Today’s artificial intelligence (AI) systems are built on data generated by humans. They’re trained on huge repositories of writing, images and videos, most of which have been scraped from the Internet without the knowledge or consent of their creators. It’s a vast and sometimes ill-gotten treasure trove of information – but for machine-learning pioneer David Silver, it’s nowhere near enough.

“I think if you provide the knowledge that humans already have, it doesn’t really answer the deepest question for AI, which is how it can learn for itself to solve problems,” Silver told an audience at the 12^th Heidelberg Laureate Forum (HLF) in Heidelberg, Germany, on Monday.

Silver’s proposed solution is to move from the “era of human data”, in which AI passively ingests information like a student cramming for an exam, into what he calls the “era of experience” in which it learns like a baby exploring its world. In his HLF talk on Monday, Silver played a sped-up video of a baby repeatedly picking up toys, manipulating them and putting them down while crawling and rolling around a room. To murmurs of appreciation from the audience, he declared, “I think that provides a different perspective of how a system might learn.”

Silver, a computer scientist at University College London, UK, has been instrumental in making this experiential learning happen in the virtual worlds of computer science and mathematics. As head of reinforcement learning at Google DeepMind, he was instrumental in developing AlphaZero, an AI system that taught itself to play the ancient stones-and-grid game of Go. It did this via a so-called “reward function” that pushed it to improve over many iterations, without ever being taught the game’s rules or strategy.

More recently, Silver coordinated a follow-up project called AlphaProof that treats formal mathematics as a game. In this case, AlphaZero’s reward is based on getting correct proofs. While it isn’t yet outperforming the best human mathematicians, in 2024 it achieved silver-medal standard on problems at the International Mathematical Olympiad.

Learning in the physics playroom

Could a similar experiential learning approach work in the physical sciences? At an HLF panel discussion on Tuesday afternoon, particle physicist Thea Klaeboe Åarrestad began by outlining one possible application. Whenever CERN’s Large Hadron Collider (LHC) is running, Åarrestad explained, she and her colleagues in the CMS experiment must control the magnets that keep protons on the right path as they zoom around the collider. Currently, this task is performed by a person, working in real time.

In principle, Åarrestad continued, a reinforcement-learning AI could take over that job after learning by experience what works and what doesn’t. There’s just one problem: if it got anything wrong, the protons would smash into a wall and melt the beam pipe. “You don’t really want to do that mistake twice,” Åarrestad deadpanned.

For Åarrestad’s fellow panellist Kyle Cranmer, a particle physicist who works on data science and machine learning at the University of Wisconsin-Madison, US, this nightmare scenario symbolizes the challenge with using reinforcement learning in physical sciences. In situations where you’re able to do many experiments very quickly and essentially for free – as is the case with AlphaGo and its descendants – you can expect reinforcement learning to work well, Cranmer explained. But once you’re interacting with a real, physical system, even non-destructive experiments require finite amounts of time and money.

Another challenge, Cranmer continued, is that particle physics already has good theories that predict some quantities to multiple decimal places. “It’s not low-hanging fruit for getting an AI to come up with a replacement framework de novo,” Cranmer said. A better option, he suggested, might be to put AI to work on modelling atmospheric fluid dynamics, which are emergent phenomena without first-principles descriptions. “Those are super-exciting places to use ideas from machine learning,” he said.

Not for nuclear arsenals

Silver, who was also on Tuesday’s panel, agreed that reinforcement learning isn’t always the right solution. “We should do this in areas where mistakes are small and it can learn from those small mistakes to avoid making big mistakes,” he said. To general laughter, he added that he would not recommend “letting an AI loose on nuclear arsenals”, either.

Reinforcement learning aside, both Åarrestad and Cranmer are highly enthusiastic about AI. For Cranmer, one of the most exciting aspects of the technology is the way it gets scientists from different disciplines talking to each other. The HLF, which aims to connect early-career researchers with senior figures in mathematics and computer science, is itself a good example, with many talks in the weeklong schedule devoted to AI in one form or another.

For Åarrestad, though, AI’s most exciting possibility relates to physics itself. Because the LHC produces far more data than humans and present-day algorithms can handle, Åarrestad explained, much of it is currently discarded. The idea that, as a result, she and her colleagues could be throwing away major discoveries sometimes keeps her up at night. “Is there new physics below 1 TeV?” Åarrestad wondered.

Someday, maybe, an AI might be able to tell us.

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Radiotherapy is a precision cancer therapy that employs personalized treatment plans to target radiation to tumours with high accuracy. Such plans are usually created from high-resolution CT scans of the patient. But interest is growing in an alternative approach: MR simulation, in which MR images are used to generate the treatment plans – for delivery on conventional linac systems as well as the increasingly prevalent MR-guided radiotherapy systems.

One site that has transitioned to this approach is the Institut Jules Bordet in Belgium, which in 2021 acquired both an Elekta Unity MR-Linac and a Siemens MAGNETOM Aera MR-Simulator. “It was a long-term objective for our clinic to have an MR-only workflow,” says Akos Gulyban, a medical physicist at Institut Jules Bordet. “When we moved to a new campus, we decided to purchase the MR-Linac. Then we thought that if we are getting into the MR world for treatment adaptation, we also need to step up in terms of simulation.”

The move to MR simulation delivers many clinical benefits, with MR images providing the detailed anatomical information required to delineate targets and organs-at-risk with the highest precision. But it also creates new challenges for the physicists, particularly when it comes to quality assurance (QA) of MR-based systems. “The biggest concern is geometric distortion,” Gulyban explains. “If there is no distortion correction, then the usability of the machine or the sequence is very limited.”

Addressing distortion

While the magnetic field gradient is theoretically linear, and MRI is indeed extremely accurate at the imaging isocentre, moving away from the isocentre increases distortion. Images of regions 30 or 40 cm away from the isocentre – a reasonable distance for a classical linac – can differ from reality by 15 to 20 mm, says Gulyban. Thankfully, 3D correction algorithms can reduce this discrepancy down to just a couple of millimetres. But such corrections first require an accurate way to measure the distortion.

To address this task, the team at Institut Jules Bordet employ a geometric distortion phantom –the QUASAR MRID^3D Geometric Distortion Analysis System from IBA Dosimetry. Gulyban explains that the MRID^3D was chosen following discussions with experienced users, and that key selling points included the phantom’s automated software and its ability to efficiently store results for long-term traceability.

“My concern was how much time we spend cross-processing, generating reports or evaluating results,” he says. “This software is fully automated, making it much easier to perform the evaluation and less dependent on the operator.”

Gulyban adds that the team was looking for a vendor-independent solution. “I think it is a good approach to use the tools provided [by the vendor] but now we have a way to measure the same thing using a different approach. Since our new campus has a mixture of Siemens MRs and the MR-Linac, this phantom provides a vendor-independent bridge between the two worlds.”

For quality control of the MR-Simulator, the team perform distortion measurements every three months, as well as after system interventions such as shimming and following any problems arising during other routine QA procedures. “We should not consider tests as individual islands in the QA process,” says Gulyban. “For instance, the ACR image quality phantom, which is used for more frequent evaluation, also partly assesses distortion. If we see that failing, I would directly trigger measurements with the more appropriate geometric distortion phantom.”

A lightweight option

To perform MR simulation, the images used for treatment planning must encompass both the target volume and the surrounding region, to ensure accurate delineation of the tumour and nearby organs-at-risk. This requires a large field-of-view (FOV) scan – plus geometric distortion QA that covers the same large FOV.

“You’re using this image to delineate the target and also to spare the organs-at-risk, so the image must reflect reality,” explains Kawtar Lakrad, medical physicist and clinical application specialist at IBA Dosimetry. “You don’t want that image to be twisted or the target volume to appear smaller or bigger than it actually is. You want to make sure that all geometric qualities of the image align with what’s real.”

Typically, geometric distortion phantoms are grid-like, with control points spaced every 0.5 or 1 cm. The entire volume is imaged in the MR scanner and the locations of control points seen in the image compared with their actual positions. “If we apply this to a large FOV phantom, which for MRI will be filled with either water or oil, it’s going to be a very large grid and it’s going to be heavy, 40 or 50 kg,” says Lakrad.

To overcome this obstacle, IBA researchers used innovative harmonic analysis algorithms to design a lightweight geometric distortion phantom with submillimetre accuracy and a large (35 x 30 cm) FOV: the MRID^3D. The phantom comprises two concentric hollow acrylic cylinders, the only liquid being a prefilled mineral oil layer between the two shells, reducing its weight to just 21 kg.

“The idea behind the phantom was very smart because it relies on a mathematical tool,” explains Lakrad. “There is a Fourier transform for the linear signal, which is used for standard grids. But there are also spherical harmonics – and this is what’s used in the MRID^3D. The control points are all on the cylinder surface, plus one in the isocentre, creating a virtual grid that measures 3D geometric distortion.” She adds that the MRID^3D can also differentiate distortion due to the main magnetic field from gradient non-linearity distortion.

Moving into the MR world

Gulyban and his team at Institut Jules Bordet first used MR simulation for pelvic treatments, particularly prostate cancer, he tells Physics World. This was followed by abdominal tumours, such as pancreatic and liver cancers (where many patients were being treated on the MR-Linac) and more recently, cranial and head-and-neck irradiations.

Gulyban points out that the introduction of the MR-Simulator was eased by the team’s experience with the MR-Linac, which helped them “step into the MR world”. Here also, the MRID^3D phantom is used to quantify geometric distortion, both for initial commissioning and continuous QA of the MR-Linac.

“It’s like a consistency check,” he explains. “We have certain manufacturer-defined conditions that we need to meet for the MR-Linac – for instance, that distortion within a 40 mm diameter should be less than 1 mm. To ensure that these are met in a consistent fashion, we repeat the measurements with the manufacturer’s phantom and with the MRID^3D. This gives us extra peace of mind that the machine is performing under the correct conditions.”

For other cancer centres looking to integrate MR into their radiotherapy clinics, Gulyban has some key points of advice. These include starting with MR-guided radiotherapy and then adding MR simulation, identifying a suitable pathology to treat first and gain familiarity, and attending relevant courses or congresses for inspiration.

“The biggest change is actually a change in culture because you have an active MRI in the radiotherapy department,” he notes. “We are used to the radioprotection aspects of radiotherapy, wearing a dosimeter and observing radiation protection principles. MRI is even less forgiving – every possible thing that could go wrong you have to eliminate. Closing all the doors and emptying your pockets must become a reflex habit. You have to prepare mentally for that.”

“When you’re used to CT-based machines, moving to an MR workflow can be a little bit new,” adds Lakrad. “Most physicists are already familiar with the MR concept, but when it comes to the QA process, that’s the most challenging part. Some people would just repeat what’s done in radiology – but the use case is different. In radiotherapy, you have to delineate the target and surrounding volumes exactly. You’re going to be delivering dose, which means the tolerance between diagnostic and radiation therapy is different. That’s the biggest challenge.”

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Artificial intelligence (AI) could help sniff out questionable open-access publications that are more interested in profit than scientific integrity. That is according to an analysis of 15,000 scientific journals by an international team of computer scientists. They find that dubious journals tend to publish an unusually high number of articles and feature authors who have many affiliations and frequently self-cite (Sci. Adv. 11 eadt2792).

Open access removes the requirement for traditional subscriptions. Articles are instead made immediately and freely available for anyone to read, with publication costs covered by authors by paying an article-processing charge.

But as the popularity of open-access journals has risen, there has been a growth in “predatory” journals that exploit the open-access model by making scientists pay publication fees without a proper peer-review process in place.

To build an AI-based method for distinguishing legitimate from questionable journals, Daniel Acuña, a computer scientist at the University of Colorado Boulder, and colleagues used the Directory of Open Access Journals (DOAJ) – an online, community-curated index of open-access journals.

The researchers trained their machine-learning model on 12,869 journals indexed on the DOAJ and 2536 journals that have been removed from the DOAJ due to questionable practices that violate the community’s listing criteria. The team then tested the tool on 15,191 journals listed by Unpaywall, an online directory of free research articles.

To identify questionable journals, the AI-system analyses journals’ bibliometric information and the content and design of their websites, scrutinising details such as the affiliations of editorial board members and the average author h-index – a metric that quantifies a researcher’s productivity and impact.

The AI-model flagged 1437 journals as questionable, with the researchers concluding that 1092 were genuinely questionable while 345 were false positives.

They also identified around 1780 problematic journals that the AI screening failed to flag. According to the study authors, their analysis shows that problematic publishing practices leave detectable patterns in citation behaviour such as the last authors having a low h-index together with a high rate of self-citation.

Acuña adds that the tool could help to pre-screen large numbers of journals, adding, however, that “human professionals should do the final analysis”. The researcher’s novel AI screening system isn’t publicly accessible but they hope to make it available to universities and publishing companies soon.

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It’s almost impossible to avoid reading about advances in quantum computing these days. Despite this, we’re still some way off having fully fault-tolerant, large-scale quantum computers as of right now. One practical difficulty is that even the best present-day quantum computers suffer from noise that can often cause them to return erroneous results.

Research in this field can be broadly divided into two areas: a) designing quantum algorithms with potential practical advantages over classical algorithms (the software) and b) physically building a quantum computer (the hardware).

One of the main approaches to algorithm design is to minimise the number of operations or runtime in an algorithm. One intuitively expects that reducing the number of operations would decrease the chance of errors – the key to constructing a reliable quantum computer.

However, this is not always the case. In a recent paper, the research team found that minimising the number of operations in a quantum algorithm can sometimes be counterproductive, leading to an increased sensitivity to noise. Essentially, running a faster algorithm in non-ideal conditions can result in more errors than if a slower algorithm had been used.

The authors proved that there’s a trade-off between an algorithm’s number of operations and its resilience to noise. This means that, for certain types of errors, slower algorithms might actually be better in some real-world conditions.

These results bring together research on quantum hardware and software. The mathematical framework developed will enable quantum algorithms to be designed with the limitations of current real quantum computers in mind.

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Despite the huge success of the Standard Model of particle physics, we know it’s not complete. Dark matter and neutrino masses are just two of the things that are conspicuously missing in our current theory.

However, it’s been notoriously difficult to perform an experiment that actually disagrees with the model’s predictions.

Many proposed extensions of the Standard Model, such as the fraternal twin Higgs or folded supersymmetry models, include so-called long-lived particles (LLPs).

Unlike most particles produced in high-energy collisions, which decay almost instantaneously, LLPs have relatively long lifetimes, meaning they travel a measurable distance before decaying.

A new paper from the CMS collaboration at CERN searched for evidence of these particles by re-examining previous data from proton-proton collision events.

The new analysis used new techniques such as machine-learning methods to enhance the sensitivity to LLPs.

So, did they find any new particles? The short answer, unfortunately, is no.

However, the new study achieves up to a tenfold improvement over previous limits for LLP masses. It also places the first constraints on many proposed models that predict these particles.

Although this study found no new physics, we’re still confident that something must be out there. And by narrowing down the possible spaces where we might find new particles, we’re one step closer to finding them.

The search continues.

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Call it millennial, generation Y or fin de siècle, high-energy physics during the last two decades of the 20th century had a special flavour. The principal pieces of the Standard Model of particle physics had come together remarkably tightly – so tightly, in fact, that physicists had to rethink what instruments to build, what experiments to plan, and what theories to develop to move forward. But it was also an era when the hub of particle physics moved from the US to Europe.

The momentous events of the 1980s and 1990s will be the focus of the 4th International Symposium on the History of Particle Physics, which is being held from 10–13 November at CERN. The meeting will take place more than four decades after the first symposium in the series was held at Fermilab near Chicago in 1980. Entitled The Birth of Particle Physics, that initial meeting covered the years 1930 to 1950.

Speakers back then included trailblazers such as Paul Dirac, Julian Schwinger and Victor Weisskopf. They reviewed discoveries such as the neutron and the positron and the development of relativistic quantum field theory. Those two decades before 1950 were a time when particle physicists “constructed the room”, so to speak, in which the discipline would be based.

The second symposium – Pions to Quarks – was also held at Fermilab and covered the 1950s. Accelerators could now create particles seen in cosmic-ray collisions, populating what Robert Oppenheimer called the “particle zoo”. Certain discoveries of this era, such as parity violation in the weak interaction, were so shocking that C N Yang likened it to having a blackout and not knowing if the room would look the same when the lights came back on. Speakers at that 1985 event included Luis Alvarez, Val Fitch, Abdus Salam, Robert Wilson and Yang himself.

The third symposium, The Rise of the Standard Model, was held in Stanford, California, in 1992 and covered the 1960s and 1970s. It was a time not of blackouts but of disruptions that dimmed the lights. Charge-parity violation and the existence of two types of neutrino were found in the 1960s, followed in the 1970s by deep inelastic electron scattering and quarks, neutral currents, a fourth quark and gluon jets.

These discoveries decimated alternative approaches to quantum field theory, which was duly established for good as the skeleton of high-energy physics. The era culminated with Sheldon Glashow, Abdus Salam and Steven Weinberg winning the 1979 Nobel Prize for Physics for their part in establishing the Standard Model. Speakers at that third symposium included Murray Gell-Mann, Leon Lederman and Weinberg himself.

Changing times

The upcoming CERN event, on whose programme committee I serve, will start exactly where the previous symposium ended. “1980 is a natural historical break,” says conference co-organizer Michael Riordan, who won the 2025 Abraham Pais Prize for History of Physics. “It begins a period of the consolidation of the Standard Model. Colliders became the main instruments, and were built with specific standard-model targets in mind. And the centre of gravity of the discipline moved across the Atlantic to Europe.”

The conference will address physics that took place at CERN’s Super Proton Synchrotron (SPS), where the W and Z particles were discovered in 1983. It will also examines the SPS’s successor – the Large Electron-Positron (LEP) collider. Opened in 1989, it was used to make precise measurements of these and other implications of the Standard Model until being controversially shut down in 2000 to make way for the Large Hadron Collider (LHC).

There will be coverage as well of failed accelerator projects, which – perhaps perversely – can be equally interesting and revealing as successful facilities

Speakers at the meeting will also discuss Fermilab’s Tevatron, where the top quark – another Standard Model component – was found in 1995. Work at the Stanford Linear Accelerator Center, DESY in Germany, and Tsukuba, Japan, will be tackled too. There will be coverage as well of failed accelerator projects, which – perhaps perversely – can be equally interesting and revealing as successful facilities.

In particular, I will speak about ISABELLE, a planned and partially built proton–proton collider at Brookhaven National Laboratory, which was terminated in 1983 to make way for the far more ambitious Superconducting Super Collider (SSC). ISABELLE was then transformed into the Relativistic Heavy Ion Collider (RHIC), which was completed in 1999 and took nuclear physics into the high-energy regime.

Riordan will talk about the fate of the SSC, which was supposed to discover the Higgs boson or whatever else plays its mass-generating role. But in 1993 the US Congress terminated that project, a traumatic episode for US physics, about which Riordan co-authored the book Tunnel Visions. Its cancellation signalled the end of the glory years for US particle physics and the realization of the need for international collaborations in ever-costlier accelerator projects.

The CERN meeting will also explore more positive developments such as the growing convergence of particle physics and cosmology during the 1980s and 1990s. During that time, researchers stepped up their studies of dark matter, neutrino oscillations and supernovas. It was a period that saw the construction of underground detectors at Gran Sasso in Italy and Kamiokande in Japan.

Other themes to be explored include the development of the Web – which transformed the world – and the impact of globalization, the end of the Cold War, and the rise of high-energy physics in China, and physics in Russia, former Soviet Union republics, and former Eastern Bloc countries. While particle physics became more global, it also grew more dependent on, and vulnerable to, changing political ambitions, economic realities and international collaborations. The growing importance of diversity, communication and knowledge transfer will be looked at too.

The critical point

The years between 1980 and 2000 were a distinct period in the history of particle physics. It took place in the afterglow of the triumph of the Standard Model. The lights in high energy physics did not go out or even dim, to use Yang’s metaphor. Instead, the Standard Model shed so much light on high-energy physics that the effort and excitement focused around consolidating the model.

Particle physics, during those years, was all about finding the deeply hidden outstanding pieces, developing the theory, and connecting with other areas of physics. The triumph was so complete that physicists began to wonder what bigger and more comprehensive structure the Standard Model’s “room” might be embedded in – what was “beyond the Standard Model”. A quarter of a century on, out attempts to make out that structure is still an ongoing task.

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When researchers at Microsoft released a list of the 40 jobs most likely to be affected by generative artificial intelligence (gen AI), few outsiders would have expected to see “mathematician” among them. Yet according to speakers at this year’s Heidelberg Laureate Forum (HLF), which connects early-career researchers with distinguished figures in mathematics and computer science, computers are already taking over many tasks formerly performed by human mathematicians – and the humans have mixed feelings about it.

One of those expressing disquiet is Yang-Hui He, a mathematical physicist at the London Institute for Mathematical Sciences. In general, He is extremely keen on AI. He’s written a textbook about the use of AI in mathematics, and he told the audience at an HLF panel discussion that he’s been peddling machine-learning techniques to his mathematical physics colleagues since 2017.

More recently, though, He has developed concerns about gen AI specifically. “It is doing mathematics so well without any understanding of mathematics,” he said, a note of wonder creeping into his voice. Then, more plaintively, he added, “Where is our place?”

AI advantages

Some of the things that make today’s gen AI so good at mathematics are the same as the ones that made Google’s DeepMind so good at the game of Go. As the theoretical computer scientist Sanjeev Arora pointed out in his HLF talk, “The reason it’s better than humans is that it’s basically tireless.” Put another way, if the 20th-century mathematician Alfréd Rényi once described his colleagues as “machines for turning coffee into theorems”, one advantage of 21st-century AI is that it does away with the coffee.

Arora, however, sees even greater benefits. In his view, AI’s ability to use feedback to improve its own performance – a technique known as reinforcement learning – is particularly well-suited to mathematics.

In the standard version of reinforcement learning, Arora explains, the AI model is given a large bank of questions, asked to generate many solutions and told to use the most correct ones (as labelled by humans) to refine its model. But because mathematics is so formalized, with answers that are so verifiably true or false, Arora thinks it will soon be possible to replace human correctness checkers with AI “proof assistants”. Indeed, he’s developing one such assistant himself, called Lean, with his colleagues at Princeton University in the US.

Humans in the loop?

But why stop there? Why not use AI to generate mathematical questions as well as producing and checking their solutions? Indeed, why not get it to write a paper, peer review it and publish it for its fellow AI mathematicians – which are, presumably, busy combing the literature for information to help them define new questions?

Arora clearly thinks that’s where things are heading, and many of his colleagues seem to agree, at least in part. His fellow HLF panellist Javier Gómez-Serrano, a mathematician at Brown University in the US, noted that AI is already generating results in a day or two that would previously have taken a human mathematician months. “Progress has been quite quick,” he said.

The panel’s final member, Maia Fraser of the University of Ottawa, Canada, likewise paid tribute to the “incredible things that are possible with AI now”.  But Fraser, who works on mathematical problems related to neuroscience, also sounded a note of caution. “My concern is the speed of the changes,” she told the HLF audience.

The risk, Fraser continued, is that some of these changes may end up happening by default, without first considering whether humans want or need them. While we can’t un-invent AI, “we do have agency” over what we want, she said.

So, do we want a world in which AI mathematicians take humans “out of the loop” entirely? For He, the benefits may outweigh the disadvantages. “I really want to see a proof of the Riemann hypothesis,” he said,  to ripples of laughter. If that means that human mathematicians “become priests to oracles”, He added, so be it.

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The first-ever “space–time crystal” has been created in the US by Hanqing Zhao and Ivan Smalyukh at the University of Colorado Boulder. The system is patterned in both space and time and comprises a rigid lattice of topological solitons that are sustained by steady oscillations in the orientations of liquid crystal molecules.

In an ordinary crystal atomic or molecular structures repeat at periodic intervals in space. In 2012, however, Frank Wilczek suggested that systems might also exist with quantum states that repeat at perfectly periodic intervals in time – even as they remain in their lowest-energy state.

First observed experimentally in 2017, these time crystals are puzzling to physicists because they spontaneously break time–translation symmetry, which states that the laws of physics are the same no matter when you observe them. In contrast, a time crystal continuously oscillates over time, without consuming energy.

A space–time crystal is even more bizarre. In addition to breaking time–translation symmetry, such a system would also break spatial symmetry, just like the repeating molecular patterns of an ordinary crystal. Until now, however, a space–time crystal had not been observed directly.

Rod-like molecules

In their study, Zhao and Smalyukh created a space–time crystal in the nematic phase of a liquid crystal. In this phase the crystal’s rod-like molecules align parallel to each other and also flow like a liquid. Building on computer simulations, they confined the liquid crystal between two glass plates coated with a light-sensitive dye.

“We exploited strong light–matter interactions between dye-coated, light-reconfigurable surfaces, and the optical properties of the liquid crystal,” Smalyukh explains.

When the researchers illuminated the top plate with linearly polarized light at constant intensity, the dye molecules rotate to align perpendicular to the direction of polarization. This reorients nearby liquid crystal molecules, and the effect propagates deeper into the bulk. However, the influence weakens with depth, so that molecules farther from the top plate are progressively less aligned.

As light travels through this gradually twisting structure, its linear polarization is transformed, becoming elliptically polarized by the time it reaches the bottom plate. The dye molecules there become aligned with this new polarization, altering the liquid crystal alignment near the bottom plate. These changes propagate back upward, influencing molecules near the top plate again.

Feedback loop

This is a feedback loop, with the top and bottom plates continuously influencing each other via the polarized light passing through the liquid crystal.

“These light-powered dynamics in confined liquid crystals leads to the emergence of particle-like topological solitons and the space–time crystallinity,” Smalyukh says.

In this environment, particle-like topological solitons emerge as stable, localized twists in the liquid crystal’s orientation that do not decay over time. Like particles, the solitons move and interact with each other while remaining intact.

Once the feedback loop is established, these solitons emerge in a repeating lattice-like pattern. This arrangement not only persisted as the feedback loop continued, but is sustained by it. This is a clear sign that the system exhibits crystalline order in time and space simultaneously.

Accessible system

Having confirmed their conclusions with simulations, Zhao and Smalyukh are confident this is the first experimental demonstration of a space–time crystal. The discovery that such an exotic state can exist in a classical, room-temperature system may have important implications.

“This is the first time that such a phenomenon is observed emerging in a liquid crystalline soft matter system,” says Smalyukh. “Our study calls for a re-examining of various time-periodic phenomena to check if they meet the criteria of time-crystalline behaviour.”

Building on these results, the duo hope to broaden the scope of time crystal research beyond a purely theoretical and experimental curiosity. “This may help expand technological utility of liquid crystals, as well as expand the currently mostly fundamental focus of studies of time crystals to more applied aspects,” Smalyukh adds.

The research is described in Nature Materials.

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Physicists at Osaka Metropolitan University in Japan and the Korea Advanced Institute of Science and Technology (KAIST) claim to have observed the quantum counterpart of the classic Kelvin-Helmholtz instability (KHI), which is the most basic instability in fluids. The effect, seen in a quantum gas of ⁷Li atoms, produces a new type of exotic vortex pattern called an eccentric fractional skyrmion. The finding not only advances our understanding of complex topological quantum systems, it could also help in the development of next-generation memory and storage devices.

Topological defects occur when a system rapidly transitions from a disordered to an ordered phase. These defects, which can occur in a wide range of condensed matter systems, from liquid crystals and atomic gases to the rapidly cooling early universe, can produce excitations such as solitons, vortices and skyrmions.

Skyrmions, first discovered in magnetic materials, are swirling vortex-like spin structures that extend across a few nanometres in a material. They can be likened to 2D knots in which the magnetic moments rotate about 360° within a plane.

Eccentric fractional skyrmions contain singularities

Skyrmions are topologically stable, which makes them robust to external perturbations, and are much smaller than the magnetic domains used to encode data in today’s disk drives. That makes them ideal building blocks for future data storage technologies such as “racetrack” memories. Eccentric fractional skyrmions (EFSs), which had only been predicted in theory until now, have a crescent-like shape and contain singularities – points in which the usual spin structure breaks down, creating sharp distortions as it becomes unsymmetrical.

“To me, the large crescent moon in the upper right corner of Van Gogh’s ‘The Starry Night’ also looks exactly like an EFS,” says Hiromitsu Takeuchi at Osaka, who co-led this new study with Jae-Yoon Choi of KAIST. “EFSs carry half the elementary charge, which means they do not fit into traditional classifications of topological defects.”

The KHI is a classic phenomenon in fluids in which waves and vortices form at the interface between two fluids moving at different speeds. “To observe the KHI in quantum systems, we need a structure containing a thin superfluid interface (a magnetic domain wall), such as in a quantum gas of ⁷Li atoms,” says Takeuchi. “We also need experimental techniques that can skilfully control the behaviour of this interface. Both of these criteria have recently been met by Choi’s group.”

The researchers began by cooling a gas of ⁷Li atoms to near absolute zero temperatures to create a multi-component Bose-Einstein condensate – a quantum superfluid containing two streams flowing at different speeds. At the interface of these streams, they observed vortices, which corresponded to the predicted EFSs.

The behaviour of the KHI is universal

“We have shown that the behaviour of the KHI is universal and exists in both the classical and quantum regimes,” says Takeuchi. This finding could not only lead to a better understanding of quantum turbulence and the unification of quantum and classic hydrodynamics, it could also help in the development of technologies such as next-generation storage and memory devices and spintronics, an emerging technology in which magnetic spin is used to store and transfer information using much less energy than existing electronic devices.

“By further refining the experiment, we might be able to verify certain predictions (some of which were made as long ago as the 19th century) about the wavelength and frequency of KHI-driven interface waves in non-viscous quantum fluids, like the one studied in this work,” he adds.

“In addition to the universal finger pattern we observed, we expect structures like zipper and sealskin patterns, which are unique to such multi-component quantum fluids,” Takeuchi tells Physics World. “As well as experiments, it is necessary to develop a theory that more precisely describes the motion of EFSs, the interaction between these skyrmions and their internal structure in the context of quantum hydrodynamics and spontaneous symmetry breaking.”

The study is detailed in Nature Physics.

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For decades, physicists believed that the top quark, the heaviest known subatomic particle, was too short-lived to form a temporary pair with its antimatter partner. Unlike lighter quarks, which can combine to form protons, neutrons, or longer-lived quark–antiquark pairs, the top quark decays almost instantly. This made the idea of a top–antitop bound state – a fleeting association held together by the strong force – seem impossible. But now, the CMS collaboration at the Large Hadron Collider (LHC) has found the first evidence of such a state, which is dubbed toponium.

Gautier Hamel de Monchenault, spokesperson for CMS, explains, “Many physicists long believed this was impossible. That’s why this result is so significant — it challenges assumptions that have been around for decades, and particle physics textbooks will likely need to be updated because of it.”

Protons and neutrons are formed from quarks, which are fundamental particles that cannot be broken down into smaller constituents.

“There are six types of quark,” explains the German physicist Christian Schwanenberger, who is at DESY and the University of Hamburg and was not involved in the study. “Five of them form bound states thanks to the strong force, one of the four fundamental forces of nature. The top quark, however, is somehow different. It is the heaviest fundamental particle we know, but so far we have not observed it forming bound states in the same way the others do.”

Quasi-bound state

The top quark’s extreme mass makes it decay almost immediately after it is produced. “The top and antitop quarks just have time to exchange a few gluons, the carriers of the strong force, before one of them decays, hence the appellation ‘quasi-bound state’,” Hamel de Monchenault explains.

By detecting these ephemeral interactions, physicists can observe the strong force in a new regime – and the CMS team developed a clever new method to do so. The breakthrough came when the team examined how the spins of the top quark and antitop quark influence each other to create a subtle signature in the particles produced when the quarks decay.

Top quarks are produced in proton–proton collisions at the LHC, where they quickly decay into other particles. These include bottom quarks that then decay to form jets of particles, which can be detected. Top quarks can also decay to form W bosons, which themselves decay into lighter particles (leptons) such as electrons or muons, accompanied by neutrinos.

“We can detect the charged leptons directly and measure their energy very precisely, but we have to infer the presence of the neutrinos indirectly, through an imbalance of the total energy measured,” says Hamel de Monchenault. By studying the pattern and energy of the leptons and jets, the CMS team deduced the existence of top–antitop pairs and spotted the subtle signature of the fleeting quasi-bound state.

Statistical significance

The CMS researchers observed an excess of events in which the top and antitop quarks were produced almost at rest relative to each other – the precise condition needed for a quasi-bound state to form. “The signal has a statistical significance above 5σ, which means the chance it’s just a statistical fluctuation is less than one in a few million,” Hamel de Monchenault says.

While this excess accounts for only about 1% of top quark pair production, it aligns with predictions for toponium formation and offers insights into the strong force.

“Within the achieved precision, the result matches the predictions of advanced calculations involving the strong force,” explains Hamel de Monchenault. “An effect once thought too subtle to detect with current technology has now been observed. It’s comforting in a way: even the heaviest known quarks are not always alone – they can briefly embrace their opposites.”

Future directions

The discovery has energized the particle physics community. “Scientists are excited to explore the strong force in a completely new regime,” says Schwanenberger. Researchers will refine theoretical models, simulate toponium more precisely, and study its decay patterns and excited states. Much of this work will rely on the High-Luminosity LHC, expected to start operations around 2030, and potentially on future electron–positron colliders capable of studying top quarks with unprecedented precision.

“The present results are based on LHC data recorded between 2015 and 2018 [Run 2]. Since 2022, ATLAS and CMS are recording data at a slightly higher energy, which is favourable for top quark production. The amount of data already surpasses that of Run 2, and we expect that with such huge amounts of data, the properties of this new signal can be studied in detail,” Hamel de Monchenault says.

This research could ultimately answer a fundamental question: is the top quark simply another quark like its lighter siblings, or could it hold the key to physics beyond the Standard Model? “Investigating different toponium states will be a key part of the top quark research programme,” Schwanenberger says. “It could reshape our understanding of matter itself and reveal whatever holds the world together in its inmost folds.”

The results are published in Reports on Progress in Physics.

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It was early in the morning of Monday 14 September 2015, exactly 10 years ago, when gravitational waves created from the collision of two black holes 1.3 billion light-years away hit the LIGO detectors in the US. The detections took place just as the two giant interferometers – one in Washington and the other in Louisiana – were being calibrated before the first observational run was due to begin four days later.

In one of those curious accidents of history, staff on duty at the Louisiana detector had gone to bed a few hours before the waves rolled in. If they hadn’t packed in their calibrations for the night, it would have prevented LIGO from making its historic measurement, dubbed GW150914. Of course, it would surely only have been a matter of time until LIGO had spotted its first signal, with more than 200 gravitational-wave events so far detected.

Observing these “ripples in space–time”, which had long been on many physicists’ bucket lists, has over the last decade become almost routine. Most gravitational-wave detections have been binary black-hole mergers, though there have also been a few neutron-star/black-hole collisions and some binary neutron-star mergers too. Gravitational-wave astronomy is now a well-established field not just thanks to LIGO but also Virgo in Italy and KAGRA in Japan.

In fact, physicists are already planning what would be a third-generation gravitational-wave detector. The Einstein Telescope, which could do in a day what took LIGO a decade, could be open by 2035, with three locations vying to host the facility. The Italian island of Sardinia is one option. Saxony in Germany is another, with the third being a site near where Germany, Belgium and the Netherlands meet.

A decision is expected to be made in two years’ time, but whichever site is picked – and assuming the €2bn construction costs can be found – Europe would be installed firmly at the forefront of gravitational-wave research. That’s because the European Space Agency is also planning a space-based gravitational-wave detector called LISA. It is set to start in 2035 – the same year as the Einstein Telescope.

The US has its own third-generation design, dubbed the Cosmic Explorer. But given the turmoil in US science under Donald Trump, it’s far from certain if it’ll ever be built. However, if other nations step in and build a network of such facilities around the world, as researchers hope, we could well be in for a new golden age for gravitational-wave astronomy. That bucket list just got longer.

The post Celebrating 10 years of gravitational waves appeared first on Physics World.

The isle of Vulcano is a part of the central volcanic ridge of the Aeolian archipelago on the Tyrrhenian Sea in southern Italy. Over the course of its history, Vulcano has undergone multiple explosive eruptions, with the last one thought to have occurred around 1888–1890. However, there is an active hydrothermal system under Vulcano that has shown evidence of intermittent magma and gas flows since 2021 – a sign that the volcano has been in a state of unrest.

During unrest, the volcanic risk increases significantly – and the summer months on the island currently attract a lot of tourists that might be at risk, even from minor eruptive events or episodes of increased degassing. To examine why this unrest has occurred, researchers from the University of Geneva have collaborated with the National Institute of Geophysics and Volcanology (INGV) in Italy to recreate a 3D model of the interior of the volcano on Vulcano, using a combination of nodal seismic networks and artificial intelligence (AI).

Until now, few studies have examined the deep underground details of volcanoes, instead relying on looking at the outline of their internal structure. This is because the geological domains where eruptions nucleate are often inaccessible using airborne geophysical techniques, and onshore studies don’t penetrate far enough into the volcanic plumbing system to look at how the magma and hydrothermal fluids mix. Recent studies have shown the outline of the plumbing systems, but they’ve not had sufficient resolution to distinguish the magma from the hydrothermal system.

3D modelling of the volcano

To better understand what could have caused the 2021 Vulcano unrest, the researchers deployed a nodal network of 196 seismic sensors across Vulcano and Lipari (another island in the archipelago) to measure secondary seismic waves (S-waves) using a technique called seismic ambient noise tomography. S-waves propagate slowly as they pass through fluid-rich zones, which allows magma to be identified.

The researchers captured the S-wave data using the nodal sensor network and processed it with AI – using a deep neural network. This allowed the extensive seismic dispersion data to be quickly and automatically recovered, enabling generation of a 3D S-wave velocity model. The data were captured during the volcano’s early unrest’s phase, and the sensors recorded the natural ground vibrations over a period of one month. The model revealed the high-resolution tomography of the shallow part of a volcanic system in unrest, with the approach compared to taking an “X-ray” of the volcano.

“Our study shows that our end-to-end ambient noise tomography method works with an unprecedented resolution due to using dense nodal seismic networks,” says lead author Douglas Stumpp from the University of Geneva. “The use of deep neural networks allowed us to quickly and accurately measure enormous seismic dispersion data to provide near-real time monitoring.”

The model showed that there was no new magma body between Lipari and Vulcano within the first 2 km of the Earth’s crust, but it did reveal regions that could host cooling melts at the base of the hydrothermal system. These melts were proposed to be degassing melts that could easily release gas and brines if disturbed by an Earthquake – suggesting that tectonic fault dynamics may trigger volcanic unrest. It’s thought that the volcano might have released trapped fluids at depth after being perturbed by fault activity during the 2021 unrest.

Improving risk management

While this method doesn’t enable the researchers to predict when the eruption will happen, it provides a significant understanding into how the internal dynamics of volcanoes work during periods of unrest. The use of AI enables rapid processing of large amounts of data, so in the future, the approach could be used as an early warning system by analysing the behaviour of the volcano as it unfolds.

In theory, this could help to design dynamic evacuation plans based on the direct real-time behaviour of the volcano, which would potentially save lives. The researchers state that this could take some time to develop due to the technical challenge of processing such massive volumes of data in real time – but they note that this is now more feasible thanks to machine learning and deep learning.

When asked about how the researchers plan to further develop the research, Stumpp concludes that “our study paves the ground for 4D ambient noise tomography monitoring – three dimensions of space and one dimension of time. However, I believe permanent and maintained seismic nodal networks with telemetric access to the data need to be implemented to achieve this goal”.

The research is published in Nature Communications.

The post Researchers map the unrest in the Vulcano volcano appeared first on Physics World.

A new high-speed multifocus microscope could facilitate discoveries in developmental biology and neuroscience thanks to its ability to image rapid biological processes over the entire volume of tiny living organisms in real time.

The pictures from many 3D microscopes are obtained sequentially by scanning through different depths, making them too slow for accurate live imaging of fast-moving natural functions in individual cells and microscopic animals. Even current multifocus microscopes that capture 3D images simultaneously have either relatively poor image resolution or can only image to shallow depths.

In contrast, the new 25-camera “M25” microscope – developed during his doctorate by Eduardo Hirata-Miyasaki and his supervisor Sara Abrahamsson, both then at the University of California Santa Cruz, together with collaborators at the Marine Biological Laboratory in Massachusetts and the New Jersey Institute of Technology – enables high-resolution 3D imaging over a large field-of-view, with each camera capturing 180 × 180 × 50 µm volumes at a rate of 100 per second.

“Because the M25 microscope is geared towards advancing biomedical imaging we wanted to push the boundaries for speed, high resolution and looking at large volumes with a high signal-to-noise ratio,” says Hirata-Miyasaki, who is now based in the Chan Zuckerberg Biohub in San Francisco.

The M25, detailed in Optica, builds on previous diffractive-based multifocus microscopy work by Abrahamsson, explains Hirata-Miyasaki. In order to capture multiple focal planes simultaneously, the researchers devised a multifocus grating (MFG) for the M25. This diffraction grating splits the image beam coming from the microscope into a 5 × 5 grid of evenly illuminated 2D focal planes, each of which is recorded on one of the 25 synchronized machine vision cameras, such that every camera in the array captures a 3D volume focused on a different depth. To avoid blurred images, a custom-designed blazed grating in front of each camera lens corrects for the chromatic dispersion (which spreads out light of different wavelengths) introduced by the MFG.

The team used computer simulations to reveal the optimal designs for the diffractive optics, before creating them at the University of California Santa Barbara nanofabrication facility by etching nanometre-scale patterns into glass. To encourage widespread use of the M25, the researchers have published the fabrication recipes for their diffraction gratings and made the bespoke software for acquiring the microscope images open source. In addition, the M25 mounts to the side port of a standard microscope, and uses off-the-shelf cameras and camera lenses.

The M25 can image a range of biological systems, since it can be used for fluorescence microscopy – in which fluorescent dyes or proteins are used to tag structures or processes within cells – and can also work in transmission mode, in which light is shone through transparent samples. The latter allows small organisms like C. elegans larvae, which are commonly used for biological research, to be studied without disrupting them.

The researchers performed various imaging tests using the prototype M25, including observations of the natural swimming motion of entire C. elegans larvae. This ability to study cellular-level behaviour in microscopic organisms over their whole volume may pave the way for more detailed investigations into how the nervous system of C. elegans controls its movement, and how genetic mutations, diseases or medicinal drugs affect that behaviour, Hirata-Miyasaki tells Physics World. He adds that such studies could further our understanding of human neurodegenerative and neuromuscular diseases.

“We live in a 3D world that is also very dynamic. So with this microscope I really hope that we can keep pushing the boundaries of acquiring live volumetric information from small biological organisms, so that we can capture interactions between them and also [see] what is happening inside cells to help us understand the biology,” he continues.

As part of his work at the Chan Zuckerberg Biohub, Hirata-Miyasaki is now developing deep-learning models for analysing dynamic cell and organism multichannel dynamic live datasets, like those acquired by the M25, “so that we can extract as much information as possible and learn from their dynamics”.

Meanwhile Abrahamsson, who is currently working in industry, hopes that other microscopy development labs will make their own M25 systems.  She is also considering commercializing the instrument to help ensure its widespread use.

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This episode of the Physics World Weekly podcast features Scott Bolton, who is principal investigator on NASA’s Juno mission to Jupiter. Launched in 2011, the mission has delivered important insights into the nature of the gas-giant planet. In this conversation with Physics World’s Margaret Harris, Bolton explains how Juno continues to change our understanding of Jupiter and other gas giants.

Bolton and Harris chat about the mission’s JunoCam, which has produced some gorgeous images of Jupiter and it moons.

Although the Juno mission was expected to last only a few years, the spacecraft is still going strong despite operating in Jupiter’s intense radiation belts. Bolton explains how the Juno team has rejuvenated radiation-damaged components, which has provided important insights for those designing future missions to space.

However Juno’s future is uncertain. Despite its great success, the mission is currently scheduled to end at the end of September, which is something that Bolton also addresses in the conversation.

The post Juno: the spacecraft that is revolutionizing our understanding of Jupiter appeared first on Physics World.

A combination of static proton arcs and shoot-through proton beams could increase plan conformity and homogeneity and reduce delivery times in upright proton therapy, according to new research from RaySearch Laboratories in Sweden.

Proton arc therapy (PAT) is an emerging rotational delivery technique with potential to improve plan quality – reducing dose to organs-at-risk while maintaining target dose. The first clinical PAT treatments employed static arcs, in which multiple energy layers are delivered from many (typically 10 to 30) discrete angles. Importantly, static arc PAT can be delivered on conventional proton therapy machines. It also offers simpler beam arrangements than intensity-modulated proton therapy (IMPT).

“In IMPT of head-and-neck cancers, the beam directions are normally set up in a complicated pattern in different planes, with range shifters needed to treat the shallow part of the tumour,” explains Erik Engwall, chief physicist at RaySearch Laboratories. “In PAT, the many beam directions are arranged in the same plane and no range shifters are typically needed. With all beams in the same plane, it is easier to move to upright treatments.”

Upright proton therapy involves rotating the patient (in an upright position) in front of a static horizontal treatment beam. The approach could reduce costs by using compact proton delivery systems. This compactness, however, places energy selection close to the patient, increasing scattering in the proton beam. To combat this, the team propose adding a layer of shoot-through protons to each direction of the proton arc.

The idea is that while most protons are delivered with Bragg peaks placed in the target, the sharp penumbra of the high-energy protons shooting through the target will combat beam broadening. The rotational delivery in the proton arc spreads the exit dose from these shoot-through beams over many angles, minimizing dose to surrounding tissues. And as the beamline is fixed, shoot-through protons exit in the same direction (behind the patient) for all angles, simplifying shielding to a single beam dump opposite the fixed beam.

Simulation studies

To test this approach, Engwall and colleagues simulated treatment plans for a virtual phantom containing three targets and an organ-at-risk, reporting their findings in Medical Physics. They used a development version of RayStation v2025 with a beam model of the Mevion s250-FIT system (which combines a compact cyclotron, an upright positioner and an in-room CT scanner).

For each target, the team created static arc plans with (Arc+ST) and without shoot-through beams and with/without collimation, as well as 3-beam IMPT plans with and without shoot-through beams (all with collimation). Arc plans used 20 uniformly spaced beam directions, and the shoot-through plans included an additional layer of the highest system energy (230 MeV) for each direction.

For all targets, Arc+ST plans showed superior conformity, homogeneity and target robustness to arc plans without shoot-through protons. Adding collimation slightly improved the arc plans without shoot-through protons but had little impact on Arc+ST plans.

The IMPT plans achieved similar homogeneity and robustness to the best arc plans, but with far lower conformity due to the shoot-through protons delivering a concentrated exit dose behind the target (while static arcs distribute this dose over many directions). Adding shoot-through protons improved IMPT plan quality, but to a lesser degree than for PAT plans.

Clinical case

The researchers repeated their analysis for a clinical head-and-neck cancer case, comparing static arcs with 5-beam IMPT. Again, Arc+ST plans performed better than any others for almost all metrics. “The Arc+ST plans have the best quality due to the sharpening of the penumbra of the shoot-through part, even better than when using a collimator,” says Engwall.

Notably, the findings suggest that collimation is not needed when combining arcs with shoot-through beams, enabling rapid treatments. With fast energy switching and the patient rotation at 1 rpm, Arc+ST achieved an estimated delivery time of less than 5.4 min – faster than all other plans for this case, including 5-beam IMPT.

“Treatment time is reduced when the leaves of the dynamic collimator do not need to move,” Engwall explains. “There is also no risk of mechanical failures of the collimator and the secondary neutron production will be lower when there are fewer objects in the beamline.”

Another benefit of upright delivery is that the shoot-through protons can be used for range verification during treatments, using a detector integrated into the beam dump behind the patient. The team investigated this concept with three simulated error scenarios: 5% systematic shift in stopping power ratio; 5 mm setup shift; and 2 cm shoulder movement. The technique successfully detected all errors.

As the range detector is permanently installed in the treatment room and the shoot-through protons are part of the treatment plan, this method does not add time to the patient setup and can be used in every treatment fraction to detect both intra- and inter-fraction uncertainties.

Although this is a proof-of-concept study, the researchers conclude that it highlights the combined advantages of the new treatment technique, which could “leverage the potential of compact upright proton treatments and make proton treatments more affordable and accessible to a larger patient group”.

Engwall tells Physics World that the team is now collaborating with several clinical research partners to investigate the technique’s potential across larger patient data sets, for other treatment sites and multiple treatment machines.

The post Optimizing upright proton therapy: hybrid delivery provides faster, sharper treatments appeared first on Physics World.

A machine learning-based approach that could help astronomers detect lower-frequency gravitational waves has been unveiled by researchers in the UK, US, and Italy. Dubbed deep loop shaping, the system would apply real-time corrections to the mirrors used in gravitational wave interferometers. This would dramatically reduce noise in the system, and could lead to a new wave of discoveries of black hole and neutron star mergers – according to the team.

In 2015, the two LIGO interferometers made the very first observation of a gravitational wave: attributing its origin to a merger of two black holes that were roughly 1.3 billion light–years from Earth.

Since then numerous gravitational waves have been observed with frequencies ranging from 30–2000 Hz. These are believed to be from the mergers of small black holes and neutron stars.

So far, however, the lower reaches of the gravitational wave frequency spectrum (corresponding to much larger black holes) have gone largely unexplored. Being able to detect gravitational waves at 10–30 Hz would allow us to observe the mergers of intermediate-mass black holes at 100–100,000 solar masses. We could also measure the eccentricities of binary black hole orbits. However, these detections are not currently possible because of vibrational noise in the mirrors at the end of each interferometer arm.

Subatomic precision

“As gravitational waves pass through LIGO’s two 4-km arms, they warp the space between them, changing the distance between the mirrors at either end,” explains Rana Adhikari at Caltech, who is part of the team that has developed the machine-learning technique. “These tiny differences in length need to be measured to an accuracy of 10^-19 m, which is 1/10,000^th the size of a proton. [Vibrational] noise has limited LIGO for decades.”

To minimize noise today, these mirrors are suspended by a multi-stage pendulum system to suppress seismic disturbances. The mirrors are also polished and coated to eliminate surface imperfections almost entirely. On top of this, a feedback control system corrects for many of the remaining vibrations and imperfections in the mirrors.

Yet for lower-frequency gravitational waves, even this subatomic level of precision and correction is not enough. As a laser beam impacts a mirror, the mirror can absorb minute amounts of energy – creating tiny thermal distortions that complicate mirror alignment. In addition, radiation pressure from the laser, combined with seismic motions that are not fully eliminated by the pendulum system, can introduce unwanted vibrations in the mirror.

The team proposed that this problem could finally be addressed with the help of artificial intelligence (AI). “Deep loop shaping is a new AI method that helps us to design and improve control systems, with less need for deep expertise in control engineering,” describes Jonas Buchli at Google DeepMind, who led the research. “While this is helping us to improve control over high precision devices, it can also be applied to many different control problems.”

Deep reinforcement learning

The team’s approach is based on deep reinforcement learning, whereby a system tests small adjustments to its controls and adapts its strategy over time through a feedback system of rewards and penalties.

With deep loop shaping, the team introduced smarter feedback controls for the pendulum system suspending the interferometer’s mirrors. This system can adapt in real time to keep the mirrors aligned with minimal control noise – counteracting thermal distortions, seismic vibrations, and forces induced by radiation pressure.

“We tested our controllers repeatedly on the LIGO system in Livingston, Louisiana,” Buchli continues. “We found that they worked as well on hardware as in simulation, confirming that our controller keeps the observatory’s system stable over prolonged periods.”

Based on these promising results, the team is now hopeful that deep loop shaping could help to boost the cosmological reach of LIGO and other existing detectors, along with future generations of gravitational-wave interferometers.

“We are opening a new frequency band, and we might see a different universe much like the different electromagnetic bands like radio, light, and X-rays tell complementary stories about the universe,” says team member Jan Harms at the Gran Sasso Science Institute in Italy. “We would gain the ability to observe larger black holes, and to provide early warnings for neutron star mergers. This would allow us to tell other astronomers where to point their telescopes before the explosion occurs.”

The research is described in Science.

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A decade ago, on 14 September 2015, the twin detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO) in Hanford, Washington, and Livingston, Louisiana, finally detected a gravitational wave. The LIGO detectors – two L-shaped laser interferometers with 4 km-long arms – had measured tiny differences in laser beams bouncing off mirrors at the end of each arm. The variations in the length of the arms, caused by the presence of a gravitational wave, were converted into the now famous audible “chirp signal”, which indicated the final approach between two merging black holes.

Since that historic detection, which led to the 2017 Nobel Prize for Physics, the LIGO detectors, together with VIRGO in Italy, have measured several hundred gravitational waves – from mergers of black holes to neutron-star collisions. More recently, they have been joined by the KAGRA detector in Japan, which is located some 200 m underground, shielding it from vibrations and environmental noise.

Yet the current number of gravitational waves could be dwarfed by what the planned Einstein Telescope (ET) would measure. This European-led, third-generation gravitational-wave detector would be built several hundred metres underground and be at least 10 times more sensitive than its second-generation counterparts including KAGRA. Capable of “listening” to a thousand times larger volume of the universe, the new detector would be able to spot many more sources of gravitational waves. In fact, the ET will be able to gather in a day what it took LIGO and VIRGO a decade to collect.

The ET is designed to operate in two frequency domains. The low-frequency regime – 2–40 Hz – is below current detectors’ capabilities and will let the ET pick up waves from more massive black holes. The high-frequency domain, on the other hand, would operate from 40 Hz to 10 kHz  and detect a wide variety of astrophysical sources, including merging black holes and other high-energy events. The detected signals from waves would also be much longer with the ET, lasting for hours. This would allow physicists to “tune in” much earlier as black holes or neutron stars approach each other.

Location, location, location

But all that is still a pipe dream, because the ET, which has a price tag of €2bn, is not yet fully funded and is unlikely to be ready until 2035 at the earliest. The precise costs will depend on the final location of the experiment, which is still up for grabs.

Three regions are vying to host the facility: the Italian island of Sardinia, the Belgian-German-Dutch border region and the German state of Saxony. Each candidate is currently investigating the suitability of its preferred site (see box below), the results of which will be published in a “bid book” by the end of 2026. The winning site will be picked in 2027 with construction beginning shortly after.

Other factors that will dictate where the ET is built include logistics in the host region, the presence of companies and research institutes (to build and exploit the facility) and government support. With the ET offering high-quality jobs, economic return, scientific appeal and prestige, that could give the German-Belgian-Dutch candidacy the edge given the three nations could share the cost.

Another major factor is the design of the ET. One proposal is to build it as an equilateral triangle with each side being 10 km. The other is a twin L-shaped design where both arms are 15 km long and each detector located far from each other. The latter design is similar to the two LIGO over-ground detectors, which are 3000 km apart. If the “2L design” is chosen, the detector would then be built at two of the three competing sites.

The 2L design is being investigated by all three sites, but those behind the Sardinia proposal strongly favour this approach. “With the detectors properly oriented relative to each other, this design could outperform the triangular design across all key scientific objectives,” claims Domenico D’Urso, scientific director of the Italian candidacy. He points to a study by the ET collaboration in 2023 that investigated the impact of the ET design on its scientific goals. “The 2L design enables, for example, more precise localization of gravitational wave sources, enhancing sky-position reconstruction,” he says. “And it provides superior overall sensitivity.”

Localization is important for multi­messenger astronomy. In other words, if a gravitational-wave source can be located quickly and precisely in the sky, other telescopes can be pointed towards it to observe any eventual light or other electromagnetic (EM) signals. This is what happened after LIGO detected a gravitational wave on 17 August 2017, originating from a neutron star collision. Dozens of ground- and space-based satellites were able to pick up a gamma-ray burst and the subsequent EM afterglow.

The triangle design, however, is favoured by the Belgian-German-Dutch consortium. It would be the Earth equivalent to the European Space Agency’s planned LISA space-based gravitational-waves detector, which will consist of three spacecraft in a triangle configuration that is set for launch in 2035, the same year that the ET could open. LISA would detect gravitational waves with even much lower frequency, coming, for example, from mergers of supermassive black holes.

While the Earth-based triangle design would not be able to locate the source as precisely, it would – unlike the 2L design – be able to do “null stream” measurements. These would yield  a clearer picture of the noise from the environment and the detector itself, including  “glitches”, which are bursts of noise that overlap with gravitational-wave signals. “With a non-stop influx of gravitational waves but also of noise and glitches, we need some form of automatic clean-up of the data,” says Jan Harms, a physicist at the Gran Sasso Science Institute in Italy and member of the scientific ET collaboration. “The null stream could provide that.”

However, it is not clear if that null stream would be a fundamental advantage for data analysis, with Harms and colleagues thinking more work is needed. “For example, different forms of noise could be connected to each other, which would compromise the null stream,” he says. The problem is also that a detector with a null stream has not yet been realized. And that applies to the triangle design in general. “While the 2L design is well established in the scientific community,” adds D’Urso.

Backers of the triangle design see the ET as being part of a wider, global network of third-generation detectors, where the localization argument no longer matters. Indeed, the US already has plans for an above-ground successor to LIGO. Known as the Cosmic Explorer, it would feature two L-shaped detectors with arm lengths of up to 40 km. But with US politics in turmoil, it is questionable how realistic these plans are.

Matthew Evans, a physicist at the Massachusetts Institute of Technology and member of the LIGO collaboration, recognizes the “network argument”. “I think that the global gravitational waves community are double counting in some sense,” he says. Yet for Evans it is all about the exciting discoveries that could be made with a next-generation gravitational-wave detector. “The best science will be done with ET as 2Ls,” he says.

The post Physicists set to decide location for next-generation Einstein Telescope appeared first on Physics World.

Studying the chain of processes that take place when UV or x-ray radiation interacts with solid matter is crucial in various fields from medical physics to materials testing.

The first of these processes is typically photoionisation, where an atom or molecule absorbs a photon and loses one or more electrons as a result.

What comes next can vary depending on the strength of the radiation and the nature of the material, but some of the most important effects are secondary ionisation processes. These often go on to dominate the dynamics of the whole system.

One of these is interatomic Coulombic decay (ICD), in which energy is transferred from one excited atom or molecule to a neighbouring one, which in turn is ionised.

ICD has captured considerable interest since its discovery, not least because it often produces low energy electrons which cause radiation damage in biological matter.

Understanding this phenomenon better was the team’s goal in this latest work. Using the ASTRID2 synchrotron in Aarhus, Denmark, they studied what happened when extreme UV photons interacted with small clusters of helium atoms.

To capture what was going on they used an electron velocity-map imaging spectrometer. This is a powerful diagnostic that measures any emitted electrons’ energy in addition to their angular distribution.

Using this technique, they were able to show that the ICD process is even more efficient than previously thought. The researchers expect it to play a crucial role in other condensed phase systems exposed to ionising radiation as well.

Knowledge gained from studies such as this one is crucial for fields like radiation therapy, where the effects of ionising radiation on human cells must be tightly controlled.

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Wireless power transfer (WPT) is increasingly used in consumer electronics, electric vehicles, and medical devices, with technologies like inductive charging and resonant coupling leading the way.

The key to successful WPT technologies is ensuring that a high percentage of the input power is transferred to its intended destination – i.e. it must be efficient.

The idea of parity-time (PT) symmetry helps achieve this goal by offering a way to balance energy gain and loss in a system, which helps maintain stable and efficient power flow – even in the presence of disturbances.

Here parity means spatial reflection (like flipping left and right), and time refers to reversing the direction of time. A PT-symmetric system behaves the same when both of these transformations are applied together.

However, this method has its limitations. It often requires very fine-tuning, it can struggle when devices do not function as idealised resistors,. Most importantly, it falls short of achieving the theoretical maximum efficiency of WPT.

This is where the new paper comes in. They’ve performed a comprehensive experimental and theoretical study demonstrating that dispersive gain can greatly enhance the efficiency of WPT beyond the limits of previous methods.

Dispersive gain describes a type of energy amplification in a system where the gain depends on the frequency of the signal. This means the system amplifies energy differently at different frequencies, rather than uniformly across all frequencies.

This allows the system to naturally shift energy into the most efficient frequency modes for transfer.

Their work could be used to enable new technologies or make existing ones more affordable. It could also open up new possibilities for harnessing dispersion effects across electronics and optics.

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A new transition-metal oxide crystal that reversibly and repeatedly absorbs and releases oxygen could be ideal for use in fuel cells and as the active medium in clean energy technologies such as thermal transistors, smart windows and new types of batteries. The “breathing” crystal, discovered by scientists at Pusan National University in Korea and Hokkaido University in Japan, is made from strontium, cobalt and iron and contains oxygen vacancies.

Transition-metal oxides boast a huge range of electrical properties that can be tuned all the way from insulating to superconducting. This means they can find applications in areas as diverse as energy storage, catalysis and electronic devices.

Among the different material parameters that can be tuned are the oxygen vacancies. Indeed, ordering these vacancies can produce new structural phases that show much promise for oxygen-driven programmable devices.

Element-specific behaviours

In the new work, a team of researchers led by physicist Hyoungjeen Jeen of Pusan and materials scientist Hiromichi Ohta in Hokkaido studied SrFe_0.5Co_0.5O_x. The researchers focused on this material, they say, since it belongs to the family of topotactic oxides, which are the main oxides being studied today in solid-state ionics. “However, previous work had not discussed which ion in this compound was catalytically active,” explains Jeen. “What is more, the cobalt-containing topotactic oxides studied so far were fragile and easily fractured during chemical reactions.”

The team succeeded in creating a unique platform from a solid solution of epitaxial SrFe_0.5Co_0.5O_2.5 in which both the cobalt and iron ions bathed in the same chemical environment. “In this way, we were able to test which ion was better for reduction reactions and whether or not it sustained its structural integrity,” Jeen tells Physics World. “We found that our material showed element-specific reduction behaviours and reversible redox reactions.”

The researchers made their material using a pulsed laser deposition technique, ideal for the epitaxial synthesis of multi-element oxides that allowed them to grow SrFe_0.5Co_0.5O_2.5 crystals in which the iron and cobalt ions were randomly located in the crystal. This random arrangement was key to the material’s ability to repeatedly release and absorb oxygen, they say.

“It’s like giving the crystal ‘lungs’ so that it can inhale and exhale oxygen on command,” says Jeen.

Stable and repeatable

This simple breathing picture comes from the difference in the catalytic activity of cobalt and iron in the compound, he explains. Cobalt ions prefer to lose and gain oxygen and these ions are the main sites for the redox activity. However, since iron ions prefer not to lose oxygen during the reduction reaction, they serve as pillars in this architecture. This allows for stable and repeatable oxygen release and uptake.

Until now, most materials that absorb and release oxygen in such a controlled fashion were either too fragile or only functioned at extremely high temperatures. The new material works under more ambient conditions and is stable. “This finding is striking in two ways: only cobalt ions are reduced, and the process leads to the formation of an entirely new and stable crystal structure,” explains Jeen.

The researchers also showed that the material could return to its original form when oxygen was reintroduced, so proving that the process is fully reversible. “This is a major step towards the realization of smart materials that can adjust themselves in real time,” says Ohta. “The potential applications include developing a cathode for intermediate solid oxide fuel cells, an active medium for thermal transistors (devices that can direct heat like electrical switches), smart windows that adjust their heat flow depending on the weather and even new types of batteries.”

Looking ahead, Jeen, Ohta and colleagues aim to investigate the material’s potential for practical applications.

They report their present work in Nature Communications.

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Optical fibres form the backbone of the Internet, carrying light signals across the globe. But some light is always lost as it travels, becoming attenuated by about 0.14 decibels per kilometre even in the best fibres. That means signals must be amplified every few dozen kilometres – a performance that hasn’t improved in nearly four decades.

Physicists at the University of Southampton, UK have now developed an alternative that could call time on that decades-long lull. Writing in Nature Photonics, they report hollow-core fibres that exhibit 35% less attenuation while transmitting signals 45% faster than standard glass fibres.

“A bit like a soap bubble”

The core of conventional fibres is made of pure glass and is surrounded by a cladding of slightly different glass. Because the core has a higher refractive index than the cladding, light entering the fibre reflects internally, bouncing back and forth in a process known as total internal reflection. This effect traps the light and guides it along the fibre’s length.

The Southampton team led by Francesco Poletti swapped the standard glass core for air. Because air is more transparent than glass, channelling light through it cuts down on scattering and speeds up signals. The problem is that air’s refractive index is lower, so the new fibre can’t use total internal reflection. Instead, Poletti and colleagues guided the light using a mechanism called anti-resonance, which requires the walls of the hollow core to be made from ultra-thin glass membranes.

“It’s a bit like a soap bubble,” Poletti says, explaining that such bubbles appear iridescent because their thin films reflect some wavelengths and lets others through. “We designed our fibre the same way, with glass membranes that reflect light at certain frequencies back into the core.” That anti-resonant reflection, he adds, keeps the light trapped and moving through the fibre’s hollow centre.

Greener telecommunications

To make the new air-core fibre, the researchers stacked thin glass capillaries in a precise pattern, forming a hollow channel in the middle. Heating and drawing the stack into a hair-thin filament preserved this pattern on a microscopic scale. The finished fibre has a nested design: an air core surrounded by ultra-thin layers that provide anti-resonant guidance and cut down on leakage.

To test their design, the team measured transmission through a full spool of fibre, then cut the fibre shorter and compared the results. They also fired in light pulses and tracked the echoes. Their results show that the hollow fibres reduce attenuation to just 0.091 decibels per kilometre. This lower loss implies that fewer amplifiers would be needed in long cables, lowering costs and energy use. “There’s big potential for greener telecommunications when using our fibres,” says Poletti.

Poletti adds that reduced attenuation (and thus lower energy use) is only one of the new fibre’s advantages. At the 0.14 dB/km attenuation benchmark, the new hollow fibre supports a bandwidth of 54 THz compared to 10 THz for a normal fibre. At the reduced 0.1 dB/km attenuation, the bandwidth is still 18 THz, which is close to twice that of a normal cable. This means that a single strand can carry far more channels at once.

Perhaps the most impressive advantage is that because the speed of light is faster in air than in glass, data could travel the same distance up to 45% faster. “It’s almost the same speed light takes when we look at a distant star,” Poletti says. The resulting drop in latency, he adds, could be crucial for real-time services like online gaming or remote surgery, and could also speed up computing tasks such as training large language models.

Field testing

As well as the team’s laboratory tests, Microsoft has begun testing the fibres in real systems, installing segments in its network and sending live traffic through them. These trials prove the hollow-core design works with existing telecom equipment, opening the door to gradual rollout. In the longer run, adapting amplifiers and other gear that are currently tuned for solid glass fibres could unlock even better performance.

Poletti believes the team’s new fibres could one day replace existing undersea cables. “I’ve been working on this technology for more than 20 years,” he says, adding that over that time, scepticism has given way to momentum, especially now with Microsoft as an industry partner. But scaling up remains a real hurdle. Making short, flawless samples is one thing; mass-producing thousands of kilometres at low cost is another. The Southampton team is now refining the design and pushing toward large-scale manufacturing. They’re hopeful that improvements could slash losses by another order of magnitude and that the anti-resonant design can be tuned to different frequency bands, including those suited to new, more efficient amplifiers.

Other experts agree the advance marks a turning point. “The work builds on decades of effort to understand and perfect hollow-core fibres,” says John Ballato, whose group at Clemson University in the US develops fibres with specialty cores for high-energy laser and biomedical applications. While Ballato notes that such fibres have been used commercially in shorter-distance communications “for some years now”, he believes this work will open them up to long-haul networks.

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The concept of cause and effect plays an important role in both our everyday lives, and in physics. If you set a ball down in front of a window and kick it hard, a split-second later the ball will hit the window and smash it. What we don’t observe is a world where the window smashes on its own, thereby causing the ball to be kicked – that would seem rather nonsensical. In other words, kick before smash, and smash before kick, are two different physical processes each having a unique and definite causal order.

But, does definite causal order also reign supreme in the quantum world, where concepts like position and time can be fuzzy?  Most physicists are happy to accept the paradox of Schrödinger’s cat – a thought experiment in which a cat hidden in a box is simultaneously dead and alive at the same time, until you open the box to check. Schrödinger’s cat illustrates the quantum concept of “superposition”, whereby a system can be in two or more states at the same time. It is only when a measurement is made (by opening the box), does the system collapse into one of its possible states.

But could two (or more) causally distinct processes occur at the same time in the quantum world? The answer, perhaps shockingly, is yes and this paradoxical phenomenon is called indefinite causal order (ICO).

Stellar superpositions and the order of time

It turns out that different causal processes can also exist in a superposition. One example is a thought experiment called the “gravitational quantum switch”, which was proposed in 2019 by Magdalena Zych of the University of Queensland and colleagues (Nat. Comms 10 3772). This features our favourite quantum observers Alice and Bob, who are in the vicinity of a very large mass, such as a star. Alice and Bob both have initially synchronized clocks and in the quantum world, these clocks would continue to run at identical rates. However, Einstein’s general theory of relativity dictates that the flow of time is influenced by the distribution of matter in the vicinity of Alice and Bob. This means that if Alice is closer to the star than Bob, then her clock will run slower than Bob’s, and vice versa.

Like with Schrödinger’s cat, quantum mechanics allows the star to be in a superposition of spatial states; meaning that in one state Alice is closer to the star than Bob, and in the other Bob is closer to the star than Alice. In other words, this is a superposition of a state in which Alice’s clock runs slower than Bob’s, and a state in which Bob’s clock runs slower than Alice’s.

Alice and Bob are both told they will receive a message at a specific time (say noon) and that they would then pass that message on to the their counterpart. If Alice’s clock is running faster than Bob’s then she will receive the message first, and then pass it on to Bob, and vice versa. This superposition of Alice to Bob with Bob to Alice is an example of indefinite causal order.

Now, you might be thinking “so what” because this seems to be a trivial example. But it becomes more interesting if you replace the message with a quantum particle like a photon; and have Alice and Bob perform different operations on that photon. If the two operations do not commute – such as rotations of the photon polarization in the X and Z planes – then the order in which the operations are done will affect the outcome.

As a result, this “gravitational quantum switch” is a superposition of two different causal processes with two different outcomes. This means that Alice and Bob could do more exotic operations on the photon, such as “measure-and-reprepare” operations (where a quantum system is first measured, and then, based on the measurement outcome, a new quantum state is prepared). In this case Alice measures the quantum state of the received photon and prepares a photon that she sends to Bob (or vice versa).

Much like Schrödinger’s cat, a gravitational quantum switch cannot currently be realized in the lab. But, never say never. Physicists have been able to create experimental analogues of some thought experiments, so who knows what the future will bring. Indeed, a gravitational quantum switch could provide important information regarding a quantum description of gravity – something that has eluded physicists ever since quantum mechanics and general relativity were being developed in the early 20^th century.

Switches and superpositions

Moving on to more practical ICO experiments, physicists have already built and tested light-based quantum switches in the lab. Instead of having the position of the star determining whether Alice or Bob go first, the causal order is determined by a two-level quantum state – which can have a value of 0 or 1. If this control state is 0, then Alice goes first and if the control state is 1, then Bob goes first. Crucially, when the control state is in a superposition of 0 and 1 the system shows indefinite causal order (see figure 1).

1 Simultaneous paths

In this illustration of a quantum switch a photon (driving a car) can follow two different paths, each with a different causal order. One path (top) leads to Alice’s garage followed by a visit to Bob’s drive thru. The second path (middle) visits Bob first, and then Alice. The path taken by the photon is determined by a control qubit that is represented by a traffic light. If the value of the qubit is “0” then the photon visits Alice First; if the qubit is “1” then the photon visits Bob first. Both of these scenarios have definite causal order.

However, the control qubit can exist in a quantum superposition of “0” and “1” (bottom). In this superposition, the path followed by the photon – and therefore the temporal order in which it visits Alice and Bob – is not defined. This is an example of indefinite causal order. Of course, any attempt to identify exactly which path the photon goes through initially will destroy the superposition (and therefore the ICO) and the photon will take only one definite path.

The first such quantum switch was created by in 2015 by Lorenzo Procopio (now at Germany’s University of Paderborn) and colleagues at the Vienna Center for Quantum Science and Technology (Nat. Comms 6, 7913). Their quantum switch involves firing a photon at a beam splitter, which puts the photon into a superposition of a photon that has travelled straight through the splitter (state 0) and a photon that has been deflected by 90 degrees (state 1). This spatial superposition is the control state of the quantum switch, playing the role of the star in the gravitational quantum switch.

State 0 photons first travel to an Alice apparatus where a polarization rotation is done in a specific direction (say X). Then the photons are sent to a Bob apparatus where a non-commuting rotation (say Z) is done. Conversely, the photons that travel along the state 1 path encounter Bob before Alice.

Finally, the state 0 and state 1 paths are recombined at a second beamsplitter, which is monitored by two photon-detectors. Because Alice-then-Bob has a different effect on a photon than does Bob-then-Alice, interference can occur between recombined photons. This interference is studied by systematically changing certain aspects of the experiment. For example, by changing Alice’s direction of rotation or the polarization of the incoming photons.

In 2017 quantum-information researcher Giulia Rubino, then at the Vienna Center for Quantum Science and Technology, teamed up with Procopia and colleagues to verify ICO in their quantum switch using a “causal witness” (Sci. Adv. 3 e1602589). This involves doing a specific set of experiments on the quantum switch and calculating a mathematical entity (the causal witness) that reveals whether a system has definite or indefinite causal order. Sure enough, this test revealed that their system does indeed have ICO. Since then, physicists working in several independent labs have successfully created their own quantum switches.

Computational speed up?

While this effect might still seem somewhat obscure, in 2019, an international team led by the renowned Chinese physicist Jian-Wei Pan showed that a quantum switch can be very useful for doing computations that are distributed between two parties (Phys. Rev. Lett. 122 120504). In such a scenario a string of data is received and then processed by Alice, who then passes the results on to Bob for further processing. In an experiment using photons, they showed that ICO delivers an exponential speed-up of the rate at which longer strings are processed – compared to a system with no ICO.

Physicists are also exploring if ICO could be used to enhance quantum metrology. Indeed, recent calculations by Oxford University’s Giulio Chiribella and colleagues suggest that it could lead to a significant increase in precision when compared to techniques that involve states with definite causal order (Phys. Rev. Lett. 124 190503).

While other applications could be possible, it is often difficult to work out whether ICO offers the best solution to a specific problem. For example, physicists had thought a quantum switch offered an advantage when it comes to communicating along a noisy channel, but it turns out that some configurations of Alice and Bob with definite causal order were just as good as an ICO.

Beyond the quantum switch, there are other types of circuits that would display ICO. These include “quantum circuits with quantum control of causal order”, which have yet to be implemented in the lab because of their complexity.

But despite the challenges in creating ICO systems and proving that they outperform other solutions, it looks like ICO is set to join ranks of other weird phenomena such as superposition and entanglement that have found practical applications in quantum technologies.

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The first-ever detection of gravitational waves was made by LIGO in 2015 and since then researchers have been trying to understand the physics of the black-hole and neutron-star mergers that create the waves. However, the physics is very complicated and is defined by Albert Einstein’s general theory of relativity.

Now Jiaxi Wu, Siddharth Boyeneni and Elias Most at the California Institute of Technology (Caltech) have addressed this challenge by developing a new formulation of general relativity that is inspired by the equations that describe electromagnetic interactions. They show that general relativity behaves in the same way as the gravitational inverse square law described by Isaac Newton more than 300 years ago. “This is a very non-trivial insight,” says Most.

One of the fascinations of black holes is the extreme physics they invoke. These astronomical objects  pack so much mass into so little space that not even light can escape their gravitational pull. Black holes (and neutron stars) can exist in binary systems in which the objects orbit each other. These pairs eventually merge to create single black holes in events that create detectable gravitational waves. The study of these waves provides an important testbed for gravitational physics. However, the mathematics of general relativity that describe these mergers is very complicated.

Inverse square law

According to Newtonian physics, the gravitational attraction between two masses is proportional to the inverse of the square of the distance between them – the inverse square law. However, as Most points out, “Unless in special cases, general relativity was not thought to act in the same way.”

Over the past decade, gravitational-wave researchers have taken various approaches including post-Newtonian theory and effective one-body approaches to better understand the physics of black-hole mergers. One important challenge is how to model parameters such as orbital eccentricity and precession in black hole systems and how best to understand “ringdown”. The latter is the process whereby a black hole formed by a merger emits gravitational waves as it relaxes into a stable state.

The trio’s recasting of the equations of general relativity was inspired by the Maxwell equations that describe how electric and magnetic fields leapfrog each other through space. According to these equations, the forces between electric charges diminish according to the same inverse square law as Newton’s gravitational attraction.

Early reformulations

The original reformulations of “gravitoelectromagnetism” date back to the 90s. Most explains how among those who did this early work was his Caltech colleague and LIGO Nobel laureate Kip Thorne, who exploited a special mathematical structure of the curvature of space–time.

“This structure mathematically looks like the equations governing light and the attraction of electric charges, but the physics is quite different,” Most tells Physics World. The gravito-electric field thus derived describes how an object might squish under the forces of gravity. “Mathematically this means that the previous gravito-electric field falls off with inverse distance cubed, which is unlike the inverse distance square law of Newtonian gravity or electrostatic attraction,” adds Most.

Most’s own work follows on from previous studies of the potential radio emission from the interaction of magnetic fields during the collision of neutron stars and black holes from which it seemed reasonable to then “think about whether some of these insights naturally carry over to Einstein’s theory of gravity”. The trio began with different formulations of general relativity and electromagnetism with the aim of deriving gravitational analogues for the electric and magnetic fields that behave more closely to classical theories of electromagnetism. They then demonstrated how their formulation might describe the behaviour of a non-rotating Schwarzschild black hole, as well as a black hole binary.

Not so different

“Our work says that actually general relativity is not so different from Newtonian gravity (or better, electric forces) when expressed in the right way,” explains Most. The actual behaviour predicted is the same in both formulations but the trio’s reformulation reveals how general relativity and Newtonian physics are more similar than they are generally considered to be. “The main new thing is then what does it mean to ‘observe’ gravity, and what does it mean to measure distances relative to how you ‘observe’.”

Alexander Phillipov is a black-hole expert at the University of Maryland in the US and was not directly involved with Most’s research. He describes the research as “very nice”, adding that while the analogy between gravity and electromagnetism has been extensively explored in the past, there is novelty in the interpretation of results from fully nonlinear general relativistic simulations in terms of effective electromagnetic fields. “It promises to provide valuable intuition for a broad class of problems involving compact object mergers.”

The research is described in Physical Review Letters.

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“Picture the world of Avatar, where glowing plants light up an entire ecosystem,” describes Shuting Liu of South China Agricultural University in Guangzhou.

Well, that vision is now a step closer thanks to researchers in China who have created glow-in-the-dark succulents that recharge in sunlight.

Instead of coaxing cells to glow through genetic modification, the team instead used afterglow phosphor particles – materials similar to those found in glow-in-the-dark toys – that can absorb light and release it slowly over time.

The researchers then injected the particles into succulents, finding that they produced a strong glow, thanks to the narrow, uniform and evenly distributed channels within the leaf that helped to disperse the particles.

After a couple of minutes of exposure to sunlight or indoor LED light, the modified plants glowed for up to two hours. By using different types of phosphors, the researchers created plants that shine in various colours, including green, red and blue.

The team even built a glowing plant wall with 56 succulents, which was bright enough to illuminate nearby objects.

“I just find it incredible that an entirely human-made, micro-scale material can come together so seamlessly with the natural structure of a plant,” notes Liu. “The way they integrate is almost magical. It creates a special kind of functionality.”

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