples of everyday physics that Physics World news editor Michael Banks explores in his book Physics Around the Clock, which begins with the physics (and chemistry) of your morning coffee and ends with a formula for predicting the winner of those cookery competitions that are mainstays of evening television. Hamish Johnston

• 2025 The History Press
• You can hear from Michael Banks talking about his book on the Physics World Weekly podcast

 

Quantum 2.0: the Past, Present and Future of Quantum Physics
By Paul Davies

You might wonder why the world needs yet another book about quantum mechanics, but for physicists there’s no better guide than Paul Davies. Based for the last two decades at Arizona State University in the US, in Quantum 2.0 Davies tackles the basics of quantum physics – along with its mysteries, applications and philosophical implications – with great clarity and insight. The book ends with truly strange topics such as quantum Cheshire cats and delayed-choice quantum erasers – see if you prefer his descriptions to those we’ve attempted in Physics World this year. Matin Durrani

• 2025 Pelican
• You can hear from Paul Davies in the November episode of the Physics World Stories podcast

 

Can You Get Music on the Moon? the Amazing Science of Sound and Space
By Sheila Kanani, illustrated by Liz Kay

Why do dogs bark but wolves howl? How do stars “sing”? Why does thunder rumble? This delightful, fact-filled children’s book answers these questions and many more, taking readers on an adventure through sound and space. Written by planetary scientist Sheila Kanani and illustrated by Liz Kay, Can you get Music on the Moon? reveals not only how sound is produced but why it can make us feel certain things. Each of the 100 or so pages brims with charming illustrations that illuminate the many ways that sound is all around us. Michael Banks

• 2025 Puffin Books

 

A Short History of Nearly Everything 2.0
By Bill Bryson

Alongside books such as Stephen Hawking’s A Brief History of Time and Carl Sagan’s Cosmos, British-American author Bill Bryson’s A Short History of Nearly Everything is one of the bestselling popular-science books of the last 50 years. First published in 2003, the book became a fan favourite of readers across the world and across disciplines as Bryson wove together a clear and humorous narrative of our universe. Now, 22 years later, he has released an updated and revised volume – A Short History of Nearly Everything 2.0 – that covers major updates in science from the past two decades. This includes the discovery of the Higgs boson and the latest on dark-matter research. The new edition is still imbued with all the wit and wisdom of the original, making it the perfect Christmas present for scientists and anyone else curious about the world around us. Tushna Commissariat

• 2025 Doubleday

The post Breakfast physics, delving into quantum 2.0, the science of sound, an update to everything: micro reviews of recent books appeared first on Physics World.

The ability to induce superconductivity in materials that are inherently semiconducting has been a longstanding research goal. Improving the conductivity of semiconductor materials could help develop quantum technologies with a high speed and energy efficiency, including superconducting quantum bits (qubits) and cryogenic CMOS control circuitry. However, this task has proved challenging in traditional semiconductors – such as silicon or germanium – as it is difficult to maintain the optimal superconductive atomic structure.

In a new study, published in Nature Nanotechnology, researchers have used molecular beam epitaxy (MBE) to grow gallium-hyperdoped germanium films that retain their superconductivity. When asked about the motivation for this latest work, Peter Jacobson from the University of Queensland tells Physics World about his collaboration with Javad Shabani from New York University.

“I had been working on superconducting circuits when I met Javad and discovered the new materials their team was making,” he explains. “We are all trying to understand how to control materials and tune interfaces in ways that could improve quantum devices.”

Germanium: from semiconductor to superconductor

Germanium is a group IV element, so its properties bridge those of both metals and insulators. Superconductivity can be induced in germanium by manipulating its atomic structure to introduce more electrons into the atomic lattice. These extra electrons interact with the germanium lattice to create electron pairs that move without resistance, or in other words, they become superconducting.

Hyperdoping germanium (at concentrations well above the solid solubility limit) with gallium induces a superconducting state. However, this material is traditionally unstable due to the presence of structural defects, dopant clustering and poor thickness control. There have also been many questions raised as to whether these materials are intrinsically superconducting, or whether it is actually gallium clusters and unintended phases that are solely responsible for the superconductivity of gallium-doped germanium.

Considering these issues and looking for a potential new approach, Jacobson notes that X-ray absorption measurements at the Australian Synchrotron were “the first real sign” that Shabani’s team had grown something special. “The gallium signal was exceptionally clean, and early modelling showed that the data lined up almost perfectly with a purely substitutional picture,” he explains. “That was a genuine surprise. Once we confirmed and extended those results, it became clear that we could probe the mechanism of superconductivity in these films without the usual complications from disorder or spurious phases.”

Epitaxial growth improves superconductivity control

In a new approach, Jacobson, Shabani and colleagues used MBE to grow the crystals instead of relying on ion implantation techniques, allowing the germanium to by hyperdoped with gallium. Using MBE forces the gallium atoms to replace germanium atoms within the crystal lattice at levels much higher than previously seen. The process also provided better control over parasitic heating during film growth, allowing the researchers to achieve the structural precision required to understand and control the superconductivity of these germanium:gallium (Ge:Ga) materials, which were found to become superconducting at 3.5 K with a carrier concentration of 4.15 × 10²¹ holes/cm³. The critical gallium dopant threshold to achieve this was 17.9%.

Using synchrotron-based X-ray absorption, the team found that the gallium dopants were substitutionally incorporated into the germanium lattice and induced a tetragonal distortion to the unit cell. Density functional theory calculations showed that this causes a shift in the Fermi level into the valence band and flattens electronic bands. This suggests that the structural order of gallium in the germanium lattice creates a narrow band that facilitates superconductivity in germanium, and that this superconductivity arises intrinsically in the germanium, rather than being governed by defects and gallium clusters.

The researchers tested trilayer heterostructures – Ge:Ga/Si/Ge:Ga and Ge:Ga/Ge/Ge:Ga – as proof-of-principle designs for vertical Josephson junction device architectures. In the future, they hope to develop these into fully fledged Josephson junction devices.

Commenting on the team’s future plans for this research, Jacobson concludes: “I’m very keen to examine this material with low-temperature scanning tunnelling microscopy (STM) to directly measure the superconducting gap, because STM adds atomic-scale insights that complement our other measurements and will help clarify what sets hyperdoped germanium apart”.

The post Scientists realize superconductivity in traditional semiconducting material appeared first on Physics World.

“This is one of the big remaining frontiers in astronomy,” says Phil Bull, a cosmologist at the Jodrell Bank Centre for Astrophysics at the University of Manchester. “It’s quite a pivotal era of cosmic history that, it turns out, we don’t actually understand.”

Bull is referring to the vital but baffling period in the early universe – from 380,000 years to one billion years after the Big Bang – when its structure went from simple to complex. To lift the veil on this epoch, experiments around the world – from Australia to the Arctic – are racing to find a specific but elusive signal from the earliest hydrogen atoms. This signal could confirm or disprove scientists’ theories of how the universe evolved and the physics that governs it.

Hydrogen is the most abundant element in the universe. As neutral hydrogen atoms change states, they can emit or absorb photons. This spectral transition, which can be stimulated by radiation, produces an emission or absorption radio wave signal with a wavelength of 21 cm. To find out what happened during that early universe, astronomers are searching for these 21 cm photons that were emitted by primordial hydrogen atoms.

But despite more teams joining the hunt every year, no-one has yet had a confirmed detection of this radiation. So who will win the race to find this signal and how is the hunt being carried out?

A blank spot

Let’s first return to about 380,000 years after the Big Bang, when the universe had expanded and cooled to below 3000 K. At this stage, neutral atoms, including atomic hydrogen, could form. Thanks to the absence of free electrons, ordinary matter particles could decouple from light, allowing it to travel freely across the universe. This ancient radiation that permeates the sky is known as the cosmic microwave background (CMB).

But after that we don’t know much about what happened for the next few hundred million years. Meanwhile, the oldest known galaxy MoM-z14 – which existed about 280 million years after the Big Bang – was observed in April 2025 by the James Webb Space Telescope. So there is currently a gap of just under 280 million years in our observations of the early universe. “It’s one of the last blank spots,” says Anastasia Fialkov, an astrophysicist at the Institute of Astronomy of the University of Cambridge.

This “blank spot” is a bridge between the early, simple universe and today’s complex structured cosmos. During this early epoch, the universe went from being filled with a thick cloud of neutral hydrogen, to being diversely populated with stars, black holes and everything in between. It covers the end of the cosmic dark ages, the cosmic dawn, and the epoch of reionization – and is arguably one of the most exciting periods in our universe’s evolution.

During the cosmic dark ages, after the CMB flooded the universe, the only “ordinary” matter (made up of protons, neutrons and electrons) was neutral hydrogen (75% by mass) and neutral helium (25%), and there were no stellar structures to provide light. It is thought that gravity then magnified any slight fluctuations in density, causing some of this primordial gas to clump and eventually form the first stars and galaxies – a time called the cosmic dawn. Next came the epoch of reionization, when ultraviolet and X-ray emissions from those first celestial objects heated and ionized the hydrogen atoms, turning the neutral gas into a charged plasma of electrons and protons.

Stellar imprint

The 21 cm signal astronomers are searching for was produced when the spectral transition was excited by collisions in the hydrogen gas during the dark ages and then by the first photons from the first stars during the cosmic dawn. However, the intensity of the 21 cm signal can only be measured against the CMB, which acts as a steady background source of 21 cm photons.

When the hydrogen was colder than the background radiation, there were few collisions, and the atoms would have absorbed slightly more 21 cm photons from the CMB than they emitted themselves. The 21 cm signal would appear as a deficit, or absorption signal, against the CMB. But when the neutral gas was hotter than the CMB, the atoms would emit more photons than they absorbed, causing the 21 cm signal to be seen as a brighter emission against the CMB. These absorption and emission rates depend on the density and temperature of the gas, and the timing and intensity of radiation from the first cosmic sources. Essentially, the 21 cm signal became imprinted with how those early sources transformed the young universe.

One way scientists are trying to observe this imprint is to measure the average – or “global” – signal across the sky, looking at how it shifts from absorption to emission compared to the CMB. Normally, a 21 cm radio wave signal has a frequency of about 1420 MHz. But this ancient signal, according to theory, has been emitted and absorbed at different intensities throughout this cosmic “blank spot”, depending on the universe’s evolutionary processes at the time. The expanding universe has also stretched and distorted the signal as it travelled to Earth. Theories predict that it would now be in the 1 to 200 MHz frequency range – with lower frequencies corresponding to older eras – and would have a wavelength of metres rather than centimetres.

Importantly, the shape of the global 21 cm signal over time could confirm the lambda-cold dark matter (ΛCDM) model, which is the most widely accepted theory of the cosmos; or it could upend it. Many astronomers have dedicated their careers to finding this radiation, but it is challenging for a number of reasons.

Unfortunately, the signal is incredibly faint. Its brightness temperature, which is measured as the change in the CMB’s black body temperature (2.7 K), will only be in the region of 0.1 K.

There is also no single source of this emission, so, like the CMB, it permeates the universe. “If it was the only signal in the sky, we would have found it by now,” says Eloy de Lera Acedo, head of Cavendish Radio Astronomy and Cosmology at the University of Cambridge. But the universe is full of contamination, with the Milky Way being a major culprit. Scientists are searching for 0.1 K in an environment “that’s a million times brighter”, he explains.

And even before this signal reaches the radio-noisy Earth, it has to travel through the atmosphere, which further distorts and contaminates it. “It’s a very difficult measurement,” says Rigel Cappallo, a research scientist at the MIT Haystack Observatory. “It takes a really, really well calibrated instrument that you understand really well, plus really good modelling.”

Seen but not confirmed

In 2018 the Experiment to Detect the Global EoR Signature (EDGES) – a collaboration between Arizona State University and MIT Haystack Observatory – hit the headlines when it claimed to have detected the global 21 cm signal (Nature 555 67).

The EDGES instrument is a dipole antenna, which resembles a ping-pong table with a gap in the middle (see photo at top of article for the 2024 set-up). It is mounted on a large metal groundsheet, which is about 30 × 30 m. Its ground-breaking observation was made at a remote site in western Australia, far from radio frequency interference.

But in the intervening seven years, no-one else has been able to replicate the EDGES results.

The spectrum dip that EDGES detected was very different from what theorists had expected. “There is a whole family of models that are predicted by the different cosmological scenarios,” explains Ravi Subrahmanyan, a research scientist at Australia’s national science agency CSIRO. “When we take measurements, we compare them with the models, so that we can rule those models in or out.”

In general, the current models predict a very specific envelope of signal possibilities (see figure 1). First, they anticipate an absorption dip in brightness temperature of around 0.1 to 0.2 K, caused by the temperature difference between the cold hydrogen gas (in an expanding universe) and the warmer CMB. Then, a speedy rise and photon emission is predicted as the gas starts to warm when the first stars form, and the signal should spike dramatically when the first X-ray binary stars fire up and heat up the surrounding gas. The signal is then expected to fade as the epoch of reionization begins, because ionized particles cannot undergo the spectral transition. With models, scientists theorize when this happened, how many stars there were, and how the cosmos unfurled.

“It’s just one line, but it packs in so many physical phenomena,” says Fialkov, referring to the shape of the 21 cm signal’s brightness temperature over time. The timing of the dip, its gradient and magnitude all represent different milestones in cosmic history, which affect how it evolved.

The EDGES team, however, reported a dip of more than double the predicted size, at about 78 MHz (see figure 2). While the frequency was consistent with predictions, the very wide and deep dip of the signal took the community by surprise.

“It would be a revolution in physics, because that signal will call for very, very exotic physics to explain it,” says de Lera Acedo. “Of course, the first thing we need to do is to make sure that that is actually the signal.”

A spanner in the works

The EDGES claim has galvanized the cosmology community. “It set a cat among the pigeons,” says Bull. “People realized that, actually, there’s some very exciting science to be done here.” Some groups are trying to replicate the EDGES observation, while others are trying new approaches to detect the signal that the models promise.

The Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) – a collaboration between the University of Cambridge and Stellenbosch University in South Africa – focuses on the 50–170 MHz frequency range. Sitting on the dry and empty plains of South Africa’s Northern Cape, it is targeting the EDGES observation (Nature Astronomy 6 984).

In this radio-quiet environment, REACH has set up two antennas: one looks like EDGES’ dipole ping-pong table, while the other is a spiral cone. They sit on top of a giant metallic mesh – the ground plate – in the shape of a many-pointed star, which aims to minimize reflections from the ground.

Hunting for this signal “requires precision cosmology and engineering”, says de Lera Acedo, the principal investigator on REACH. Reflections from the ground or mesh, calibration errors, and signals from the soil, are the kryptonite of cosmic dawn measurements. “You need to reduce your systemic noise, do better analysis, better calibration, better cleaning [to remove other sources from observations],” he says.

Desert, water, snow

Another radio telescope, dubbed the Shaped Antenna measurement of the background Radio Spectrum (SARAS) – which was established in the late 2000s by the Raman Research Institute (RRI) in Bengaluru, India – has undergone a number of transformations to reduce noise and limit other sources of radiation. Over time, it has morphed from a dipole on the ground to a metallic cone floating on a raft. It is looking at 40 to 200 MHz (Exp. Astron. 51 193).

After the EDGES claim, SARAS pivoted its attention to verifying the detection, explains Saurabh Singh, a research scientist at the RRI. “Initially, we were not able to get down to the required sensitivity to be able to say anything about their detection,” he explains. “That’s why we started floating our radiometer on water.” Buoying the experiment reduces ground contamination and creates a more predictable surface to include in calculations.

Using data from their floating radiometer, in 2022 Singh and colleagues disfavoured EDGES’ claim (Nature Astronomy 6 607), but for many groups the detection still remains a target for observations.

While SARAS has yet to detect a cosmic-dawn signal of its own, Singh says that non-detection is also an important element of finding the global 21 cm signal. “Non-detection gives us an opportunity to rule out a lot of these models, and that has helped us to reject a lot of properties of these stars and galaxies,” he says.

Raul Monsalve Jara – a cosmologist at the University of California, Berkeley – has been part of the EDGES collaboration since 2012, but decided to also explore other ways to detect the signal. “My view is that we need several experiments doing different things and taking different approaches,” he says.

The Mapper of the IGM Spin Temperature (MIST) experiment, of which Monsalve is co-principal investigator, is a collaboration between Chilean, Canadian, Australian and American researchers. These instruments are looking at 25 to 105 MHz (MNRAS 530 4125). “Our approach was to simplify the instrument, get rid of the metal ground plate, and to take small, portable instruments to remote locations,” he explains. These locations have to fulfil very specific requirements – everything around the instrument, from mountains to the soil, can impact the instrument’s performance. “If the soil itself is irregular, that will be very difficult to characterize and its impact will be difficult to remove [from observations],” Monsalve says.

So far, the MIST instrument, which is also a dipole ping-pong table, has visited a desert in California, another in Nevada, and even the Arctic. Each time, the researchers spend a few weeks at the site collecting data, and it is portable and easy to set up, Monsalve explains. The team is planning more observations in Chile. “If you suspect that your environment could be doing something to your measurements, then you need to be able to move around,” continues Monsalve. “And we are contributing to the field by doing that.”

Aaron Parsons, also from the University of California, Berkeley, decided that the best way to detect this elusive signal would be to try and eliminate the ground entirely – by suspending a rotating antenna over a giant canyon with 100 m empty space in every direction.

His Electromagnetically Isolated Global Signal Estimation Platform (EIGSEP) includes an antenna hanging four storeys above the ground, attached to Kevlar cable strung across a canyon in Utah. It’s observing at 50 to 250 MHz. “It continuously rotates around and twists every which way,” Parsons explains. Hopefully, that will allow them to calibrate the instrument very accurately. Two antennas on the ground cross-correlate observations. EIGSEP began making observations last year.

More experiments are expected to come online in the next year. The Remote HI eNvironment Observer (RHINO), an initiative of the University of Manchester, will have a horn-shaped receiver made of a metal mesh that is usually used to construct skyscrapers. Horn shapes are particularly good for calibration, allowing for very precise measurements. The most famous horn-shaped antenna is Bell Laboratories’ Holmdel Horn Antenna in the US, with which two scientists accidentally discovered the CMB in 1965.

Initially, RHINO will be based at Jodrell Bank Observatory in the UK, but like other experiments, it could travel to other remote locations to hunt for the 21 cm signal.

Similarly, Subrahmanyan – who established the SARAS experiment in India and is now with CSIRO in Australia – is working to design a new radiometer from scratch. The instrument, which will focus on 40–160 MHz, is called Global Imprints from Nascent Atoms to Now (GINAN). He says that it will feature a recently patented self-calibrating antenna. “It gives a much more authentic measurement of the sky signal as measured by the antenna,” he explains.

In the meanwhile, the EDGES collaboration has not been idle. MIT Haystack Observatory’s Cappallo project manages EDGES, which is currently in its third iteration. It is still the size of a desk, but its top now looks like a box, with closed sides and its electronics tucked inside, and an even larger metal ground plate. The team has now made observations from islands in the Canadian archipelago and in Alaska’s Aleutian island chain (see photo at top of article).

“The 2018 EDGES result is not going to be accepted by the community until somebody completely independently verifies it,” Cappallo explains. “But just for our own sanity and also to try to improve on what we can do, we want to see it from as many places as possible and as many conditions as possible.” The EDGES team has replicated its results using the same data analysis pipeline, but no-one else has been able to reproduce the unusual signal.

All the astronomers interviewed welcomed the introduction of new experiments. “I think it’s good to have a rich field of people trying to do this experiment because nobody is going to trust any one measurement,” says Parsons. “We need to build consensus here.”

Taking off

Some astronomers have decided to avoid the struggles of trying to detect the global 21 cm signal from Earth – instead, they have their sights set on the Moon. Earth’s atmosphere is one of the reasons why the 21 cm signal is so difficult to measure. The ionosphere, a charged region of the atmosphere, distorts and contaminates this incredibly faint signal. On the far side of the Moon, any antenna would also be shielded from the cacophony of radio-frequency interference from Earth.

“This is why some experiments are going to the Moon,” says Parsons, adding that he is involved in NASA’s LuSEE-Night experiment. LuSEE-Night, or the Lunar Surface Electromagnetics Experiment, aims to land a low-frequency experiment on the Moon next year.

In July, at the National Astronomical Meeting in Durham, the University of Cambridge’s de Lera Acedo presented a proposal to put a miniature radiometer into lunar orbit. Dubbed “Cosmocube”, it will be a nanosatellite that will orbit the Moon searching for this 21 cm signal.

“It is just in the making,” says de Lera Acedo, adding that it will not be in operation for at least a decade. “But it is the next step.”

In the meanwhile, groups here on Earth are in a race to detect this elusive signal. The instruments are getting more sensitive, the modelling is improving, and the unknowns are reducing. “If we do the experiments right, we will find the signal,” Monsalve believes. The big question is who, of the many groups with their hat in the ring, is doing the experiment “right”.

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Measuring blood flow to the brain is essential for diagnosing and developing treatments for neurological disorders such as stroke, vascular dementia or traumatic brain injury. Performing this measurement non-invasively is challenging, however, and achieved predominantly using costly MRI and nuclear medicine imaging techniques.

Emerging as an alternative, modalities based on optical transcranial measurement are cost-effective and easy to use. In particular, speckle contrast optical spectroscopy (SCOS) – an offshoot of laser speckle contrast imaging, which uses laser light speckles to visualize blood vessels – can measure cerebral blood flow (CBF) with high temporal resolution, typically above 30 Hz, and cerebral blood volume (CBV) through optical signal attenuation.

Researchers at the California Institute of Technology (Caltech) and the Keck School of Medicine’s USC Neurorestoration Center have designed a lightweight SCOS system that accurately measures blood flow to the brain, distinguishing it from blood flow to the scalp. Co-senior author Charles Liu of the Keck School of Medicine and team describe the system and their initial experimentation with it in APL Bioengineering.

The SCOS system consists of a 3D-printed head mount designed for secure placement over the temple region. It holds a single 830 nm laser illumination fibre and seven detector fibres positioned at seven different source-to-detector (S–D) distances (between 0.6 and 2.6 cm) to simultaneously capture blood flow dynamics across layers of the scalp, skull and brain. Fibres with shorter S–D distances acquire shallower optical data from the scalp, while those with greater distances obtain deeper and broader data. The seven channels are synchronized to exhibit identical oscillation frequencies corresponding to the heart rate and cardiac cycle.

When the SCOS system directs the laser light onto a sample, multiple random scattering events occur before the light exits the sample, creating speckles. These speckles, which materialize on rapid timescales, are the result of interference of light travelling along different trajectories. Movement within the sample (of red blood cells, for instance) causes dynamic changes in the speckle field. These changes are captured by a multi-million-pixel camera with a frame rate above 30 frames/s and quantified by calculating the speckle contrast value for each image.

Human testing

The researchers used the SCOS system to perform CBF and CBV measurements in 20 healthy volunteers. To isolate and obtain surface blood dynamics from brain signals, the researchers gently pressed on the superficial temporal artery (a terminal branch of the external carotid artery that supplies blood to the face and scalp) to block blood flow to the scalp.

In tests on the volunteers, when temporal artery blood flow was occluded for 8 s, scalp-sensitive channels exhibited significant decreases in blood flow while brain-sensitive channels showed minimal change, enabling signals from the internal carotid artery that supplies blood to the brain to be clearly distinguished. Additionally, the team found that positioning the detector 2.3 cm or more away from the source allowed for optimal brain blood flow measurement while minimizing interference from the scalp.

“Combined with the simultaneous measurements at seven S–D separations, this approach enables the first quantitative experimental assessment of how scalp and brain signal contributions vary with depth in SCOS-based CBF measurements and, more broadly, in optical measurements,” they write. “This work also provides crucial insights into the optimal device S–D distance configuration for preferentially probing brain signal over scalp signal, with a practical and subject-friendly alternative for evaluating depth sensitivity, and complements more advanced, hardware-intensive strategies such as time-domain gating.”

The researchers are now working to improve the signal-to-noise ratio of the system. They plan to introduce a compact, portable laser and develop a custom-designed extended camera that spans over 3 cm in one dimension, enabling simultaneous and continuous measurement of blood dynamics across S–D distances from 0.5 to 3.5 cm. These design advancements will enhance spatial resolution and enable deeper brain measurements.

“This crucial step will help transition the system into a compact, wearable form suitable for clinical use,” comments Liu. “Importantly, the measurements described in this publication were achieved in human subjects in a very similar manner to how the final device will be used, greatly reducing barriers to clinical application.”

“I believe this study will advance the engineering of SCOS systems and bring us closer to a wearable, clinically practical device for monitoring brain blood flow,” adds co-author Simon Mahler, now at Stevens Institute of Technology. “I am particularly excited about the next stage of this project: developing a wearable SCOS system that can simultaneously measure both scalp and brain blood flow, which will unlock many fascinating new experiments.”

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Significant progress towards answering one of the Clay Mathematics Institute’s seven Millennium Prize Problems has been achieved using deep learning. The challenge is to establish whether or not the Navier-Stokes equation of fluid dynamics develops singularities. The work was done by researchers in the US and UK – including some at Google Deepmind. Some team members had already shown that simplified versions of the equation could develop stable singularities, which reliably form. In the new work, the researchers found unstable singularities, which form only under very specific conditions.

The Navier–Stokes partial differential equation was developed in the early 19th century by Claude-Louis Navier and George Stokes. It has proved its worth for modelling incompressible fluids in scenarios including water flow in pipes; airflow around aeroplanes; blood moving in veins; and magnetohydrodynamics in plasmas.

No-one has yet proved, however, whether smooth, non-singular solutions to the equation always exist in three dimensions. “In the real world, there is no singularity…there is no energy going to infinity,” says fluid dynamics expert Pedram Hassanzadeh of the University of Chicago. “So if you have an equation that has a singularity, it tells you that there is some physics that is missing.” In 2000, the Clay Mathematics Institute in Denver, Colorado listed this proof as one of seven key unsolved problems in mathematics, offering a reward of $1,000,000 for an answer.

Computational approaches

Researchers have traditionally tackled the problem analytically, but in recent decades high-level computational simulations have been used to assist in the search. In a 2023 paper, mathematician Tristan Buckmaster of New York University and colleagues used a special type of machine learning algorithm called a physics-informed neural network to address the question.

“The main difference is…you represent [the solution] in a highly non-linear way in terms of a neural network,” explains Buckmaster. This allows it to occupy a lower-dimensional space with fewer free parameters, and therefore to be optimized more efficiently. Using this approach, the researchers successfully obtained the first stable singularity in the Euler equation. This is an analogy to the Navier-Stokes equation that does not include viscosity.

A stable singularity will still occur if the initial conditions of the fluid are changed slightly – although the time taken for them to form may be altered. An unstable singularity, however, may never occur if the initial conditions are perturbed even infinitesimally. Some researchers have hypothesized that any singularities in the Navier-Stokes equation must be unstable, but finding unstable singularities in a computer model is extraordinarily difficult.

“Before our result there hadn’t been an unstable singularity for an incompressible fluid equation found numerically,” says geophysicist Ching-Yao Lai of California’s Stanford University.

Physics-informed neural network

In the new work the authors of the original paper and others teamed up with researchers at Google Deepmind to search for unstable singularities in a bounded 3D version of the Euler equation using a physics-informed neural network. “Unlike conventional neural networks that learn from vast datasets, we trained our models to match equations that model the laws of physics,” writes Yongji Wang of New York University and Stanford on Deepmind’s blog. “The network’s output is constantly checked against what the physical equations expect, and it learns by minimizing its ‘residual’, the amount by which its solution fails to satisfy the equations.”

After an exhaustive search at a precision that is orders of magnitude higher than a normal deep learning protocol, the researchers discovered new families of singularities in the 3D Euler equation. They also found singularities in the related incompressible porous media equation used to model fluid flows in soil or rock; and in the Boussinesq equation that models atmospheric flows.

The researchers also gleaned insights into the strength of the singularities. This could be important as stronger singularities might be less readily smoothed out by viscosity when moving from the Euler equation to the Navier-Stokes equation. The researchers are now seeking to model more open systems to study the problem in a more realistic space.

Hassanzadeh, who was not involved in the work, believes that it is significant – although the results are not unexpected. “If the Euler equation tells you that ‘Hey, there is a singularity,’ it just tells you that there is physics that is missing and that physics becomes very important around that singularity,” he explains. “In the case of Euler we know that you get the singularity because, at the very smallest scales, the effects of viscosity become important…Finding a singularity in the Euler equation is a big achievement, but it doesn’t answer the big question of whether Navier-Stokes is a representation of the real world, because for us Navier-Stokes represents everything.”

He says the extension to studying the full Navier-Stokes equation will be challenging but that “they are working with the best AI people in the world at Deepmind,” and concludes “I’m sure it’s something they’re thinking about”.

The work is available on the arXiv pre-print server.

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NASA’s Goddard Space Flight Center (GSFC) looks set to lose a big proportion of its budget as a two-decade reorganization plan for the centre is being accelerated. The move, which is set to be complete by March, has left the Goddard campus with empty buildings and disillusioned employees. Some staff even fear that the actions during the 43-day US government shutdown, which ended on 12 November, could see the end of much of the centre’s activities.

Based in Greenbelt, Maryland, the GSFC has almost 10 000 scientists and engineers, about 7000 of whom are directly employed by NASA contractors. Responsible for many of NASA’s most important uncrewed missions, telescopes, and probes, the centre is currently working on the Nancy Grace Roman Space Telescope, which is scheduled to launch in 2027, as well as the Dragonfly mission that is due to head for Saturn’s largest moon Titan in 2028.

The ability to meet those schedules has now been put in doubt by the Trump administration’s proposed budget for financial year 2026, which started in September. It calls for NASA to receive almost $19bn – far less than the $25bn it has received for the past two years. If passed, Goddard would lose more than 42% of its staff.

Congress, which passes the final budget, is not planning to cut NASA so deeply as it prepares its 2026 budget proposal. But on 24 September, Goddard managers began what they told employees was “a series of moves…that will reduce our footprint into fewer buildings”. The shift is intended to “bring down overall operating costs while maintaining the critical facilities we need for our core capabilities of the future”.

While this is part of a 20-year “master plan” for the GSFC that NASA’s leadership approved in 2019, the management’s memo stated that “all planned moves will take place over the next several months and be completed by March 2026″. A report in September by Democratic members of the Senate Committee on Commerce, Science, and Transportation, which is responsible for NASA, asserts that the cuts are “in clear violation of the [US] constitution [without] regard for the impacts on NASA’s science missions and workforce”.

On 3 November, the Goddard Engineers, Scientists and Technicians Association, a union representing NASA workers, reported that the GSFC had already closed over a third of its buildings, including some 100 labs. This had been done, it says, “with extreme haste and with no transparent strategy or benefit to NASA or the nation”. The union adds that the “closures are being justified as cost-saving but no details are being provided and any short-term savings are unlikely to offset a full account of moving costs and the reduced ability to complete NASA missions”.

Accounting for the damage

Zoe Lofgren, the lead Democrat on the House of Representatives Science Committee, has demanded of Sean Duffy, NASA’s acting administrator, that the agency “must now halt” any laboratory, facility and building closure and relocation activities at Goddard. In a  letter to Duffy dated 10 November, she also calls for the “relocation, disposal, excessing, or repurposing of any specialized equipment or mission-related activities, hardware and systems” to also end immediately.

Lofgren now wants NASA to carry out a “full accounting of the damage inflicted on Goddard thus far” by 18 November. Owing to the government shutdown, no GSFC or NASA official was available to respond to Physics World’s requests for a response.

Meanwhile, the Trump administration has renominated billionaire entrepreneur Jared Isaacman as NASA’s administrator. Trump had originally nominated Isaacman, who had flown on a private SpaceX mission and carried out spacewalk, on the recommendation of SpaceX founder Elon Musk. But the administration withdrew the nomination in May following concerns among some Republicans that Isaacman had funded the Democrat party.

The post NASA’s Goddard Space Flight Center hit by significant downsizing appeared first on Physics World.

Games played under the laws of quantum mechanics dissipate less energy than their classical equivalents. This is the finding of researchers at Singapore’s Nanyang Technological University (NTU), who worked with colleagues in the UK, Austria and the US to apply the mathematics of game theory to quantum information. The researchers also found that for more complex game strategies, the quantum-classical energy difference can increase without bound, raising the possibility of a “quantum advantage” in energy dissipation.

Game theory is the field of mathematics that aims to formally understand the payoff or gains that a person or other entity (usually called an agent) will get from following a certain strategy. Concepts from game theory are often applied to studies of quantum information, especially when trying to understand whether agents who can use the laws of quantum physics can achieve a better payoff in the game.

In the latest work, which is published in Physical Review Letters, Jayne Thompson, Mile Gu and colleagues approached the problem from a different direction. Rather than focusing on differences in payoffs, they asked how much energy must be dissipated to achieve identical payoffs for games played under the laws of classical versus quantum physics. In doing so, they were guided by Landauer’s principle, an important concept in thermodynamics and information theory that states that there is a minimum energy cost to erasing a piece of information.

This Landauer minimum is known to hold for both classical and quantum systems. However, in practice systems will spend more than the minimum energy erasing memory to make space for new information, and this energy will be dissipated as heat. What the NTU team showed is that this extra heat dissipation can be reduced in the quantum system compared to the classical one.

Planning for future contingencies

To understand why, consider that when a classical agent creates a strategy, it must plan for all possible future contingencies. This means it stores possibilities that never occur, wasting resources. Thompson explains this with a simple analogy. Suppose you are packing to go on a day out. Because you are not sure what the weather is going to be, you must pack items to cover all possible weather outcomes. If it’s sunny, you’d like sunglasses. If it rains, you’ll need your umbrella. But if you only end up using one of these items, you’ll have wasted space in your bag.

“It turns out that the same principle applies to information,” explains Thompson. “Depending on future outcomes, some stored information may turn out to be unnecessary – yet an agent must still maintain it to stay ready for any contingency.”

For a classical system, this can be a very wasteful process. Quantum systems, however, can use superposition to store past information more efficiently. When systems in a quantum superposition are measured, they probabilistically reveal an outcome associated with only one of the states in the superposition. Hence, while superposition can be used to store both pasts, upon measurement all excess information is automatically erased “almost as if they had never stored this information at all,” Thompson explains.

The upshot is that because information erasure has close ties to energy dissipation, this gives quantum systems an energetic advantage. “This is a fantastic result focusing on the physical aspect that many other approaches neglect,” says Vlatko Vedral, a physicist at the University of Oxford, UK who was not involved in the research.

Implications of the research

Gu and Thompson say their result could have implications for the large language models (LLMs) behind popular AI tools such as ChatGPT, as it suggests there might be theoretical advantages, from an energy consumption point of view, in using quantum computers to run them.

Another, more foundational question they hope to understand regarding LLMs is the inherent asymmetry in their behaviour. “It is likely a lot more difficult for an LLM to write a book from back cover to front cover, as opposed to in the more conventional temporal order,” Thompson notes. When considered from an information-theoretic point of view, the two tasks are equivalent, making this asymmetry somewhat surprising.

In Thompson and Gu’s view, taking waste into consideration could shed light on this asymmetry. “It is likely we have to waste more information to go in one direction over the other,” Thompson says, “and we have some tools here which could be used to analyse this”.

For Vedral, the result also has philosophical implications. If quantum agents are more optimal, he says, it is “surely is telling us that the most coherent picture of the universe is the one where the agents are also quantum and not just the underlying processes that they observe”.

• This article was amended on 19 November 2025 to correct a reference to the minimum energy cost of erasing information. It is the Landauer minimum, not the Landau minimum.

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When you look back at the early days of computing, some familiar names pop up, including John von Neumann, Nicholas Metropolis and Richard Feynman. But they were not lonely pioneers – they were part of a much larger group, using mechanical and then electronic computers to do calculations that had never been possible before.

These people, many of whom were women, were the first scientific programmers and computational scientists. Skilled in the complicated operation of early computing devices, they often had degrees in maths or science, and were an integral part of research efforts. And yet, their fundamental contributions are mostly forgotten.

This was in part because of their gender – it was an age when sexism was rife, and it was standard for women to be fired from their job after getting married. However, there is another important factor that is often overlooked, even in today’s scientific community – people in technical roles are often underappreciated and underacknowledged, even though they are the ones who make research possible.

Human and mechanical computers

Originally, a “computer” was a human being who did calculations by hand or with the help of a mechanical calculator. It is thought that the world’s first computational lab was set up in 1937 at Columbia University. But it wasn’t until the Second World War that the demand for computation really exploded; with the need for artillery calculations, new technologies and code breaking.

In the US, the development of the atomic bomb during the Manhattan Project (established in 1943) required huge computational efforts, so it wasn’t long before the New Mexico site had a hand-computing group. Called the T-5 group of the Theoretical Division, it initially consisted of about 20 people. Most were women, including the spouses of other scientific staff. Among them was Mary Frankel, a mathematician married to physicist Stan Frankel; mathematician Augusta “Mici” Teller who was married to Edward Teller, the “father of the hydrogen bomb”; and Jean Bacher, the wife of physicist Robert Bacher.

As the war continued, the T-5 group expanded to include civilian recruits from the nearby towns and members of the Women’s Army Corps. Its staff worked around the clock, using printed mathematical tables and desk calculators in four-hour shifts – but that was not enough to keep up with the computational needs for bomb development. In the early spring of 1944, IBM punch-card machines were brought in to supplement the human power. They became so effective that the machines were soon being used for all large calculations, 24 hours a day, in three shifts.

The computational group continued to grow, and among the new recruits were Naomi Livesay and Eleonor Ewing. Livesay held an advanced degree in mathematics and had done a course in operating and programming IBM electric calculating machines, making her an ideal candidate for the T-5 division. She in turn recruited Ewing, a fellow mathematician who was a former colleague. The two young women supervised the running of the IBM machines around the clock.

The frantic pace of the T-5 group continued until the end of the war in September 1945. The development of the atomic bomb required an immense computational effort, which was made possible through hand and punch-card calculations.

Electronic computers

Shortly after the war ended, the first fully electronic, general-purpose computer – the Electronic Numerical Integrator and Computer (ENIAC) – became operational at the University of Pennsylvania, following two years of development. The project had been led by physicist John Mauchly and electrical engineer J Presper Eckert. The machine was operated and coded by six women – mathematicians Betty Jean Jennings (later Bartik); Kathleen, or Kay, McNulty (later Mauchly, then Antonelli); Frances Bilas (Spence); Marlyn Wescoff (Meltzer) and Ruth Lichterman (Teitelbaum); as well as Betty Snyder (Holberton) who had studied journalism.

Polymath John von Neumann also got involved when looking for more computing power for projects at the new Los Alamos Laboratory, established in New Mexico in 1947. In fact, although originally designed to solve ballistic trajectory problems, the first problem to be run on the ENIAC was “the Los Alamos problem” – a thermonuclear feasibility calculation for Teller’s group studying the H-bomb.

Like in the Manhattan Project, several husband-and-wife teams worked on the ENIAC, the most famous being von Neumann and his wife Klara Dán, and mathematicians Adele and Herman Goldstine. Dán von Neumann in particular worked closely with Nicholas Metropolis, who alongside mathematician Stanislaw Ulam had coined the term Monte Carlo to describe numerical methods based on random sampling. Indeed, between 1948 and 1949 Dán von Neumann and Metropolis ran the first series of Monte Carlo simulations on an electronic computer.

Work began on a new machine at Los Alamos in 1948 – the Mathematical Analyzer Numerical Integrator and Automatic Computer (MANIAC) – which ran its first large-scale hydrodynamic calculation in March 1952. Many of its users were physicists, and its operators and coders included mathematicians Mary Tsingou (later Tsingou-Menzel), Marjorie Jones (Devaney) and Elaine Felix (Alei); plus Verna Ellingson (later Gardiner) and Lois Cook (Leurgans).

Early algorithms

The Los Alamos scientists tried all sorts of problems on the MANIAC, including a chess-playing program – the first documented case of a machine defeating a human at the game. However, two of these projects stand out because they had profound implications on computational science.

In 1953 the Tellers, together with Metropolis and physicists Arianna and Marshall Rosenbluth, published the seminal article “Equation of state calculations by fast computing machines” (J. Chem. Phys. 21 1087). The work introduced the ideas behind the “Metropolis (later renamed Metropolis–Hastings) algorithm”, which is a Monte Carlo method that is based on the concept of “importance sampling”. (While Metropolis was involved in the development of Monte Carlo methods, it appears that he did not contribute directly to the article, but provided access to the MANIAC nightshift.) This is the progenitor of the Markov Chain Monte Carlo methods, which are widely used today throughout science and engineering.

Marshall later recalled how the research came about when he and Arianna had proposed using the MANIAC to study how solids melt (AIP Conf. Proc. 690 22).

Edward Teller meanwhile had the idea of using statistical mechanics and taking ensemble averages instead of following detailed kinematics for each individual disk, and Mici helped with programming during the initial stages. However, the Rosenbluths did most of the work, with Arianna translating and programming the concepts into an algorithm.

The 1953 article is remarkable, not only because it led to the Metropolis algorithm, but also as one of the earliest examples of using a digital computer to simulate a physical system. The main innovation of this work was in developing “importance sampling”. Instead of sampling from random configurations, it samples with a bias toward physically important configurations which contribute more towards the integral.

Furthermore, the article also introduced another computational trick, known as “periodic boundary conditions” (PBCs): a set of conditions which are often used to approximate an infinitely large system by using a small part known as a “unit cell”. Both importance sampling and PBCs went on to become workhorse methods in computational physics.

In the summer of 1953, physicist Enrico Fermi, Ulam, Tsingou and physicist John Pasta also made a significant breakthrough using the MANIAC. They ran a “numerical experiment” as part of a series meant to illustrate possible uses of electronic computers in studying various physical phenomena.

The team modelled a 1D chain of oscillators with a small nonlinearity to see if it would behave as hypothesized, reaching an equilibrium with the energy redistributed equally across the modes (doi.org/10.2172/4376203). However, their work showed that this was not guaranteed for small perturbations – a non-trivial and non-intuitive observation that would not have been apparent without the simulations. It is the first example of a physics discovery made not by theoretical or experimental means, but through a computational approach. It would later lead to the discovery of solitons and integrable models, the development of chaos theory, and a deeper understanding of ergodic limits.

Although the paper says the work was done by all four scientists, Tsingou’s role was forgotten, and the results became known as the Fermi–Pasta–Ulam problem. It was not until 2008, when French physicist Thierry Dauxois advocated for giving her credit in a Physics Today article, that Tsingou’s contribution was properly acknowledged. Today the finding is called the Fermi–Pasta–Ulam–Tsingou problem.

The year 1953 also saw IBM’s first commercial, fully electronic computer – an IBM 701 – arrive at Los Alamos. Soon the theoretical division had two of these machines, which, alongside the MANIAC, gave the scientists unprecedented computing power. Among those to take advantage of the new devices were Martha Evans (whom very little is known about) and theoretical physicist Francis Harlow, who began to tackle the largely unexplored subject of computational fluid dynamics.

The idea was to use a mesh of cells through which the fluid, represented as particles, would move. This computational method made it possible to solve complex hydrodynamics problems (involving large distortions and compressions of the fluid) in 2D and 3D. Indeed, the method proved so effective that it became a standard tool in plasma physics where it has been applied to every conceivable topic from astrophysical plasmas to fusion energy.

The resulting internal Los Alamos report – The Particle-in-cell Method for Hydrodynamic Calculations, published in 1955 – showed Evans as first author and acknowledged eight people (including Evans) for the machine calculations. However, while Harlow is remembered as one of the pioneers of computational fluid dynamics, Evans was forgotten.

A clear-cut division of labour?

In an age where women had very limited access to the frontlines of research, the computational war effort brought many female researchers and technical staff in. As their contributions come more into the light, it becomes clearer that their role was not a simple clerical one.

There is a view that the coders’ work was “the vital link between the physicist’s concepts (about which the coders more often than not didn’t have a clue) and their translation into a set of instructions that the computer was able to perform, in a language about which, more often than not, the physicists didn’t have a clue either”, as physicists Giovanni Battimelli and Giovanni Ciccotti wrote in 2018 (Eur. Phys. J. H 43 303). But the examples we have seen show that some of the coders had a solid grasp of the physics, and some of the physicists had a good understanding of the machine operation. Rather than a skilled–non-skilled/men–women separation, the division of labour was blurred. Indeed, it was more of an effective collaboration between physicists, mathematicians and engineers.

Even in the early days of the T-5 division before electronic computers existed, Livesay and Ewing, for example, attended maths lectures from von Neumann, and introduced him to punch-card operations. As has been documented in books including Their Day in the Sun by Ruth Howes and Caroline Herzenberg, they also took part in the weekly colloquia held by J Robert Oppenheimer and other project leaders. This shows they should not be dismissed as mere human calculators and machine operators who supposedly “didn’t have a clue” about physics.

Verna Ellingson (Gardiner) is another forgotten coder who worked at Los Alamos. While little information about her can be found, she appears as the last author on a 1955 paper (Science 122 465) written with Metropolis and physicist Joseph Hoffman – “Study of tumor cell populations by Monte Carlo methods”. The next year she was first author of “On certain sequences of integers defined by sieves” with mathematical physicist Roger Lazarus, Metropolis and Ulam (Mathematics Magazine 29 117). She also worked with physicist George Gamow on attempts to discover the code for DNA selection of amino acids, which just shows the breadth of projects she was involved in.

Evans not only worked with Harlow but took part in a 1959 conference on self-organizing systems, where she queried AI pioneer Frank Rosenblatt on his ideas about human and machine learning. Her attendance at such a meeting, in an age when women were not common attendees, implies we should not view her as “just a coder”.

With their many and wide-ranging contributions, it is more than likely that Evans, Gardiner, Tsingou and many others were full-fledged researchers, and were perhaps even the first computational scientists. “These women were doing work that modern computational physicists in the [Los Alamos] lab’s XCP [Weapons Computational Physics] Division do,” says Nicholas Lewis, a historian at Los Alamos. “They needed a deep understanding of both the physics being studied, and of how to map the problem to the particular architecture of the machine being used.”

Overlooked then, overlooked now

Credited or not, these pioneering women and their contributions have been mostly forgotten, and only in recent decades have their roles come to light again. But why were they obscured by history in the first place?

Secrecy and sexism seem to be the main factors at play. For example, Livesay was not allowed to pursue a PhD in mathematics because she was a woman, and in the cases of the many married couples, the team contributions were attributed exclusively to the husband. The existence of the Manhattan Project was publicly announced in 1945, but documents that contain certain nuclear-weapons-related information remain classified today. Because these are likely to remain secret, we will never know the full extent of these pioneers’ contributions.

But another often overlooked reason is the widespread underappreciation of the key role of computational scientists and research software engineers, a term that was only coined just over a decade ago. Even today, these non-traditional research roles end up being undervalued. A 2022 survey by the UK Software Sustainability Institute, for example, showed that only 59% of research software engineers were named as authors, with barely a quarter (24%) mentioned in the acknowledgements or main text, while a sixth (16%) were not mentioned at all.

The separation between those who understand the physics and those who write the code, understand and operate the hardware goes back to the early days of computing (see box above), but it wasn’t entirely accurate even then. People who implement complex scientific computations are not just coders or skilled operators of supercomputers, but truly multidisciplinary scientists who have a deep understanding of the scientific problems, mathematics, computational methods and hardware.

Such people – whatever their gender – play a key role in advancing science and yet remain the unsung heroes of the discoveries their work enables. Perhaps what this story of the forgotten pioneers of computational physics tells us is that some views rooted in the 1950s are still influencing us today. It’s high time we moved on.

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Gravity might be able to quantum-entangle particles even if the gravitational field itself is classical. That is the conclusion of a new study by Joseph Aziz and Richard Howl at Royal Holloway University of London. This challenges a popular view that such entanglement would necessarily imply that gravity must be quantized. This could be important in the ongoing attempt to develop a theory of quantum gravity that unites quantum mechanics with Einstein’s general theory of relativity.

“When you try to quantize the gravitational interaction in exactly the same way we tried to mathematically quantize the other forces, you end up with mathematically inconsistent results – you end up with infinities in your calculations that you can’t do anything about,” Howl tells Physics World.

“With the other interactions, we quantized them assuming they live within an independent background of classical space and time,” Howl explains. “But with quantum gravity, arguably you cannot do this [because] gravity describes space−time itself rather than something within space−time.”

Quantum entanglement occurs when two particles share linked quantum states even when separated. While it has become a powerful probe of the gravitational field, the central question is whether gravity can mediate entanglement only if it is itself quantum in nature.

General treatment

“It has generally been considered that the gravitational interaction can only entangle matter if the gravitational field is quantum,” Howl says. “We have argued that you could treat the gravitational interaction as more general than just the mediation of the gravitational field such that even if the field is classical, you could in principle entangle matter.”

Quantum field theory postulates that entanglement between masses arises through the exchange of virtual gravitons. These are hypothetical, transient quantum excitations of the gravitational field. Aziz and Howl propose that even if the field remains classical, virtual-matter processes can still generate entanglement indirectly. These processes, he says, “will persist even when the gravitational field is considered classical and could in principle allow for entanglement”.

The idea of probing the quantum nature of gravity through entanglement goes back to a suggestion by Richard Feynman in the 1950s. He envisioned placing a tiny mass in a superposition of two locations and checking whether its gravitational field was also superposed. Though elegant, the idea seemed untestable at the time.

Recent proposals − most notably by teams led by Sougato Bose and by Chiara Marletto and Vlatko Vedral – revived Feynman’s insight in a more practical form.

Feasible tests

“Recently, two proposals showed that one way you could test that the field is in a superposition (and thus quantum) is by putting two masses in a quantum superposition of two locations and seeing if they become entangled through the gravitational interaction,” says Howl. “This also seemed to be much more feasible than Feynman’s original idea.” Such experiments might use levitated diamonds, metallic spheres, or cold atoms – systems where both position and gravitational effects can be precisely controlled.

Aziz and Howl’s work, however, considers whether such entanglement could arise even if gravity is not quantum. They find that certain classical-gravity processes can in principle entangle particles, though the predicted effects are extremely small.

“These classical-gravity entangling effects are likely to be very small in near-future experiments,” Howl says. “This though is actually a good thing: it means that if we see entanglement…we can be confident that this means that gravity is quantized.”

The paper has drawn a strong response from some leading figures in the field, including Marletto at the University of Oxford, who co-developed the original idea of using gravitationally induced entanglement as a test of quantum gravity.

“The phenomenon of gravitationally induced entanglement … is a game changer in the search for quantum gravity, as it provides a way to detect quantum effects in the gravitational field indirectly, with laboratory-scale equipment,” she says. Detecting it would, she adds, “constitute the first experimental confirmation that gravity is quantum, and the first experimental refutation of Einstein’s relativity as an adequate theory of gravity”.

However, Marletto disputes Aziz and Howl’s interpretation. “No classical theory of gravity can mediate entanglement via local means, contrary to what the study purports to show,” she says. “What the study actually shows is that a classical theory with direct, non-local interactions between the quantum probes can get them entangled.” In her view, that mechanism “is not new and has been known for a long time”.

Despite the controversy, Howl and Marletto agree that experiments capable of detecting gravitationally induced entanglement would be transformative. “We see our work as strengthening the case for these proposed experiments,” Howl says. Marletto concurs that “detecting gravitationally induced entanglement will be a major milestone … and I hope and expect it will happen within the next decade.”

Howl hopes the work will encourage further discussion about quantum gravity. “It may also lead to more work on what other ways you could argue that classical gravity can lead to entanglement,” he says.

The research is described in Nature.

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Better together. That’s the headline take on a newly inked technology partnership between Bluefors, a heavyweight Finnish supplier of cryogenic measurement systems, and Delft Circuits, a Dutch manufacturer of specialist I/O cabling solutions designed for the scale-up and industrial deployment of next-generation quantum computers.

The drivers behind the tie-up are clear: as quantum systems evolve – think vastly increased qubit counts plus ever-more exacting requirements on gate fidelity – developers in research and industry will reach a point where current coax cabling technology doesn’t cut it anymore. The answer? Collaboration, joined-up thinking and product innovation.

In short, by integrating Delft Circuits’ Cri/oFlex^® cabling technology into Bluefors’ dilution refrigerators, the vendors’ combined customer base will benefit from a complete, industrially proven and fully scalable I/O solution for their quantum systems. The end-game: to overcome the quantum tech industry’s biggest bottleneck, forging a development pathway from quantum computing systems with hundreds of qubits today to tens of thousands of qubits by 2030.

Joined-up thinking

For context, Cri/oFlex^® cryogenic RF cables comprise a stripline (a type of transmission line) based on planar microwave circuitry – essentially a conducting strip encapsulated in dielectric material and sandwiched between two conducting ground planes. The use of the polyimide Kapton^® as the dielectric ensures Cri/oFlex^® cables remain flexible in cryogenic environments (which are necessary to generate quantum states, manipulate them and read them out), with silver or superconducting NbTi providing the conductive strip and ground layer. The standard product comes as a multichannel flex (eight channels per flex) with a range of I/O channel configurations tailored to the customer’s application needs, including flux bias lines, microwave drive lines, signal lines or read-out lines.

“Reliability is a given with Cri/oFlex^®,” says Robby Ferdinandus, global chief commercial officer for Delft Circuits and a driving force behind the partnership with Bluefors. “By integrating components such as attenuators and filters directly into the flex,” he adds, “we eliminate extra parts and reduce points of failure. Combined with fast thermalization at every temperature stage, our technology ensures stable performance across thousands of channels, unmatched by any other I/O solution.”

Technology aside, the new partnership is informed by a “one-stop shop” mindset, offering the high-density Cri/oFlex^® solution pre-installed and fully tested in Bluefors cryogenic measurement systems. For the end-user, think turnkey efficiency: streamlined installation, commissioning, acceptance and, ultimately, enhanced system uptime.

Scalability is front-and-centre too, thanks to Delft Circuits’ pre-assembled and tested side-loading systems. The high-density I/O cabling solution delivers up to 50% more channels per side-loading port to Bluefors’ (current) High Density Wiring, providing a total of 1536 input or control lines to an XLDsl cryostat. In addition, more wiring lines can be added to multiple KF ports as a custom option.

Doubling up for growth

Reciprocally, there’s significant commercial upside to this partnership. Bluefors is the quantum industry’s leading cryogenic systems OEM and, by extension, Delft Circuits now has access to the former’s established global customer base, amplifying its channels to market by orders of magnitude. “We have stepped into the big league here and, working together, we will ensure that Cri/oFlex^® becomes a core enabling technology on the journey to quantum advantage,” notes Ferdinandus.

That view is amplified by Reetta Kaila, director for global technical sales and new products at Bluefors (and, alongside Ferdinandus, a main-mover behind the partnership). “Our market position in cryogenics is strong, so we have the ‘muscle’ and specialist know-how to integrate innovative technologies like Cri/oFlex^® into our dilution refrigerators,” she explains.

A win-win, it seems, along several coordinates. “The Bluefors sales teams are excited to add Cri/oFlex^® into the product portfolio,” Kaila adds. “It’s worth noting, though, that the collaboration extends across multiple functions – technical and commercial – and will therefore ensure close alignment of our respective innovation roadmaps.”

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International research collaborations will be increasingly led by scientists in China over the coming decade. That is according to a new study by researchers at the University of Chicago, which finds that the power balance in international science has shifted markedly away from the US and towards China over the last 25 years (Proc. Natl. Acad. Sci. 122 e2414893122).

To explore China’s role in global science, the team used a machine-learning model to predict the lead researchers of almost six million scientific papers that involved international collaboration listed by online bibliographic catalogue OpenAlex. The model was trained on author data from 80 000 papers published in high-profile journals that routinely detail author contributions, including team leadership.

The study found that between 2010 and 2012 there were only 4429 scientists from China who were likely to have led China-US collaborations. By 2023, this number had risen to 12714, meaning that the proportion of team leaders affiliated with Chinese institutions had risen from 30% to 45%.

Key areas

If this trend continues, China will hit “leadership parity” with the US in chemistry, materials science and computer science by 2028, with maths, physics and engineering being level by 2031. The analysis also suggests that China will achieve leadership parity with the US in eight “critical technology” areas by 2030, including AI, semiconductors, communications, energy and high-performance computing.

For China-UK partnerships, the model found that equality had already been reached in 2019, while EU and China leadership roles will be on par this year or next. The authors also found that China has been actively training scientists in nations in the “Belt and Road Initiative” which seeks to connect China closer to the world through investments and infrastructure projects.

This, the researchers warn, limits the ability to isolate science done in China. Instead, they suggest that it could inspire a different course of action, with the US and other countries expanding their engagement with the developing world to train a global workforce and accelerate scientific advancements beneficial to their economies.

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The LIGO–Virgo–KAGRA collaboration has detected strong evidence for second-generation black holes, which were formed from earlier mergers of smaller black holes. The two gravitational wave signals provide one of the strongest confirmations to date for how Einstein’s general theory of relativity describes rotating black holes. Studying such objects also provides a testbed for probing new physics beyond the Standard Model.

Over the past decade, the global network of interferometers operated by LIGO, Virgo, and KAGRA have detected close to 300 gravitational waves (GWs) – mostly from the mergers of binary black holes.

In October 2024 the network detected a clear signal that pointed back to a merger that occurred 700 million light-years away. The progenitor black holes were 20 and 6 solar masses and the larger object was spinning at 370 Hz, which makes it one of the fastest-spinning black holes ever observed.

Just one month later, the collaboration detected the coalescence of another highly imbalanced binary (17 and 8 solar masses), 2.4 billion light-years away. This signal was even more unusual – showing for the first time that the larger companion was spinning in the opposite direction of the binary orbit.

Massive and spinning

While conventional wisdom says black holes should not be spinning at such high rates, the observations were not entirely unexpected. “With both events having one black hole, which is both significantly more massive than the other and rapidly spinning, [the observations] provide tantalizing evidence that these black holes were formed from previous black hole mergers,” explains Stephen Fairhurst at Cardiff University, spokesperson of the LIGO Collaboration. If this were the case, the two GW signals – called GW241011 and GW241110 – are first observations of second-generation black holes. This is because when a binary merges, the resulting second-generation object tends to have a large spin.

The GW241011 signal was particularly clear, which allowed the team to make the third-ever observation of higher harmonic modes. These are overtones in the GW signal that become far clearer when the masses of the coalescing bodies are highly imbalanced.

The precision of the GW241011 measurement provides one of the most stringent verifications so far of general relativity. The observations also support Roy Kerr’s prediction that rapid rotation distorts the shape of a black hole.

Kerr and Einstein confirmed

“We now know that black holes are shaped like Einstein and Kerr predicted, and general relativity can add two more checkmarks in its list of many successes,” says team member Carl-Johan Haster at the University of Nevada, Las Vegas. “This discovery also means that we’re more sensitive than ever to any new physics that might lie beyond Einstein’s theory.”

This new physics could include hypothetical particles called ultralight bosons. These could form in clouds just outside the event horizons of spinning black holes, and would gradually drain a black hole’s rotational energy via a quantum effect called superradiance.

The idea is that the observed second-generation black holes had been spinning for billions of years before their mergers occurred. This means that if ultralight bosons were present, they cannot have removed lots of angular momentum from the black holes. This places the tightest constraint to date on the mass of ultralight bosons.

“Planned upgrades to the LIGO, Virgo and KAGRA detectors will enable further observations of similar systems,” Fairhurst says. “They will enable us to better understand both the fundamental physics governing these black hole binaries and the astrophysical mechanisms that lead to their formation.”

Haster adds, “Each new detection provides important insights about the universe, reminding us that each observed merger is both an astrophysical discovery but also an invaluable laboratory for probing the fundamental laws of physics”.

The observations are described in The Astrophysical Journal Letters.

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