Physics

Research roundup: 6 cool stories we almost missed

animals, Biology, chemistry, fermentation, microbiology, Physics, psychology, robotics, Science, social networks / Rejus Almole / December 1, 2025

The assassination of a Hungarian duke, why woodpeckers grunt when they peck, and more.

Skull of remains found in a 13th century Dominican monastery on Margaret Island, Budapest, Hungary Credit: Eötvös Loránd University

It’s a regrettable reality that there is never enough time to cover all the interesting scientific stories we come across each month. In the past, we’ve featured year-end roundups of cool science stories we (almost) missed. This year, we’re experimenting with a monthly collection. November’s list includes forensic details of the medieval assassination of a Hungarian duke, why woodpeckers grunt when they peck, and more evidence that X’s much-maligned community notes might actually help combat the spread of misinformation after all.

An assassinated medieval Hungarian duke

The observed perimortem lesions on the human remains (CL=cranial lesion, PL= Postcranial lesion). The drawing of the skeleton was generated using OpenAI’s image generation tools (DALL·E) via ChatGPT. — Credit: Tamás Hajdu et al., 2026

Back in 1915, archaeologists discovered the skeletal remains of a young man in a Dominican monastery on Margaret Island in Budapest, Hungary. The remains were believed to be those of Duke Bela of Masco, grandson of the medieval Hungarian King Bela IV. Per historical records, the young duke was brutally assassinated in 1272 by a rival faction and his mutilated remains were recovered by the duke’s sister and niece and buried in the monastery.

The identification of the remains was based on a contemporary osteological analysis, but they were subsequently lost and only rediscovered in 2018. A paper published in the journal Forensic Science International: Genetics has now confirmed that identification and shed more light on precisely how the duke died. (A preprint is available on bioRxiv.]

An interdisciplinary team of researchers performed various kinds of bioarchaeological analysis on the remains. including genetic testing, proteomics, 3D modeling, and radiocarbon dating. The resulting data definitively proves that the skeleton is indeed that of Duke Bela of Masco.

The authors were also able to reconstruct the manner of the duke’s death, concluding that this was a coordinated attack by three people. One attacked from the front while the other two attacked from the left and right sides, and the duke was facing his assassins and tried to defend himself. The weapons used were most likely a saber and a long sword, and the assassins kept raining down blows even after the duke had fallen to the ground. The authors concluded that while the attack was clearly planned, it was also personal and fueled by rage or hate.

DOI: Forensic Science International: Genetics, 2025. 10.1016/j.fsigen.2025.103381 (About DOIs).

Why woodpeckers grunt when they peck

A male Pileated woodpecker foraging on a t

Woodpeckers energetically drum away at tree trunks all day long with their beaks and yet somehow never seem to get concussions, despite the fact that such drumming can produce deceleration forces as high as 1,200 g’s. (Humans suffer concussions with a sudden deceleration of just 100 g’s.) While popular myth holds that woodpecker heads are structured in such a way to absorb the shock, and there has been some science to back that up, more recent research found that their heads act more like hammers than shock absorbers. A paper published in the Journal of Experimental Biology sheds further light on the biomechanics of how woodpeckers essentially turn themselves into hammers and reveals that the birds actually grunt as they strike wood.

The authors caught eight wild downy woodpeckers and recorded them drilling and tapping on pieces of hardwood in the lab for three days, while also measuring electrical signals in their heads, necks, abdomens, tails, and leg muscles. Analyzing the footage, they found that woodpeckers use their hip flexors and front neck muscles to propel themselves forward as they peck while tipping their heads back and bracing themselves using muscles at the base of the skull and back of the neck. The birds use abdominal muscles for stability and brace for impact using their tail muscles to anchor their bodies against a tree. As for the grunting, the authors noted that it’s a type of breathing pattern used by tennis players (and martial artists) to boost the power of a strike.

DOI: Journal of Experimental Biology, 2025. 10.1242/jeb.251167 (About DOIs).

Raisins turn water into wine

wine glass half filled with raisins — Credit: Kyoto University

Fermentation has been around in some form for millennia, relying on alcohol-producing yeasts like Saccharomyces cerevisiae; cultured S. cerevisiae is still used by winemakers today. It’s long been thought that winemakers in ancient times stored fresh crushed grapes in jars and relied on natural fermentation to work its magic, but recent studies have called this into question by demonstrating that S. cerevisiae colonies usually don’t form on fresh grape skins. But the yeast does like raisins, as Kyoto University researchers recently discovered. They’ve followed up that earlier work with a paper published in Scientific Reports, demonstrating that it’s possible to use raisins to turn water into wine.

The authors harvested fresh grapes and dried them for 28 days. Some were dried using an incubator, some were sun-dried, and a third batch was dried using a combination of the two methods. The researchers then added the resulting raisins to bottles of water—three samples for each type of drying process—sealed the bottles, and stored them at room temperature for two weeks. One incubator-dried sample and two combo samples successfully fermented, but all three of the sun-dried samples did so, and at higher ethanol concentrations. Future research will focus on identifying the underlying molecular mechanisms. And for those interested in trying this at home, the authors warn that it only works with naturally sun-dried raisins, since store-bought varieties have oil coatings that block fermentation.

DOI: Scientific Reports, 2025. 10.1038/s41598-025-23715-3 (About DOIs).

An octopus-inspired pigment

An octopus camouflages itself with the seafloor. — Credit: Charlotte Seid

Octopuses, cuttlefish, and several other cephalopods can rapidly shift the colors in their skin thanks to that skin’s unique complex structure, including layers of chromatophores, iridophores, and leucophores. A color-shifting natural pigment called xanthommatin also plays a key role, but it’s been difficult to study because it’s hard to harvest enough directly from animals, and lab-based methods of making the pigment are labor-intensive and don’t yield much. Scientists at the University of San Diego have developed a new method for making xanthommatin in substantially larger quantities, according to a paper published in Nature Biotechnology.

The issue is that trying to get microbes to make foreign compounds creates a metabolic burden, and the microbes hence resist the process, hindering yields. The USD team figured out how to trick the cells into producing more xanthommatin by genetically engineering them in such a way that making the pigment was essential to a cell’s survival. They achieved yields of between 1 and 3 grams per liter, compared to just five milligrams of pigment per liter using traditional approaches. While this work is proof of principle, the authors foresee such future applications as photoelectronic devices and thermal coatings, dyes, natural sunscreens, color-changing paints, and environmental sensors. It could also be used to make other kinds of chemicals and help industries shift away from older methods that rely on fossil fuel-based materials.

DOI: Nature Biotechnology, 2025. 10.1038/s41587-025-02867-7 (About DOIs).

A body-swap robot

Participant standing on body-swap balance robot — Credit: Sachi Wickramasinghe/UBC Media Relations

Among the most serious risks facing older adults is falling. According to the authors of a paper published in Science Robotics, standing upright requires the brain to coordinate signals from the eyes, inner ears, and feet to counter gravity, and there’s a natural lag in how fast this information travels back and forth between brain and muscles. Aging and certain diseases like diabetic neuropathy and multiple sclerosis can further delay that vital communication; the authors liken it to steering a car with a wheel that responds half a second late. And it’s a challenge to directly study the brain under such conditions.

That’s why researchers at the University of British Columbia built a large “body swap” robotic platform. Subjects stood on force plates attached to a motor-driven backboard to reproduce the physical forces at play when standing upright: gravity, inertia, and “viscosity,” which in this case describes the damping effect of muscles and joints that allow us to lean without falling. The platform is designed to subtly alter those forces and also add a 200-millisecond delay.

The authors tested 20 participants and found that lowering inertia and making the viscosity negative resulted in similar instability to that which resulted from a signal delay. They then brought in ten new subjects to study whether adjusting body mechanics could compensate for information delays. They found that adding inertia and viscosity could at least partially counter the instability that arose from signal delay—essentially giving the body a small mechanical boost to help the brain maintain balance. The eventual goal is to design wearables that offer gentle resistance when an older person starts to lose their balance, and/or help patients with MS, for example, adjust to slower signal feedback.

DOI: Science Robotics, 2025. 10.1126/scirobotics.adv0496 (About DOIs).

X community notes might actually work

cropped image of phone screen showing an X post with a community note underneath — Credit: Huaxia Rui

Earlier this year, Elon Musk claimed that X’s community notes feature needed tweaking because it was being gamed by “government & legacy media” to contradict Trump—despite vigorously defending the robustness of the feature against such manipulation in the past. A growing body of research seems to back Musk’s earlier stance.

For instance, last year Bloomberg pointed to several studies suggesting that crowdsourcing worked just as well as using professional fact-checkers when assessing the accuracy of news stories. The latest evidence that crowd-sourcing fact checks can be effective at curbing misinformation comes from a paper published in the journal Information Systems Research, which found that X posts with public corrections were 32 percent more likely to be deleted by authors.

Co-author Huaxia Rui of the University of Rochester pointed out that community notes must meet a threshold before they will appear publicly on posts, while those that do not remain hidden from public view. Seeing a prime opportunity in the arrangement, Rui et al. analyzed 264,600 X posts that had received at least one community note and compared those just above and just below that threshold. The posts were collected from two different periods: June through August 2024, right before the US presidential election (when misinformation typically surges), and the post-election period of January and February 2025.

The fact that roughly one-third of authors responded to public community notes by deleting the post suggests that the built-in dynamics of social media (e.g., status, visibility, peer feedback) might actually help improve the spread of misinformation as intended. The authors concluded that crowd-checking “strikes a balance between First Amendment rights and the urgent need to curb misinformation.” Letting AI write the community notes, however, is probably still a bad idea.

DOI: Information Systems Research, 2025. 10.1287/isre.2024.1609 (About DOIs).

Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

Research roundup: 6 cool stories we almost missed Read More »

What if the aliens come and we just can’t communicate?

aliens, books, culture, extraterrestrial life, Features, Linguistics, mathematics, Physics, Science / Rejus Almole / November 13, 2025

Ars chats with particle physicist Daniel Whiteson about his new book Do Aliens Speak Physics?

Science fiction has long speculated about the possibility of first contact with an alien species from a distant world and how we might be able to communicate with them. But what if we simply don’t have enough common ground for that to even be possible? An alien species is bound to be biologically very different, and their language will be shaped by their home environment, broader culture, and even how they perceive the universe. They might not even share the same math and physics. These and other fascinating questions are the focus of an entertaining new book, Do Aliens Speak Physics? And Other Questions About Science and the Nature of Reality.

Co-author Daniel Whiteson is a particle physicist at the University of California, Irvine, who has worked on the ATLAS collaboration at CERN’s Large Hadron Collider. He’s also a gifted science communicator who previously co-authored two books with cartoonist Jorge Cham of PhD Comics fame: 2018’s We Have No Idea and 2021’s Frequently Asked Questions About the Universe. (The pair also co-hosted a podcast from 2018 to 2024, Daniel and Jorge Explain the Universe.) This time around, cartoonist Andy Warner provided the illustrations, and Whiteson and Warner charmingly dedicate their book to “all the alien scientists we have yet to meet.”

Whiteson has long been interested in the philosophy of physics. “I’m not the kind of physicist who’s like, ‘whatever, let’s just measure stuff,’” he told Ars. “The thing that always excited me about physics was this implicit promise that we were doing something universal, that we were learning things that were true on other planets. But the more I learned, the more concerned I became that this might have been oversold. None are fundamental, and we don’t understand why anything emerges. Can we separate the human lens from the thing we’re looking at? We don’t know in the end how much that lens is distorting what we see or defining what we’re looking at. So that was the fundamental question I always wanted to explore.”

Whiteson initially pitched his book idea to his 14-year-old son, who inherited his father’s interest in science. But his son thought Whiteson’s planned discussion of how physics might not be universal was, well, boring. “When you ask for notes, you’ve got to listen to them,” said Whiteson. “So I came back and said, ‘Well, what about a book about when aliens arrive? Will their science be similar to ours? Can we collaborate together?’” That pitch won the teen’s enthusiastic approval: same ideas, but couched in the context of alien contact to make them more concrete.

As for Warner’s involvement as illustrator, “I cold-emailed him and said, ‘Want to write a book about aliens? You get to draw lots of weird aliens,’” said Whiteson. Who could resist that offer?

Ars caught up with Whiteson to learn more.

cartoon exploring possible outcomes of first alien contact — Credit: Andy Warner

Ars Technica: You open each chapter with fictional hypothetical scenarios. Why?

Daniel Whiteson: I sent an early version of the book to my friend, [biologist] Matt Giorgianni, who appears in cartoon form in the book. He said, “The book is great, but it’s abstract. Why don’t you write out a hypothetical concrete scenario for each chapter to show us what it would be like and how we would stumble.”

All great ideas seem obvious once you hear them. I’ve always been a huge science fiction fan. It’s thoughtful and creative and exploratory about the way the universe could be and might be. So I jumped at the opportunity to write a little bit of science fiction. Each one was challenging because you have to come up with a specific example that illustrates the concepts in that chapter, the issues that you might run into, but also be believable and interesting. We went through a lot of drafts. But I had a lot of fun writing them.

Ars Technica: The Voyager Golden Record is perhaps the best known example of humans attempting to communicate with an alien species, spearheaded by the late Carl Sagan, among others. But what are the odds that, despite our best efforts, any aliens will ever be able to decipher our “message in a bottle”?

Daniel Whiteson: I did an informal experiment where I printed out a picture of the Pioneer plaque and showed it to a bunch of grad students who were young enough to not have seen it before. This is Sagan’s audience: biological humans, same brain, same culture, physics grad students—none of them had any idea what any of that was supposed to refer to. NASA gave him two weeks to come up with that design. I don’t know that I would’ve done any better. It’s easy to criticize.

Those folks, they were doing their best. They were trying to step away from our culture. They didn’t use English, they didn’t even use mathematical symbols. They understood that those things are arbitrary, and they were reaching for something they hoped was going to be universal. But in the end, nothing can be universal because language is always symbols, and the choice of those symbols is arbitrary and cultural. It’s impossible to choose a symbol that can only be interpreted in one way.

Fundamentally, the book is trying to poke at our assumptions. It’s so inspiring to me that the history of physics is littered with times when we have had to abandon an assumption that we clung to desperately, until we were shown otherwise with enough data. So we’ve got to be really open-minded about whether these assumptions hold true, whether it’s required to do science, to be technological, or whether there is even a single explanation for reality. We could be very well surprised by what we discover.

Ars Technica: It’s often assumed that math and physics are the closest thing we have to a universal language. You challenge that assumption, probing such questions as “what does it even mean to ‘count’”?

Daniel Whiteson: At an initial glance, you’re like, well, of course mathematics is required, and of course numbers are universal. But then you dig into it and you start to realize there are fuzzy issues here. So many of the assumptions that underlie our interpretation of what we learned about physics are that way. I had this experience that’s probably very common among physics undergrads in quantum mechanics, learning about those calculations where you see nine decimal places in the theory and nine decimal places in the experiment, and you go, “Whoa, this isn’t just some calculational tool. This is how the universe decides what happens to a particle.”

I literally had that moment. I’m not a religious person, but it was almost spiritual. For many years, I believed that deeply, and I thought it was obvious. But to research this book, I read Science Without Numbers by Hartry Field. I was lucky—here at Irvine, we happen to have an amazing logic and philosophy of science department, and those folks really helped me digest [his ideas] and understand how you can pull yourself away from things like having a number line. It turns out you don’t need numbers; you can just think about relationships. It was really eye-opening, both how essential mathematics seems to human science and how obvious it is that we’re making a bunch of assumptions that we don’t know how to justify.

There are dotted lines humans have drawn because they make sense to us. You don’t have to go to plasma swirls and atmospheres to imagine a scenario where aliens might not have the same differentiation between their identities, me and you, here’s where I end, and here’s where you begin. That’s complicated for aliens that are plasma swirls, but also it’s not even very well-defined for us. How do I define the edge of my body? Is it where my skin ends? What about the dead skin, the hair, my personal space? There’s no obvious definition. We just have a cultural sense for “this is me, this is not me.” In the end, that’s a philosophical choice.

Cartoon of an alien emerging from a spaceship and a human saying — Credit: Andy Warner

Ars Technica: You raise another interesting question in the book: Would aliens even need physics theory or a deeper understanding of how the universe works? Perhaps they could invent, say, warp drive through trial and error. You suggest that our theory is more like a narrative framework. It’s the story we tell, and that is very much prone to bias.

Daniel Whiteson: Absolutely. And not just bias, but emotion and curiosity. We put energy into certain things because we think they’re important. Physicists spend our lives on this because we think, among the many things we could spend our time on, this is an important question. That’s an emotional choice. That’s a personal subjective thing.

Other people find my work dead boring and would hate to have my life, and I would feel the same way about theirs. And that’s awesome. I’m glad that not everybody wants to be a particle physicist or a biologist or an economist. We have a diversity of curiosity, which we all benefit from. People have an intuitive feel for certain things. There’s something in their minds that naturally understands how the system works and reflects it, and they probably can’t explain it. They might not be able to design a better car, but they can drive the heck out of it.

This is maybe the biggest stumbling block for people who are just starting to think about this for the first time. “Obviously aliens are scientific.” Well, how do we know? What do we mean by scientific? That concept has evolved over time, and is it really required? I felt that that was a big-picture thing that people could wrap their minds around but also a shock to the system. They were already a little bit off-kilter and might realize that some things they assumed must be true maybe not have to be.

Ars Technica: You cite the 2016 film Arrival as an example of first contact and the challenge of figuring out how to communicate with an alien species. They had to learn each other’s cultural context before they had any chance of figuring out what their respective symbols meant.

Daniel Whiteson: I think that is really crucial. Again, how you choose to represent your ideas is, in a sense, arbitrary. So if you’re on the other side of that, and you have to go from symbols to ideas, you have to know something about how they made those choices in order to reverse-engineer a message, in order to figure out what it means. How do you know if you’ve done it correctly? Say we get a message from aliens and we spend years of supercomputer time cranking on it. Something we rely on for decoding human messages is that you can tell when you’ve done it right because you have something that makes sense.

How do we know when we’ve done that for an alien text? How do you know the difference between nonsense and things that don’t yet make sense to you? It’s essentially impossible. I spoke to some philosophers of language who convinced me that if we get a message from aliens, it might be literally impossible to decode it without their help, without their context. There aren’t enough examples of messages from aliens. We have the “Wow!” signal—who knows what that means? Maybe it’s a great example of getting a message and having no idea how to decode it.

As in many places in the book, I turned to human history because it’s the one example we have. I was shocked to discover how many human languages we haven’t decoded. Not to mention, we haven’t decoded whale. We know whales are talking to each other. Maybe they’re talking to us and we can’t decode it. The lesson, again and again, is culture.

With the Egyptians, the only reason we were able to decode hieroglyphics is because we had the Rosetta Stone, but that still took 20 years there. How does it take 20 years when you have examples and you know what it’s supposed to say? And the answer is that we made cultural assumptions. We assumed pictograms reflected the ideas in the pictures. If there’s a bird in it, it’s about birds. And we were just wrong. That’s maybe why we’ve been struggling with Etruscan and other languages we’ve never decoded.

Even when we do have a lot of culture in common, it’s very, very tricky. So the idea that we would get a message from space and have no cultural clues at all and somehow be able to decode it—I think that only works in the scenario where aliens have been listening to us for a long time and they’re essentially writing to us in something like our language. I’m a big fan of SETI. They host these conferences where they listen to philosophers and linguists and anthropologists. I don’t mean to say that they’ve thought too narrowly, but I think it’s not widely enough appreciated how difficult it is to decode another language with no culture in common.

Ars Technica: You devote a chapter to the possibility that aliens might be able to, say, “taste” electrons. That drives home your point that physiologically, they will probably be different, biologically they will be different, and their experiences are likely to be different. So their notion of culture will also be different.

Daniel Whiteson: Something I really wanted to get across was that perception determines your sense of intuition, which defines in many ways the answers you find acceptable. I read Ed Yong’s amazing book, An Immense World, about animal perception, the diversity of animal experience or animal interaction with the environment. What is it like to be an octopus with a distributed mind? What is it like to be a bird that senses magnetic fields? If you’re an alien and you have very different perceptions, you could also have a different intuitive language in which to understand the universe. What is a photon? Is it a particle? Is it a wave? Maybe we just struggle with the concept because our intuitive language is limited.

For an alien that can see photons in superposition, this is boring. They could be bored by things we’re fascinated by, or we could explain our theories to them and they could be unsatisfied because to them, it doesn’t translate into their intuitive language. So even though we’ve transcended our biological limitations in many ways, we can detect gravitational waves and infrared photons, we’re still, I think, shaped by those original biological senses that frame our experience, the models we build. What it’s like to be a human in the world could be very, very different from what it’s like to be an alien in the world.

Ars Technica: Your very last line reads, “Our theories may reveal the patterns of our thoughts as much as the patterns of nature.” Why did you choose to end your book on that note?

Daniel Whiteson: That’s a message to myself. When I started this journey, I thought physics is universal. That’s what makes it beautiful. That implies that if the aliens show up and they do physics in a very different way, it would be a crushing disappointment. Not only is what we’ve learned just another human science, but also it means maybe we can’t benefit from their work or we can’t have that fantasy of a galactic scientific conference. But that actually might be the best-case scenario.

I mean, the reason that you want to meet aliens is the reason you go traveling. You want to expand your horizons and learn new things. Imagine how boring it would be if you traveled around the world to some new country and they just had all the same food. It might be comforting in some way, but also boring. It’s so much more interesting to find out that they have spicy fish soup for breakfast. That’s the moment when you learn not just about what to have for breakfast but about yourself and your boundaries.

So if aliens show up and they’re so weirdly different in a way we can’t possibly imagine—that would be deeply revealing. It’ll give us a chance to separate the reality from the human lens. It’s not just questions of the universe. We are interesting, and we should learn about our own biases. I anticipate that when the aliens do come, their culture and their minds and their science will be so alien, it’ll be a real challenge to make any kind of connection. But if we do, I think we’ll learn a lot, not just about the universe but about ourselves.

What if the aliens come and we just can’t communicate? Read More »

Quantum computing tech keeps edging forward

Computer science, ibm, IonQ, Physics, Quantum Art, quantum computing, quantum mechanics, Science, trapped ion / Rejus Almole / November 12, 2025

More superposition, less supposition

IBM follows through on its June promises, plus more trapped ion news.

IBM has moved to large-scale manufacturing of its Quantum Loon chips. Credit: IBM

The end of the year is usually a busy time in the quantum computing arena, as companies often try to announce that they’ve reached major milestones before the year wraps up. This year has been no exception. And while not all of these announcements involve interesting new architectures like the one we looked at recently, they’re a good way to mark progress in the field, and they often involve the sort of smaller, incremental steps needed to push the field forward.

What follows is a quick look at a handful of announcements from the past few weeks that struck us as potentially interesting.

IBM follows through

IBM is one of the companies announcing a brand-new architecture this year. That’s not at all a surprise, given that the company promised to do so back in June; this week sees the company confirming that it has built the two processors it said it would earlier in the year. These include one called Loon, which is focused on the architecture that IBM will use to host error-corrected logical qubits. Loon represents two major changes for the company: a shift to nearest-neighbor connections and the addition of long-distance connections.

IBM had previously used what it termed the “heavy hex” architecture, in which alternating qubits were connected to either two or three of their neighbors, forming a set of overlapping hexagonal structures. In Loon, the company is using a square grid, with each qubit having connections to its four closest neighbors. This higher density of connections can enable more efficient use of the qubits during computations. But qubits in Loon have additional long-distance connections to other parts of the chip, which will be needed for the specific type of error correction that IBM has committed to. It’s there to allow users to test out a critical future feature.

The second processor, Nighthawk, is focused on the now. It also has the nearest-neighbor connections and a square grid structure, but it lacks the long-distance connections. Instead, the focus with Nighthawk is to get error rates down so that researchers can start testing algorithms for quantum advantage—computations where quantum computers have a clear edge over classical algorithms.

In addition, the company is launching a GitHub repository that will allow the community to deposit code and performance data for both classical and quantum algorithms, enabling rigorous evaluations of relative performance. Right now, those are broken down into three categories of algorithms that IBM expects are most likely to demonstrate a verifiable quantum advantage.

This isn’t the only follow-up to IBM’s June announcement, which also saw the company describe the algorithm it would use to identify errors in its logical qubits and the corrections needed to fix them. In late October, the company said it had confirmed that the algorithm could work in real time when run on an FPGA made in collaboration with AMD.

Record lows

A few years back, we reported on a company called Oxford Ionics, which had just announced that it achieved a record-low error rate in some qubit operations using trapped ions. Most trapped-ion quantum computers move qubits by manipulating electromagnetic fields, but they perform computational operations using lasers. Oxford Ionics figured out how to perform operations using electromagnetic fields, meaning more of their processing benefited from our ability to precisely manufacture circuitry (lasers were still needed for tasks like producing a readout of the qubits). And as we noted, it could perform these computational operations extremely effectively.

But Oxford Ionics never made a major announcement that would give us a good excuse to describe its technology in more detail. The company was ultimately acquired by IonQ, a competitor in the trapped-ion space.

Now, IonQ is building on what it gained from Oxford Ionics, announcing a new, record-low error rate for two-qubit gates: greater than 99.99 percent fidelity. That could be critical for the company, as a low error rate for hardware qubits means fewer are needed to get good performance from error-corrected qubits.

But the details of the two-qubit gates are perhaps more interesting than the error rate. Two-qubit gates involve bringing both qubits involved into close proximity, which often requires moving them. That motion pumps a bit of energy into the system, raising the ions’ temperature and leaving them slightly more prone to errors. As a result, any movement of the ions is generally followed by cooling, in which lasers are used to bleed energy back out of the qubits.

This process, which involves two distinct cooling steps, is slow. So slow that as much as two-thirds of the time spent in operations involves the hardware waiting around while recently moved ions are cooled back down. The new IonQ announcement includes a description of a method for performing two-qubit gates that doesn’t require the ions to be fully cooled. This allows one of the two cooling steps to be skipped entirely. In fact, coupled with earlier work involving one-qubit gates, it raises the possibility that the entire machine could operate with its ions at a still very cold but slightly elevated temperature, avoiding all need for one of the two cooling steps.

That would shorten operation times and let researchers do more before the limit of a quantum system’s coherence is reached.

State of the art?

The last announcement comes from another trapped-ion company, Quantum Art. A couple of weeks back, it announced a collaboration with Nvidia that resulted in a more efficient compiler for operations on its hardware. On its own, this isn’t especially interesting. But it’s emblematic of a trend that’s worth noting, and it gives us an excuse to look at Quantum Art’s technology, which takes a distinct approach to boosting the efficiency of trapped-ion computation.

First, the trend: Nvidia’s interest in quantum computing. The company isn’t interested in the quantum aspects (at least not publicly); instead, it sees an opportunity to get further entrenched in high-performance computing. There are three areas where the computational capacity of GPUs can play a role here. One is small-scale modeling of quantum processors so that users can perform an initial testing of algorithms without committing to paying for access to the real thing. Another is what Quantum Art is announcing: using GPUs as part of a compiler chain to do all the computations needed to find more efficient ways of executing an algorithm on specific quantum hardware.

Finally, there’s a potential role in error correction. Error correction involves some indirect measurements of a handful of hardware qubits to determine the most likely state that a larger collection (called a logical qubit) is in. This requires modeling a quantum system in real time, which is quite difficult—hence the computational demands that Nvidia hopes to meet. Regardless of the precise role, there has been a steady flow of announcements much like Quantum Art’s: a partnership with Nvidia that will keep the company’s hardware involved if the quantum technology takes off.

In Quantum Art’s case, that technology is a bit unusual. The trapped-ion companies we’ve covered so far are all taking different routes to the same place: moving one or two ions into a location where operations can be performed and then executing one- or two-qubit gates. Quantum Art’s approach is to perform gates with much larger collections of ions. At the compiler level, it would be akin to figuring out which qubits need a specific operation performed, clustering them together, and doing it all at once. Obviously, there are potential efficiency gains here.

The challenge would normally be moving so many qubits around to create these clusters. But Quantum Art uses lasers to “pin” ions in a row so they act to isolate the ones to their right from the ones to their left. Each cluster can then be operated on separately. In between operations, the pins can be moved to new locations, creating different clusters for the next set of operations. (Quantum Art is calling each cluster of ions a “core” and presenting this as multicore quantum computing.)

At the moment, Quantum Art is behind some of its competitors in terms of qubit count and performing interesting demonstrations, and it’s not pledging to scale quite as fast. But the company’s founders are convinced that the complexity of doing so many individual operations and moving so many ions around will catch up with those competitors, while the added efficiency of multiple qubit gates will allow it to scale better.

This is just a small sampling of all the announcements from this fall, but it should give you a sense of how rapidly the field is progressing—from technology demonstrations to identifying cases where quantum hardware has a real edge and exploring ways to sustain progress beyond those first successes.

John is Ars Technica’s science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots.

Quantum computing tech keeps edging forward Read More »

Next-generation black hole imaging may help us understand gravity better

astrophysics, black hole, event horizon, Event Horizon Telescope, gravity, Physics, relativity, Science / Paul Patrick / November 6, 2025

Right now, we probably don’t have the ability to detect these small changes in phenomena. However, that may change, as a next-generation version of the Event Horizon Telescope is being considered, along with a space-based telescope that would operate on similar principles. So the team (four researchers based in Shanghai and CERN) decided to repeat an analysis they did shortly before the Event Horizon Telescope went operational, and consider whether the next-gen hardware might be able to pick up features of the environment around the black hole that might discriminate among different theorized versions of gravity.

Theorists have been busy, and there are a lot of potential replacements for general relativity out there. So, rather than working their way through the list, they used a model of gravity (the parametric Konoplya–Rezzolla–Zhidenko metric) that allows that isn’t specific to any given hypothesis. Instead, it allows some of its parameters to be changed, thus allowing the team to vary the behavior of gravity within some limits. To get a sense of the sort of differences that might be present, the researchers swapped two different parameters between zero and one, giving them four different options. Those results were compared to the Kerr metric, which is the standard general relativity version of the event horizon.

Small but clear differences

Using those five versions of gravity, they model the three-dimensional environment near the event horizon using hydrodynamic simulations, including infalling matter, the magnetic fields it produces, and the jets of matter that those magnetic fields power.

The results resemble the sorts of images that the Event Horizon Telescope produced. These include a bright ring with substantial asymmetry, where one side is significantly brighter due to the rotation of the black hole. And, while the differences are subtle between all the variations of gravity, they’re there. One extreme version produced the smallest but brightest ring; another had a reduced contrast between the bright and dim side of the ring. There were also differences between the width of the jets produced in these models.

Next-generation black hole imaging may help us understand gravity better Read More »

New quantum hardware puts the mechanics in quantum mechanics

Computer science, Helios, Physics, quantinuum, quantum computing, quantum mechanics, Science, trapped ion / Rejus Almole / November 5, 2025

As a test case, the machine was used to test a model of superconductivity.

Quantum computers based on ions or atoms have one major advantage: The hardware itself isn’t manufactured, so there’s no device-to-device variability. Every atom is the same and should perform similarly every time. And since the qubits themselves can be moved around, it’s theoretically possible to entangle any atom or ion with any other in the system, allowing for a lot of flexibility in how algorithms and error correction are performed.

This combination of consistent, high-fidelity performance with all-to-all connectivity has led many key demonstrations of quantum computing to be done on trapped-ion hardware. Unfortunately, the hardware has been held back a bit by relatively low qubit counts—a few dozen compared to the hundred or more seen in other technologies. But on Wednesday, a company called Quantinuum announced a new version of its trapped-ion hardware that significantly boosts the qubit count and uses some interesting technology to manage their operation.

Trapped-ion computing

Both neutral atom and trapped-ion computers store their qubits in the spin of the nucleus. That spin is somewhat shielded from the environment by the cloud of electrons around the nucleus, giving these qubits a relatively long coherence time. While neutral atoms are held in place by a network of lasers, trapped ions are manipulated via electromagnetic control based on the ion’s charge. This means that key components of the hardware can be built using standard electronic manufacturing, although lasers are still needed for manipulations and readout.

While the electronics are static—they stay wherever they were manufactured—they can be used to move the ions around. That means that as long as the trackways the atoms can move on enable it, any two ions can be brought into close proximity and entangled. This all-to-all connectivity can enable more efficient implementation of algorithms performed directly on the hardware qubits or the use of error-correction codes that require a complicated geometry of connections. That’s one reason why Microsoft used a Quantinuum machine to demonstrate error-correction code based on a tesseract.

But arranging the trackways so that any two qubits can be next to each other can become increasingly complicated. Moving ions around is a relatively slow process, so retrieving two ions from the far ends of a chip too often can cause a system to start pushing up against the coherence time of the qubits. In the long term, Quantinuum plans to build chips with a square grid reminiscent of the street layout of many cities. But doing so will require a mastery of controlling the flow of ions through four-way intersections.

And that’s what Quantinuum is doing in part with its new chip, named Helios. It has a single intersection that couples two ion-storage areas, enabling operations as ions slosh from one end of the chip to the other. And it comes with significantly more qubits than its earlier hardware, moving from 56 to 96 qubits without sacrificing performance. “We’ve kept and actually even improved the two qubit gate fidelity,” Quantinuum VP Jenni Strabley told Ars. “So we’re not seeing any degradation in the two-qubit gate fidelity as we go to larger and larger sizes.”

Doing the loop

The image below is taken using the fluorescence of the atoms in the hardware itself. As you can see, the layout is dominated by two features: A loop at the left and two legs extending to the right. They’re connected by a four-way intersection. The Quantinuum staff described this intersection as being central to the computer’s operation.

A black background on which a series of small blue dots trace out a circle and two parallel lines connected by an x-shaped junction. — The actual ions trace out the physical layout of the Helios system, featuring a storage ring and two legs that contain dedicated operation sites. Credit: Quantinuum

The system works by rotating the ions around the loop. As an ion reaches the intersection, the system chooses whether to kick it into one of the legs and, if so, which leg. “We spin that ring almost like a hard drive, really, and whenever the ion that we want to gate gets close to the junction, there’s a decision that happens: Either that ion goes [into the legs], or it kind of makes a little turn and goes back into the ring,” said David Hayes, Quantinuum’s director of Computational Design and Theory. “And you can make that decision with just a few electrodes that are right at that X there.”

Each leg has a region where operations can take place, so this system can ensure that the right qubits are present together in the operation zones for things like two-qubit gates. Once the operations are complete, the qubits can be moved into the leg storage regions, and new qubits can be shuffled in. When the legs fill up, the qubits can be sent back to the loop, and the process is restarted.

“You get less traffic jams if all the traffic is running one way going through the gate zones,” Hayes told Ars. “If you had to move them past each other, you would have to do kind of physical swaps, and you want to avoid that.”

Obviously, issuing all the commands to control the hardware will be quite challenging for anything but the simplest operations. That puts an increasing emphasis on the compilers that add a significant layer of abstraction between what you want a quantum computer to do and the actual hardware commands needed to implement it. Quantinuum has developed its own compiler to take user-generated code and produce something that the control system can convert into the sequence of commands needed.

The control system now incorporates a real-time engine that can read data from Helios and update the commands it issues based on the state of the qubits. Quantinuum has this portion of the system running on GPUs rather than requiring customized hardware.

Quantinuum’s SDK for users is called Guppy and is based on Python, which has been modified to allow users to describe what they’d like the system to do. Helios is being accompanied by a new version of Guppy that includes some traditional programming tools like FOR loops and IF-based conditionals. These will be critical for the sorts of things we want to do as we move toward error-corrected qubits. This includes testing for errors, fixing them if they’re present, or repeatedly attempting initialization until it succeeds without error.

Hayes said the new version is also moving toward error correction. Thanks to Guppy’s ability to dynamically reassign qubits, Helios will be able to operate as a machine with 94 qubits while detecting errors on any of them. Alternatively, the 96 hardware qubits can be configured as a single unit that hosts 48 error-corrected qubits. “It’s actually a concatenated code,” Hayes told Ars. “You take two error detection codes and weave them together… it’s a single code block, but it has 48 logical cubits housed inside of it.” (Hayes said it’s a distance-four code, meaning it can fix up to two errors that occur simultaneously.)

Tackling superconductivity

While Quantinuum hardware has always had low error rates relative to most of its competitors, there was only so much you could do with 56 qubits. With 96 now at their disposal, researchers at the company decided to build a quantum implementation of a model (called the Fermi-Hubbard model) that’s meant to help study the electron pairing that takes place during the transition to superconductivity.

“There are definitely terms that the model doesn’t capture,” Quantinuum’s Henrik Dreyer acknowledged. “They neglect their electrorepulsion that [the electrons] still have—I mean, they’re still negatively charged; they are still repelling. There are definitely terms that the model doesn’t capture. On the other hand, I should say that this Fermi-Hubbard model—it has many of the features that a superconductor has.”

Superconductivity occurs when electrons join to form what are called Cooper pairs, overcoming their normal repulsion. And the model can tell that apart from normal conductivity in the same material.

“You ask the question ‘What’s the chance that one of the charged particles spontaneously disappears because of quantum fluctuations and goes over here?’” Dreyer said, describing what happens when simulating a conductor. “What people do in superconductivity is they take this concept, but instead of asking what’s the chance of a single-charge particle to tunnel over there spontaneously, they’re asking what is the chance of a pair to tunnel spontaneously?”

Even in its simplified form, however, it’s still a model of a quantum system, with all the computational complexity that comes with that. So the Quantinuum team modeled a few systems that classical computers struggle with. One was simply looking at a larger grid of atoms than most classical simulations have done; another expanded the grid in an additional dimension, modeling layers of a material. Perhaps the most complicated simulation involved what happens when a laser pulse of the right wavelength hits a superconductor at room temperature, an event that briefly induces a superconducting state.

And the system produced results, even without error correction. “It’s maybe a technical point, but I think it’s very important technical point, which is [that] the circuits that we ran, they all had errors,” Dreyer told Ars. “Maybe on the average of three or so errors, and for some reason, that is not very fully understood for this application, it doesn’t matter. You still get almost the perfect result in some of these cases.”

That said, he also indicated that having higher-fidelity hardware would help the team do a better job of putting the system in a ground state or running the simulation for longer. But those will have to wait for future hardware.

What’s next

If you look at Quantinuum’s roadmap for that future hardware, Helios would appear to be the last of its kind. It and earlier versions of the processors have loops and large straight stretches; everything in the future features a grid of squares. But both Strabley and Hayes said that Helios has several key transitional features. “Those ions are moving through that junction many, many times over the course of a circuit,” Strabley told Ars. “And so it’s really enabled us to work on the reliability of the junction, and that will translate into the large-scale systems.”

Image of a product roadmap, with years from 2020 to 2029 noted across the top. There are five processors arrayed from left to right, each with increasingly complex geometry. — Helios sits at the pivot between the simple geometries of earlier Quantinuum processors and the grids of future designs. Credit: Quantinuum

The collection of squares seen in future processors will also allow the same sorts of operations to be done with the loop-and-legs of Helios. Some squares can serve as the equivalent of a loop in terms of storage and sorting, while some of the straight lines nearby can be used for operations.

“What will be common to both of them is kind of the general concept that you can have a storage and sorting region and then gating regions on the side and they’re separated from one another,” Hayes said. “It’s not public yet, but that’s the direction we’re heading: a storage region where you can do really fast sorting in these 2D grids, and then gating regions that have parallelizable logical operations.”

In the meantime, we’re likely to see improvements made to Helios—ideas that didn’t quite make today’s release. “There’s always one more improvement that people want to make, and I’m the person that says, ‘No, we’re going to go now. Put this on the market, and people are going to go use it,’” Strabley said. “So there is a long list of things that we’re going to add to improve the performance. So expect that over the course of Helios, the performance is going to get better and better and better.”

That performance is likely to be used for the sort of initial work done on superconductivity or the algorithm recently described by Google, which is at or a bit beyond what classical computers can manage and may start providing some useful insights. But it will still be a generation or two before we start seeing quantum computing fulfill some of its promise.

New quantum hardware puts the mechanics in quantum mechanics Read More »

Google has a useful quantum algorithm that outperforms a supercomputer

Computer science, Features, Google, NMR, Physics, quantum computing, quantum mechanics, Science / Paul Patrick / October 22, 2025

An approach it calls “quantum echoes” takes 13,000 times longer on a supercomputer.

The work relied on Google’s current-generation quantum hardware, the Willow chip. Credit: Google

A few years back, Google made waves when it claimed that some of its hardware had achieved quantum supremacy, performing operations that would be effectively impossible to simulate on a classical computer. That claim didn’t hold up especially well, as mathematicians later developed methods to help classical computers catch up, leading the company to repeat the work on an improved processor.

While this back-and-forth was unfolding, the field became less focused on quantum supremacy and more on two additional measures of success. The first is quantum utility, in which a quantum computer performs computations that are useful in some practical way. The second is quantum advantage, in which a quantum system completes calculations in a fraction of the time it would take a typical computer. (IBM and a startup called Pasqual have published a useful discussion about what would be required to verifiably demonstrate a quantum advantage.)

Today, Google and a large collection of academic collaborators are publishing a paper describing a computational approach that demonstrates a quantum advantage compared to current algorithms—and may actually help us achieve something useful.

Out of time

Google’s latest effort centers on something it’s calling “quantum echoes.” The approach could be described as a series of operations on the hardware qubits that make up its machine. These qubits hold a single bit of quantum information in a superposition between two values, with probabilities of finding the qubit in one value or the other when it’s measured. Each qubit is entangled with its neighbors, allowing its probability to influence those of all the qubits around it. The operations that allow computation, called gates, are ways of manipulating these probabilities. Most current hardware, including Google’s, perform manipulations on one or two qubits at a time (termed one- and two-qubit gates, respectively.

For quantum echoes, the operations involved performing a set of two-qubit gates, altering the state of the system, and later performing the reverse set of gates. On its own, this would return the system to its original state. But for quantum echoes, Google inserts single-qubit gates performed with a randomized parameter. This alters the state of the system before the reverse operations take place, ensuring that the system won’t return to exactly where it started. That explains the “echoes” portion of the name: You’re sending an imperfect copy back toward where things began, much like an echo involves the imperfect reversal of sound waves.

That’s what the process looks like in terms of operations performed on the quantum hardware. But it’s probably more informative to think of it in terms of a quantum system’s behavior. As Google’s Tim O’Brien explained, “You evolve the system forward in time, then you apply a small butterfly perturbation, and then you evolve the system backward in time.” The forward evolution is the first set of two qubit gates, the small perturbation is the randomized one qubit gate, and the second set of two qubit gates is the equivalent of sending the system backward in time.

Because this is a quantum system, however, strange things happen. “On a quantum computer, these forward and backward evolutions, they interfere with each other,” O’Brien said. One way to think about that interference is in terms of probabilities. The system has multiple paths between its start point and the point of reflection—where it goes from evolving forward in time to evolving backward—and from that reflection point back to a final state. Each of those paths has a probability associated with it. And since we’re talking about quantum mechanics, those paths can interfere with each other, increasing some probabilities at the expense of others. That interference ultimately determines where the system ends up.

(Technically, these are termed “out of time order correlations,” or OTOCs. If you read the Nature paper describing this work, prepare to see that term a lot.)

Demonstrating advantage

So how do you turn quantum echoes into an algorithm? On its own, a single “echo” can’t tell you much about the system—the probabilities ensure that any two runs might show different behaviors. But if you repeat the operations multiple times, you can begin to understand the details of this quantum interference. And performing the operations on a quantum computer ensures that it’s easy to simply rerun the operations with different random one-qubit gates and get many instances of the initial and final states—and thus a sense of the probability distributions involved.

This is also where Google’s quantum advantage comes from. Everyone involved agrees that the precise behavior of a quantum echo of moderate complexity can be modeled using any leading supercomputer. But doing so is very time-consuming, so repeating those simulations a few times becomes unrealistic. The paper estimates that a measurement that took its quantum computer 2.1 hours to perform would take the Frontier supercomputer approximately 3.2 years. Unless someone devises a far better classical algorithm than what we have today, this represents a pretty solid quantum advantage.

But is it a useful algorithm? The repeated sampling can act a bit like the Monte Carlo sampling done to explore the behavior of a wide variety of physical systems. Typically, however, we don’t view algorithms as modeling the behavior of the underlying hardware they’re being run on; instead, they’re meant to model some other physical system we’re interested in. That’s where Google’s announcement stands apart from its earlier work—the company believes it has identified an interesting real-world physical system with behaviors that the quantum echoes can help us understand.

That system is a small molecule in a Nuclear Magnetic Resonance (NMR) machine. In a second draft paper being published on the arXiv later today, Google has collaborated with a large collection of NMR experts to explore that use.

From computers to molecules

NMR is based on the fact that the nucleus of every atom has a quantum property called spin. When nuclei are held near to each other, such as when they’re in the same molecule, these spins can influence one another. NMR uses magnetic fields and photons to manipulate these spins and can be used to infer structural details, like how far apart two given atoms are. But as molecules get larger, these spin networks can extend for greater distances and become increasingly complicated to model. So NMR has been limited to focusing on the interactions of relatively nearby spins.

For this work, though, the researchers figured out how to use an NMR machine to create the physical equivalent of a quantum echo in a molecule. The work involved synthesizing the molecule with a specific isotope of carbon (carbon-13) in a known location in the molecule. That isotope could be used as the source of a signal that propagates through the network of spins formed by the molecule’s atoms.

“The OTOC experiment is based on a many-body echo, in which polarization initially localized on a target spin migrates through the spin network, before a Hamiltonian-engineered time-reversal refocuses to the initial state,” the team wrote. “This refocusing is sensitive to perturbations on distant butterfly spins, which allows one to measure the extent of polarization propagation through the spin network.”

Naturally, something this complicated needed a catchy nickname. The team came up with TARDIS, or Time-Accurate Reversal of Dipolar InteractionS. While that name captures the “out of time order” aspect of OTOC, it’s simply a set of control pulses sent to the NMR sample that starts a perturbation of the molecule’s network of nuclear spins. A second set of pulses then reflects an echo back to the source.

The reflections that return are imperfect, with noise coming from two sources. The first is simply imperfections in the control sequence, a limitation of the NMR hardware. But the second is the influence of fluctuations happening in distant atoms along the spin network. These happen at a certain frequency at random, or the researchers could insert a fluctuation by targeting a specific part of the molecule with randomized control signals.

The influence of what’s going on in these distant spins could allow us to use quantum echoes to tease out structural information at greater distances than we currently do with NMR. But to do so, we need an accurate model of how the echoes will propagate through the molecule. And again, that’s difficult to do with classical computations. But it’s very much within the capabilities of quantum computing, which the paper demonstrates.

Where things stand

For now, the team stuck to demonstrations on very simple molecules, making this work mostly a proof of concept. But the researchers are optimistic that there are many ways the system could be used to extract structural information from molecules at distances that are currently unobtainable using NMR. They list a lot of potential upsides that should be explored in the discussion of the paper, and there are plenty of smart people who would love to find new ways of using their NMR machines, so the field is likely to figure out pretty quickly which of these approaches turns out to be practically useful.

The fact that the demonstrations were done with small molecules, however, means that the modeling run on the quantum computer could also have been done on classical hardware (it only required 15 hardware qubits). So Google is claiming both quantum advantage and quantum utility, but not at the same time. The sorts of complex, long-distance interactions that would be out of range of classical simulation are still a bit beyond the reach of the current quantum hardware. O’Brien estimated that the hardware’s fidelity would have to improve by a factor of three or four to model molecules that are beyond classical simulation.

The quantum advantage issue should also be seen as a work in progress. Google has collaborated with enough researchers at enough institutions that there’s unlikely to be a major improvement in algorithms that could allow classical computers to catch up. Until the community as a whole has some time to digest the announcement, though, we shouldn’t take that as a given.

The other issue is verifiability. Some quantum algorithms will produce results that can be easily verified on classical hardware—situations where it’s hard to calculate the right result but easy to confirm a correct answer. Quantum echoes isn’t one of those, so we’ll need another quantum computer to verify the behavior Google has described.

But Google told Ars nothing is up to the task yet. “No other quantum processor currently matches both the error rates and number of qubits of our system, so our quantum computer is the only one capable of doing this at present,” the company said. (For context, Google says that the algorithm was run on up to 65 qubits, but the chip has 105 qubits total.)

There’s a good chance that other companies would disagree with that contention, but it hasn’t been possible to ask them ahead of the paper’s release.

In any case, even if this claim proves controversial, Google’s Michel Devoret, a recent Nobel winner, hinted that we shouldn’t have long to wait for additional ones. “We have other algorithms in the pipeline, so we will hopefully see other interesting quantum algorithms,” Devoret said.

Nature, 2025. DOI: 10.1038/s41586-025-09526-6 (About DOIs).

Google has a useful quantum algorithm that outperforms a supercomputer Read More »

2025 Nobel Prize in Physics awarded for macroscale quantum tunneling

Nobel Prize in Physics, nobel prizes, Physics, Quantum tunneling, quantum weirdness, Science / Tim Belzer / October 7, 2025

John Clarke, Michel H. Devoret, and John Martinis built an electrical circuit-based oscillator on a microchip.

A device consisting of four transmon qubits, four quantum buses, and four readout resonators fabricated by IBM in 2017. Credit: ay M. Gambetta, Jerry M. Chow & Matthias Steffen/CC BY 4.0

The 2025 Nobel Prize in Physics has been awarded to John Clarke, Michel H. Devoret, and John M. Martinis “for the discovery of macroscopic quantum tunneling and energy quantization in an electrical circuit.” The Nobel committee said during a media briefing that the laureates’ work provides opportunities to develop “the next generation of quantum technology, including quantum cryptography, quantum computers, and quantum sensors.” The three men will split the $1.1 million (11 million Swedish kroner) prize money. The presentation ceremony will take place in Stockholm on December 10, 2025.

“To put it mildly, it was the surprise of my life,” Clarke told reporters by phone during this morning’s press conference. “Our discovery in some ways is the basis of quantum computing. Exactly at this moment where this fits in is not entirely clear to me. One of the underlying reasons that cellphones work is because of all this work.”

When physicists began delving into the strange new realm of subatomic particles in the early 20th century, they discovered a realm where the old, deterministic laws of classical physics no longer apply. Instead, uncertainty reigns supreme. It is a world governed not by absolutes, but by probabilities, where events that would seem impossible on the macroscale occur on a regular basis.

For instance, subatomic particles can “tunnel” through seemingly impenetrable energy barriers. Imagine that an electron is a water wave trying to surmount a tall barrier. Unlike water, if the electron’s wave is shorter than the barrier, there is still a small probability that it will seep through to the other side.

This neat little trick has been experimentally verified many times. In the 1950s, physicists devised a system in which the flow of electrons would hit an energy barrier and stop because they lacked sufficient energy to surmount that obstacle. But some electrons didn’t follow the established rules of behavior. They simply tunneled right through the energy barrier.

(l-r): John Clarke, Michel H. Devoret and John M. Martinis — (l-r): John Clarke, Michel H. Devoret, and John M. Martinis. Credit: Niklas Elmehed/Nobel Prize Outreach

From subatomic to the macroscale

Clarke, Devoret, and Martinis were the first to demonstrate that quantum effects, such as quantum tunneling and energy quantization, can operate on macroscopic scales, not just one particle at a time.

After earning his PhD from University of Cambridge, Clarke came to the University of California, Berkeley, as a postdoc, eventually joining the faculty in 1969. By the mid-1980s, Devoret and Martinis had joined Clarke’s lab as a postdoc and graduate student, respectively. The trio decided to look for evidence of macroscopic quantum tunneling using a specialized circuit called a Josephson junction—a macroscopic device that takes advantage of a tunneling effect that is now widely used in quantum computing, quantum sensing, and cryptography.

A Josephson junction—named after British physicist Brian Josephson, who won the 1973 Nobel Prize in physics—is basically two semiconductor pieces separated by an insulating barrier. Despite this small gap between two conductors, electrons can still tunnel through the insulator and create a current. That occurs at sufficiently low temperatures, when the junction becomes superconducting as electrons form so-called “Cooper pairs.”

The team built an electrical circuit-based oscillator on a microchip measuring about one centimeter in size—essentially a quantum version of the classic pendulum. Their biggest challenge was figuring out how to reduce the noise in their experimental apparatus. For their experiments, they first fed a weak current into the junction and measured the voltage—initially zero. Then they increased the current and measured how long it took for the system to tunnel out of its enclosed state to produce a voltage.

Credit: Johan Jarnestad/The Royal Swedish Academy of Sciences

They took many measurements and found that the average current increased as the device’s temperature falls, as expected. But at some point, the temperature got so low that the device became superconducting and the average current became independent of the device’s temperature—a telltale signature of macroscopic quantum tunneling.

The team also demonstrated that the Josephson junction exhibited quantized energy levels—meaning the energy of the system was limited to only certain allowed values, just like subatomic particles can gain or lose energy only in fixed, discrete amounts—confirming the quantum nature of the system. Their discovery effectively revolutionized quantum science, since other scientists could now test precise quantum physics on silicon chips, among other applications.

Lasers, superconductors, and superfluid liquids exhibit quantum mechanical effects at the macroscale, but these arise by combining the behavior of microscopic components. Clarke, Devoret, and Martinis were able to create a macroscopic effect—a measurable voltage—from a macroscopic state. Their system contained billions of Cooper pairs filling the entire superconductor on the chip, yet all of them were described by a single wave function. They behave like a large-scale artificial atom.

In fact, their circuit was basically a rudimentary qubit. Martinis showed in a subsequent experiment that such a circuit could be an information-bearing unit, with the lowest energy state and the first step upward functioning as a 0 and a 1, respectively. This paved the way for such advances as the transmon in 2007: a superconducting charge qubit with reduced sensitivity to noise.

“That quantization of the energy levels is the source of all qubits,” said Irfan Siddiqi, chair of UC Berkeley’s Department of Physics and one of Devoret’s former postdocs. “This was the grandfather of qubits. Modern qubit circuits have more knobs and wires and things, but that’s just how to tune the levels, how to couple or entangle them. The basic idea that Josephson circuits could be quantized and were quantum was really shown in this experiment. The fact that you can see the quantum world in an electrical circuit in this very direct way was really the source of the prize.”

So perhaps it is not surprising that Martinis left academia in 2014 to join Google’s quantum computing efforts, helping to build a quantum computer the company claimed had achieved “quantum supremacy” in 2019. Martinis left in 2020 and co-founded a quantum computing startup, Qolab, in 2022. His fellow Nobel laureate, Devoret, now leads Google’s quantum computing division and is also a faculty member at the University of California, Santa Barbara. As for Clarke, he is now a professor emeritus at UC Berkeley.

“These systems bridge the gap between microscopic quantum behavior and macroscopic devices that form the basis for quantum engineering,” Gregory Quiroz, an expert in quantum information science and quantum algorithms at Johns Hopkins University, said in a statement. “The rapid progress in this field over the past few decades—in part fueled by their critical results—has allowed superconducting qubits to go from small-scale laboratory experiments to large-scale, multi-qubit devices capable of realizing quantum computation. While we are still on the hunt for undeniable quantum advantage, we would not be where we are today without many of their key contributions to the field.”

As is often the case with fundamental research, none of the three physicists realized at the time how significant their discovery would be in terms of its impact on quantum computing and other applications.

“This prize really demonstrates what the American system of science has done best,” Jonathan Bagger, CEO of the American Physical Society, told the New York Times. “It really showed the importance of the investment in research for which we do not yet have an application, because we know that sooner or later, there will be an application.”

2025 Nobel Prize in Physics awarded for macroscale quantum tunneling Read More »

Scientists unlock secret to thick, stable beer foams

beer, beer physics, fluid dynamics, foamy physics, Physics, Science / Kris Guyer / August 26, 2025

For many beer lovers, a nice thick head of foam is one of life’s pure pleasures, and the longer that foam lasts, the better the beer-drinking experience. A team of Swiss researchers spent seven years studying why some beer foams last longer than others and found that the degree of fermentation—i.e., whether a given beer has been singly, doubly, or triply fermented—is crucial, according to a new paper published in the journal Physics of Fluids.

As previously reported, foams are ubiquitous in everyday life, found in foods (whipped cream), beverages (beer, cappuccino), shaving cream and hair-styling mousse, packing peanuts, building insulation, flame-retardant materials, and so forth. All foams are the result of air being beaten into a liquid formula that contains some kind of surfactant (active surface agent), usually fats or proteins in edible foams, or chemical additives in non-edible products. That surfactant strengthens the liquid film walls of the bubbles to keep them from collapsing.

Individual bubbles typically form a sphere because that’s the shape with the minimum surface area for any volume and hence is the most energy-efficient. One reason for the minimizing principle when it comes to a bubble’s shape is that many bubbles can then tightly pack together to form a foam. But bubbles “coarsen” over time, the result of gravity pulling down on the liquid and thinning out the walls. Eventually, they start to look more like soccer balls (polyhedrons). In a coarsening foam, smaller bubbles are gradually absorbed by larger ones. There is less and less liquid to separate the individual bubbles, so they press together to fill the space.

This “jamming” is why foams are typically far more rigid than their gas (95 percent) and liquid (5 percent) components. The more tightly the bubbles jam together, the less they can move around and the greater the pressure inside them becomes, giving them properties of a solid.

Various factors can affect foam stability. For instance, in 2019, Japanese researchers investigated a phenomenon known as “collective bubble collapse,” or CBC, in which breaking one bubble at the edge of a foam results in a cascading effect as the breakage spreads to other bubbles in the foam. They identified two distinct mechanisms for the resulting CBCs: a so-called “propagating mode,” in which a broken bubble is absorbed into the liquid film, and a “penetrating mode,” in which the breakage of a bubble causes droplets to shoot off and hit other bubbles, causing them to break in turn.

Scientists unlock secret to thick, stable beer foams Read More »

Physics of badminton’s new killer spin serve

badminton, computational fluid dynamics, fluid dynamics, Physics, physics of sports, Science, sports science / Kris Guyer / August 19, 2025

Serious badminton players are constantly exploring different techniques to give them an edge over opponents. One of the latest innovations is the spin serve, a devastatingly effective method in which a player adds a pre-spin just before the racket contacts the shuttlecock (aka the birdie). It’s so effective—some have called it “impossible to return“—that the Badminton World Federation (BWF) banned the spin serve in 2023, at least until after the 2024 Paralympic Games in Paris.

The sanction wasn’t meant to quash innovation but to address players’ concerns about the possible unfair advantages the spin serve conferred. The BWF thought that international tournaments shouldn’t become the test bed for the technique, which is markedly similar to the previously banned “Sidek serve.” The BWF permanently banned the spin serve earlier this year. Chinese physicists have now teased out the complex fundamental physics of the spin serve, publishing their findings in the journal Physics of Fluids.

Shuttlecocks are unique among the various projectiles used in different sports due to their open conical shape. Sixteen overlapping feathers protrude from a rounded cork base that is usually covered in thin leather. The birdies one uses for leisurely backyard play might be synthetic nylon, but serious players prefer actual feathers.

Those overlapping feathers give rise to quite a bit of drag, such that the shuttlecock will rapidly decelerate as it travels and its parabolic trajectory will fall at a steeper angle than its rise. The extra drag also means that players must exert quite a bit of force to hit a shuttlecock the full length of a badminton court. Still, shuttlecocks can achieve top speeds of more than 300 mph. The feathers also give the birdie a slight natural spin around its axis, and this can affect different strokes. For instance, slicing from right to left, rather than vice versa, will produce a better tumbling net shot.

Chronophotographies of shuttlecocks after an impact with a racket. Credit: Caroline Cohen et al., 2015

The cork base makes the birdie aerodynamically stable: No matter how one orients the birdie, once airborne, it will turn so that it is traveling cork-first and will maintain that orientation throughout its trajectory. A 2015 study examined the physics of this trademark flip, recording flips with high-speed video and conducting free-fall experiments in a water tank to study how its geometry affects the behavior. The latter confirmed that shuttlecock feather geometry hits a sweet spot in terms of an opening inclination angle that is neither too small nor too large. And they found that feather shuttlecocks are indeed better than synthetic ones, deforming more when hit to produce a more triangular trajectory.

Physics of badminton’s new killer spin serve Read More »

Ice discs slingshot across a metal surface all on their own

fluid dynamics, Leidenfrost effect, materials science, Physics, reverse Leidenfrost effect, Science / Tim Belzer / August 14, 2025

VA Tech experiment was inspired by Death Valley’s mysterious “sailing stones” at Racetrack Playa.

Graduate student Jack Tapocik sets up ice on an engineered surface in the VA Tech lab of Jonathan Boreyko. Credit: Alex Parrish/Virginia Tech

Scientists have figured out how to make frozen discs of ice self-propel across a patterned metal surface, according to a new paper published in the journal ACS Applied Materials and Interfaces. It’s the latest breakthrough to come out of the Virginia Tech lab of mechanical engineer Jonathan Boreyko.

A few years ago, Boreyko’s lab experimentally demonstrated a three-phase Leidenfrost effect in water vapor, liquid water, and ice. The Leidenfrost effect is what happens when you dash a few drops of water onto a very hot, sizzling skillet. The drops levitate, sliding around the pan with wild abandon. If the surface is at least 400° Fahrenheit (well above the boiling point of water), cushions of water vapor, or steam, form underneath them, keeping them levitated. The effect also works with other liquids, including oils and alcohol, but the temperature at which it manifests will be different.

Boreyko’s lab discovered that this effect can also be achieved in ice simply by placing a thin, flat disc of ice on a heated aluminum surface. When the plate was heated above 150° C (302° F), the ice did not levitate on a vapor the way liquid water does. Instead, there was a significantly higher threshold of 550° Celsius (1,022° F) for levitation of the ice to occur. Unless that critical threshold is reached, the meltwater below the ice just keeps boiling in direct contact with the surface. Cross that critical point and you will get a three-phase Leidenfrost effect.

The key is a temperature differential in the meltwater just beneath the ice disc. The bottom of the meltwater is boiling, but the top of the meltwater sticks to the ice. It takes a lot to maintain such an extreme difference in temperature, and doing so consumes most of the heat from the aluminum surface, which is why it’s harder to achieve levitation of an ice disc. Ice can suppress the Leidenfrost effect even at very high temperatures (up to 550° C), which means that using ice particles instead of liquid droplets would be better for many applications involving spray quenching: rapid cooling in nuclear power plants, for example, firefighting, or rapid heat quenching when shaping metals.

This time around, Boreyko et al. have turned their attention to what the authors term “a more viscous analog” to a Leidenfrost ratchet, a form of droplet self-propulsion. “What’s different here is we’re no longer trying to levitate or even boil,” Boreyko told Ars. “Now we’re asking a more straightforward question: Is there a way to make ice move across the surface directionally as it is melting? Regular melting at room temperature. We’re not boiling, we’re not levitating, we’re not Leidenfrosting. We just want to know, can we make ice shoot across the surface if we design a surface in the right way?”

Mysterious moving boulders

The researchers were inspired by Death Valley’s famous “sailing stones” on Racetrack Playa. Watermelon-sized boulders are strewn throughout the dry lake bed, and they leave trails in the cracked earth as they slowly migrate a couple of hundred meters each season. Scientists didn’t figure out what was happening until 2014. Although co-author Ralph Lorenz (Johns Hopkins University) admitted he thought theirs would be “the most boring experiment ever” when they first set it up in 2011, two years later, the boulders did indeed begin to move while the playa was covered with a pond of water a few inches deep.

So Lorenz and his co-authors were finally able to identify the mechanism. The ground is too hard to absorb rainfall, and that water freezes when the temperature drops. When temperatures rise above freezing again, the ice starts to melt, creating ice rafts floating on the meltwater. And when the winds are sufficiently strong, they cause the ice rafts to drift along the surface.

A sailing stone in Death Valley's Racetrack Playa. — A sailing stone at Death Valley’s Racetrack Playa. Credit: Tahoenathan/CC BY-SA 3.0

“Nature had to have wind blowing to kind of push the boulder and the ice along the meltwater that was beneath the ice,” said Boreyko. “We thought, what if we could have a similar idea of melting ice moving directionally but use an engineered structure to make it happen spontaneously so we don’t have to have energy or wind or anything active to make it work?”

The team made their ice discs by pouring distilled water into thermally insulated polycarbonate Petrie dishes. This resulted in bottom-up freezing, which minimizes air bubbles in the ice. They then milled asymmetric grooves into uncoated aluminum plates in a herringbone pattern—essentially creating arrowhead-shaped channels—and then bonded them to hot plates heated to the desired temperature. Each ice disc was placed on the plate with rubber tongs, and the experiments were filmed from various angles to fully capture the disc behavior.

The herringbone pattern is the key. “The directionality is what really pushes the water,” Jack Tapocik, a graduate student in Boreyko’s lab, told Ars. “The herringbone doesn’t allow for water to flow backward, the water has to go forward, and that basically pushes the water and the ice together forward. We don’t have a treated surface, so the water just sits on top and the ice all moves as one unit.”

Boreyko draws an analogy to tubing on a river, except it’s the directional channels rather than gravity causing the flow. “You can see [in the video below] how it just follows the meltwater,” he said. “This is your classic entrainment mechanism where if the water flows that way and you’re floating on the water, you’re going to go the same way, too. It’s basically the same idea as what makes a Leidenfrost droplet also move one way: It has a vapor flow underneath. The only difference is that was a liquid drifting on a vapor flow, whereas now we have a solid drifting on a liquid flow. The densities and viscosities are different, but the idea is the same: You have a more dense phase that is drifting on the top of a lighter phase that is flowing directionally.”

Jonathan Boreyko/Virginia Tech

Next, the team repeated the experiment, this time coating the aluminum herringbone surface with water-repellant spray, hoping to speed up the disc propulsion. Instead, they found that the disc ended up sticking to the treated surface for a while before suddenly slingshotting across the metal plate.

“It’s a totally different concept with totally different physics behind it, and it’s so much cooler,” said Tapocik. “As the ice is melting on these coated surfaces, the water just doesn’t want to sit within the channels. It wants to sit on top because of the [hydrophobic] coating we have on there. The ice is directly sticking now to the surface, unlike before when it was floating. You get this elongated puddle in front. The easiest place [for the ice] to be is in the center of this giant, long puddle. So it re-centers, and that’s what moves it forward like a slingshot.”

Essentially, the water keeps expanding asymmetrically, and that difference in shape gives rise to a mismatch in surface tension because the amount of force that surface tension exerts on a body depends on curvature. The flatter puddle shape in front has less curvature than the smaller shape in back. As the video below shows, when the mismatch in surface tension becomes sufficiently strong, “It just rips the ice off the surface and flings it along,” said Boreyko. “In the future, we could try putting little things like magnets on top of the ice. We could probably put a boulder on it if we wanted to. The Death Valley effect would work with or without a boulder because it’s the floating ice raft that moves with the wind.”

Jonathan Boreyko/Virginia Tech

One potential application is energy harvesting. For example, one could pattern the metal surface in a circle rather than a straight line so the melting ice disk would continually rotate. Put magnets on the disk, and they would also rotate and generate power. One might even attach a turbine or gear to the rotating disc.

The effect might also provide a more energy-efficient means of defrosting, a longstanding research interest for Boreyko. “If you had a herringbone surface with a frosting problem, you could melt the frost, even partially, and use these directional flows to slingshot the ice off the surface,” he said. “That’s both faster and uses less energy than having to entirely melt the ice into pure water. We’re looking at potentially over a tenfold reduction in heating requirements if you only have to partially melt the ice.”

That said, “Most practical applications don’t start from knowing the application beforehand,” said Boreyko. “It starts from ‘Oh, that’s a really cool phenomenon. What’s going on here?’ It’s only downstream from that it turns out you can use this for better defrosting of heat exchangers for heat pumps. I just think it’s fun to say that we can make a little melting disk of ice very suddenly slingshot across the table. It’s a neat way to grab your attention and think more about melting and ice and how all this stuff works.”

DOI: ACS Applied Materials and Interfaces, 2025. 10.1021/acsami.5c08993 (About DOIs).

Ice discs slingshot across a metal surface all on their own Read More »

Misunderstood “photophoresis” effect could loft metal sheets to exosphere

engineering, materials science, photophoresis, Physics, Science / Kris Guyer / August 14, 2025

Photophoresis can generate a tiny bit of lift without any moving parts.

Image of a wooden stand holding a sealed glass bulb with a spinning set of vanes, each of which has a lit and dark side.

Most people would recognize the device in the image above, although they probably wouldn’t know it by its formal name: the Crookes radiometer. As its name implies, placing the radiometer in light produces a measurable change: the blades start spinning.

Unfortunately, many people misunderstand the physics of its operation (which we’ll return to shortly). The actual forces that drive the blades to spin, called photophoresis, can act on a variety of structures as long as they’re placed in a sufficiently low-density atmosphere. Now, a team of researchers has figured out that it may be possible to use the photophoretic effect to loft thin sheets of metal into the upper atmosphere of Earth and other planets. While their idea is to use it to send probes to the portion of the atmosphere that’s too high for balloons and too low for satellites, they have tested some working prototypes a bit closer to the Earth’s surface.

Photophoresis

It’s quite common—and quite wrong—to see explanations of the Crookes radiometer that involve radiation pressure. Supposedly, the dark sides of the blades absorb more photons, each of which carries a tiny bit of momentum, giving the dark side of the blades a consistent push. The problem with this explanation is that photons are bouncing off the silvery side, which imparts even more momentum. If the device were spinning due to radiation pressure, it would be turning in the opposite direction than it actually does.

An excess of the absorbed photons on the dark side is key to understanding how it works, though. Photophoresis operates through the temperature difference that develops between the warm, light-absorbing dark side of the blade and the cooler silvered side.

Any gas molecule that bumps into the dark side will likely pick up some of the excess thermal energy from it and move away from the blade faster than it arrived. At the sorts of atmospheric pressures we normally experience, these molecules don’t get very far before they bump into other gas molecules, which keeps any significant differences from developing.

But a Crookes radiometer is in a sealed glass container with a far lower air pressure. This allows the gas molecules to speed off much farther from the dark surface of the blade before they run into anything, creating an area of somewhat lower pressure at its surface. That causes gas near the surface of the shiny side to rush around and fill this lower-pressure area, imparting the force that starts the blades turning.

It’s pretty impressively inefficient in that sort of configuration, though. So people have spent a lot of time trying to design alternative configurations that can generate a bit more force. One idea with a lot of research traction is a setup that involves two thin metal sheets—one light, one dark—arranged parallel to each other. Both sheets would be heavily perforated to cut down on weight. And a subset of them would have a short pipe connecting holes on the top and bottom sheet. (This has picked up the nickname “nanocardboard.”)

These pipes would serve several purposes. One is to simply link the two sheets into a single unit. Another is to act as an insulator, keeping heat from moving from the dark sheet to the light one, and thus enhancing the temperature gradient. Finally, they provide a direct path for air to move from the top of the light-colored sheet to the bottom of the dark one, giving a bit of directed thrust to help keep the sheets aloft.

Optimization

As you might imagine, there are a lot of free parameters you can tweak: the size of the gap between the sheets, the density of perforations in them, the number of those holes that are connected by a pipe, and so on. So a small team of researchers developed a system to model different configurations and attempt to optimize for lift. (We’ll get to their motivations for doing so a bit later.)

Starting with a disk of nanocardboard, “The inputs to the model are the geometric, optical and thermal properties of the disk, ambient gas conditions, and external radiative heat fluxes on the disk,” as the researchers describe it. “The outputs are the conductive heat fluxes on the two membranes, the membrane temperatures, and the net photophoretic lofting force on the structure.” In general, the ambient gas conditions needed to generate lift are similar to the ones inside the Crookes radiometer: well below the air pressure at sea level.

The model suggested that three trends should influence any final designs. The first is that the density of perforations is a balance. At relatively low elevations (meaning a denser atmosphere), many perforations increase the stress on large sheets, but they decrease the stress for small items at high elevations. The other thing is that, rather than increasing with surface area, lift tends to drop because the sheets are more likely to equilibrate to the prevailing temperatures. A square millimeter of nanocardboard produces over 10 times more lift per surface area than a 10-square-centimeter piece of the same material.

Finally, the researchers calculate that the lift is at its maximum in the mesosphere, the area just above the stratosphere (50–100 kilometers above Earth’s surface).

Light and lifting

The researchers then built a few sheets of nanocardboard to test the output of their model. The actual products, primarily made of chromium, aluminum, and aluminum oxide, were incredibly light, weighing only a gram for a square meter of material. When illuminated by a laser or white LED, they generated measurable force on a testing device, provided the atmosphere was kept sufficiently sparse. With an exposure equivalent to sunlight, the device generated more than it weighed.

It’s a really nice demonstration that we can take a relatively obscure and weak physical effect and design devices that can levitate in the upper atmosphere, powered by nothing more than sunlight—which is pretty cool.

But the researchers have a goal beyond that. The mesophere turns out to be a really difficult part of the atmosphere to study. It’s not dense enough to support balloons or aircraft, but it still has enough gas to make quick work of any satellites. So the researchers really want to turn one of these devices into an instrument-carrying aircraft. Unfortunately, that would mean adding the structural components needed to hold instruments, along with the instruments themselves. And even in the mesosphere, where lift is optimal, these things do not generate much in the way of lift.

Plus, there’s the issue of getting them there, given that they won’t generate enough lift in the lower atmosphere, so they’ll have to be carried into the upper stratosphere by something else and then be released gently enough to not damage their fragile structure. And then, unless you’re lofting them during the polar summer, they will likely come floating back down at night.

None of this is to say this is an impossible dream. But there are definitely a lot of very large hurdles between the work and practical applications on Earth—much less on Mars, where the authors suggest the system could also be used to explore the mesosphere. But even if that doesn’t end up being realistic, this is still a pretty neat bit of physics.

Misunderstood “photophoresis” effect could loft metal sheets to exosphere Read More »

Scientists hid secret codes in light to combat video fakes

image processing, optics, photometric, Physics, Science, video manipulation / Rejus Almole / August 11, 2025

Hiding in the light

Previously, the Cornell team had figured out how to make small changes to specific pixels to tell if a video had been manipulated or created by AI. But its success depended on the creator of the video using a specific camera or AI model. Their new method, “noise-coded illumination” (NCI), addresses those and other shortcomings by hiding watermarks in the apparent noise of light sources. A small piece of software can do this for computer screens and certain types of room lighting, while off-the-shelf lamps can be coded via a small attached computer chip.

“Each watermark carries a low-fidelity time-stamped version of the unmanipulated video under slightly different lighting. We call these code videos,” Davis said. “When someone manipulates a video, the manipulated parts start to contradict what we see in these code videos, which lets us see where changes were made. And if someone tries to generate fake video with AI, the resulting code videos just look like random variations.” Because the watermark is designed to look like noise, it’s difficult to detect without knowing the secret code.

The Cornell team tested their method with a broad range of types of manipulation: changing warp cuts, speed and acceleration, for instance, and compositing and deep fakes. Their technique proved robust to things like signal levels below human perception; subject and camera motion; camera flash; human subjects with different skin tones; different levels of video compression; and indoor and outdoor settings.

“Even if an adversary knows the technique is being used and somehow figures out the codes, their job is still a lot harder,” Davis said. “Instead of faking the light for just one video, they have to fake each code video separately, and all those fakes have to agree with each other.” That said, Davis added, “This is an important ongoing problem. It’s not going to go away, and in fact it’s only going to get harder,” he added.

DOI: ACM Transactions on Graphics, 2025. 10.1145/3742892 (About DOIs).

Scientists hid secret codes in light to combat video fakes Read More »