Physics – Page 4

Physicists unlock another clue to brewing the perfect espresso

espresso, fluid dynamics, percolation, Physics, Science / Kris Guyer / March 18, 2025

The team initially tried to use a simple home coffee machine for their experiments but eventually partnered with Coffeelab, a major roaster in Poland, and CoffeeMachineSale, the largest global distributor of roasting gear. This brought industrial-grade equipment and much professional coffee expertise to the project: state-of-the-art grinders, for instance, and a cafe-grade espresso machine, tricked out with a pressure sensor, flow meter, and a set of scales. The entire setup was connected to laboratory laptops via a microchip and controlled with custom software that allowed the scientists to precisely monitor pressure, mass, and water flowing through the coffee.

The scientists measured the total dissolved solids to determine the rate at which coffee is dissolved, comparing brews without a channel to those with artificially induced channels. They found that, indeed, channeling adversely affected extraction yields. However, channeling does not have an impact on the rate at which water flows through the espresso puck.

“That is mostly due to the structural rearrangement of coffee grounds under pressure,” Lisicki said. “When the dry coffee puck is hit with water under high pressure—as high as 10 times the atmospheric pressure, so roughly the pressure 100 meters below the sea surface—it compacts and swells up. So even though water can find a preferential path, there is still significant resistance limiting the flow.”

The team is now factoring their results into numerical and theoretical models of porous bed extraction. They are also compiling an atlas of the different kinds of espresso pucks based on micro-CT imaging of the coffee.

“What we have found can help the coffee industry brew with more knowledge,” said Myck. “Many people follow procedures based on unconfirmed intuitions or claims which prove to have confirmation. What’s more, we have really interesting data regarding pressure-induced flow in coffee, the results of which have been a surprise to us as well. Our approach may let us finally understand the magic that happens inside your coffee machine.”

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Small charges in water spray can trigger the formation of key biochemicals

biochemistry, Biology, chemistry, origin of life, Physics, Science / Mike M. / March 15, 2025

Once his team nailed how droplets become electrically charged and how the micro-lightning phenomenon works, they recreated the Miller-Urey experiment. Only without the spark plugs.

Ingredients of life

After micro-lightnings started jumping between droplets in a mixture of gases similar to that used by Miller and Urey, the team examined their chemical composition with a mass spectrometer. They confirmed glycine, uracil, urea, cyanoethylene, and lots of other chemical compounds were made. “Micro-lightnings made all organic molecules observed previously in the Miller-Urey experiment without any external voltage applied,” Zare claims.

But does it really bring us any closer to explaining the beginnings of life? After all, Miller and Urey already demonstrated those molecules could be produced by electrical discharges in a primordial Earth’s atmosphere—does it matter all that much where those discharges came from? Zare argues that it does.

“Lightning is intermittent, so it would be hard for these molecules to concentrate. But if you look at waves crashing into rocks, you can think the spray would easily go into the crevices in these rocks,” Zare suggests. He suggests that the water in these crevices would evaporate, new spray would enter and evaporate again and again. The cyclic drying would allow the chemical precursors to build into more complex molecules. “When you go through such a dry cycle, it causes polymerization, which is how you make DNA,” Zare argues. Since sources of spray were likely common on the early Earth, Zare thinks this process could produce far more organic chemicals than potential alternatives like lightning strikes, hydrothermal vents, or impacting comets.

But even if micro-lightning really produced the basic building blocks of life on Earth, we’re still not sure how those combined into living organisms. “We did not make life. We just demonstrated a possible mechanism that gives us some chemical compounds you find in life,” Zare says. “It’s very important to have a lot of humility with this stuff.”

Science Advances, 2025. DOI: 10.1126/sciadv.adt8979

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D-Wave quantum annealers solve problems classical algorithms struggle with

algorithm, Computer science, D-Wave, ising model, Physics, quantum annealing, quantum computing, quantum mechanics, Science / Paul Patrick / March 13, 2025

The latest claim of a clear quantum supremacy solves a useful problem.

Right now, quantum computers are small and error-prone compared to where they’ll likely be in a few years. Even within those limitations, however, there have been regular claims that the hardware can perform in ways that are impossible to match with classical computation (one of the more recent examples coming just last year). In most cases to date, however, those claims were quickly followed by some tuning and optimization of classical algorithms that boosted their performance, making them competitive once again.

Today, we have a new entry into the claims department—or rather a new claim by an old entry. D-Wave is a company that makes quantum annealers, specialized hardware that is most effective when applied to a class of optimization problems. The new work shows that the hardware can track the behavior of a quantum system called an Ising model far more efficiently than any of the current state-of-the-art classical algorithms.

Knowing what will likely come next, however, the team behind the work writes, “We hope and expect that our results will inspire novel numerical techniques for quantum simulation.”

Real physics vs. simulation

Most of the claims regarding quantum computing superiority have come from general-purpose quantum hardware, like that of IBM and Google. These can solve a wide range of algorithms, but have been limited by the frequency of errors in their qubits. Those errors also turned out to be the reason classical algorithms have often been able to catch up with the claims from the quantum side. They limit the size of the collection of qubits that can be entangled at once, allowing algorithms that focus on interactions among neighboring qubits to perform reasonable simulations of the hardware’s behavior.

In any case, most of these claims have involved quantum computers that weren’t solving any particular algorithm, but rather simply behaving like a quantum computer. Google’s claims, for example, are based around what are called “random quantum circuits,” which is exactly what it sounds like.

Off in its own corner is a company called D-Wave, which makes hardware that relies on quantum effects to perform calculations, but isn’t a general-purpose quantum computer. Instead, its collections of qubits, once configured and initialized, are left to find their way to a ground energy state, which will correspond to a solution to a problem. This approach, called quantum annealing, is best suited to solving problems that involve finding optimal solutions to complex scheduling problems.

D-Wave was likely to have been the first company to experience the “we can outperform classical” followed by an “oh no you can’t” from algorithm developers, and since then it has typically been far more circumspect. In the meantime, a number of companies have put D-Wave’s computers to use on problems that align with where the hardware is most effective.

But on Thursday, D-Wave will release a paper that will once again claim, as its title indicates, “beyond classical computation.” And it will be doing it on a problem that doesn’t involve random circuits.

You sing, Ising

The new paper describes using D-Wave’s hardware to compute the evolution over time of something called an Ising model. A simple version of this model is a two-dimensional grid of objects, each of which can be in two possible states. The state that any one of these objects occupies is influenced by the state of its neighbors. So, it’s easy to put an Ising model into an unstable state, after which values of the objects within it will flip until it reaches a low-energy, stable state. Since this is also a quantum system, however, random noise can sometimes flip bits, so the system will continue to evolve over time. You can also connect the objects into geometries that are far more complicated than a grid, allowing more complex behaviors.

Someone took great notes from a physics lecture on Ising models that explains their behavior and role in physics in more detail. But there are two things you need to know to understand this news. One is that Ising models don’t involve a quantum computer merely acting like an array of qubits—it’s a problem that people have actually tried to find solutions to. The second is that D-Wave’s hardware, which provides a well-connected collection of quantum devices that can flip between two values, is a great match for Ising models.

Back in 2023, D-Wave used its 5,000-qubit annealer to demonstrate that its output when performing Ising model evolution was best described using Schrödinger’s equation, a central way of describing the behavior of quantum systems. And, as quantum systems become increasingly complex, Schrödinger’s equation gets much, much harder to solve using classical hardware—the implication being that modeling the behavior of 5,000 of these qubits could quite possibly be beyond the capacity of classical algorithms.

Still, having been burned before by improvements to classical algorithms, the D-Wave team was very cautious about voicing that implication. As they write in their latest paper, “It remains important to establish that within the parametric range studied, despite the limited correlation length and finite experimental precision, approximate classical methods cannot match the solution quality of the [D-Wave hardware] in a reasonable amount of time.”

So it’s important that they now have a new paper that indicates that classical methods in fact cannot do that in a reasonable amount of time.

Testing alternatives

The team, which is primarily based at D-Wave but includes researchers from a handful of high-level physics institutions from around the world, focused on three different methods of simulating quantum systems on classical hardware. They were put up against a smaller version of what will be D-Wave’s Advantage 2 system, designed to have a higher qubit connectivity and longer coherence times than its current Advantage. The work essentially involved finding where the classical simulators bogged down as either the simulation went on for too long, or the complexity of the Ising model’s geometry got too high (all while showing that D-Wave’s hardware could perform the same calculation).

Three different classical approaches were tested. Two of them involved a tensor network, one called MPS, for matrix product of states, and the second called projected entangled-pair states (PEPS). They also tried a neural network, as a number of these have been trained successfully to predict the output of Schrödinger’s equation for different systems.

These approaches were first tested on a simple 8×8 grid of objects rolled up into a cylinder, which increases the connectivity by eliminating two of the edges. And, for this simple system that evolved over a short period, the classical methods and the quantum hardware produced answers that were effectively indistinguishable.

Two of the classical algorithms, however, were relatively easy to eliminate from serious consideration. The neural network provided good results for short simulations but began to diverge rapidly once the system was allowed to evolve for longer times. And PEPS works by focusing on local entanglement and failed as entanglement was spread to ever-larger systems. That left MPS as the classical representative as more complex geometries were run for longer times.

By identifying where MPS started to fail, the researchers could estimate the amount of classical hardware that would be needed to allow the algorithm to keep pace with the Advantage 2 hardware on the most complex systems. And, well, it’s not going to be realistic any time soon. “On the largest problems, MPS would take millions of years on the Frontier supercomputer per input to match [quantum hardware] quality,” they conclude. “Memory requirements would exceed its 700PB storage, and electricity requirements would exceed annual global consumption.” By contrast, it took a few minutes on D-Wave’s hardware.

Again, in the paper, the researchers acknowledge that this may lead to another round of optimizations that bring classical algorithms back into competition. And, apparently those have already started once a draft of this upcoming paper was placed on the arXiv. At a press conference happening as this report was being prepared, one of D-Wave’s scientists, Andrew King, noted that two pre-prints have already appeared on the arXiv that described improvements to classical algorithms.

While these allow classical simulations to perform more of the results demonstrated in the new paper, they don’t involve simulating the most complicated geometries, and require shorter times and fewer total qubits. Nature talked to one of the people behind these algorithm improvements, who was optimistic that they could eventually replicate all of D-Wave’s results using non-quantum algorithms. D-Wave, obviously, is skeptical. And King said that a new, larger Advantage 2 test chip with over 4,000 qubits available had recently been calibrated, and he had already tested even larger versions of these same Ising models on it—ones that would be considerably harder for classical methods to catch up to.

In any case, the company is acting like things are settled. During the press conference describing the new results, people frequently referred to D-Wave having achieved quantum supremacy, and its CEO, Alan Baratz, in responding to skepticism sparked by the two draft manuscripts, said, “Our work should be celebrated as a significant milestone.”

Science, 2025. DOI: 10.1126/science.ado6285 (About DOIs).

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.

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These hot oil droplets can bounce off any surface

bouncing droplets, inverse leidenfrost effect, Leidenfrost effect, Physics, Science / Tim Belzer / March 4, 2025

The Hong Kong physicists were interested in hot droplets striking cold surfaces. Prior research showed there was less of a bouncing effect in such cases involving heated water droplets, with the droplets sticking to the surface instead thanks to various factors such as reduced droplet surface tension. The Hong Kong team discovered they could achieve enhanced bouncing by using hot droplets of less volatile liquids—namely, n-hexadecane, soybean oil, and silicon oil, which have lower saturation pressures compared to water.

Follow the bouncing droplet

The researchers tested these hot droplets (as well as burning and normal temperature droplets) on various solid, cold surfaces, including scratched glass, smooth glass, acrylic surfaces, surfaces with liquid-repellant coatings from candle soot, and surfaces coated with nanoparticles with varying “wettability” (i.e., how well particles stick to the surface). They captured the droplet behavior with both high-speed and thermal cameras, augmented with computer modeling.

The room-temperature droplets stuck to all the surfaces as expected, but the hot and burning droplets bounced. The team found that the bottom of a hot droplet cools faster than the top as it approaches a room-temperature surface, which causes hotter liquid within the droplet to flow from the edges toward the bottom. The air that is dragged to the bottom with it forms a thin cushion there and prevents the droplet from making contact with the surface, bouncing off instead. They dubbed the behavior “self-lubricated bouncing.”

“It is now clear that droplet-bouncing strategies are not isolated to engineering the substrate and that the thermophysical properties of droplets themselves are critical,” Jonathan B. Boreyko of Virginia Tech, who was not involved in the research, wrote in an accompanying commentary.

Future applications include improving the combustion efficiency of fuels or developing better fire-retardant coatings. “If burning droplets can’t stick to surfaces, they won’t be able to ignite new materials and allow fires to propagate,” co-author Pingan Zhu said. “Our study could help protect flammable materials like textiles from burning droplets. Confining fires to a smaller area and slowing their spread could give firefighters more time to put them out.”

DOI: Newton, 2025. 10.1016/j.newton.2025.100014 (About DOIs).

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Research roundup: 7 cool science stories from February

ancient egypt, fluid dynamics, Herculaneum scrolls, Physics, research roundup, Science / Mike M. / March 1, 2025

Dancing sea turtles, the discovery of an Egyptian pharaoh’s tomb, perfectly boiled eggs, and more.

X-ray image of the PHerc.172 scroll Credit: Vesuvius Challenge

It’s a regrettable reality that there is never 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. February’s list includes dancing sea turtles, the secret to a perfectly boiled egg, the latest breakthrough in deciphering the Herculaneum scrolls, the discovery of an Egyptian pharaoh’s tomb, and more.

Dancing sea turtles

There is growing evidence that certain migratory animal species (turtles, birds, some species of fish) are able to exploit the Earth’s magnetic field for navigation, using it both as a compass to determine direction and as a kind of “map” to track their geographical position while migrating. A paper published in the journal Nature offers evidence of a possible mechanism for this unusual ability, at least in loggerhead sea turtles, who perform an energetic “dance” when they follow magnetic fields to a tasty snack.

Sea turtles make impressive 8,000-mile migrations across oceans and tend to return to the same feeding and nesting sites. The authors believe they achieve this through their ability to remember the magnetic signature of those areas and store them in a mental map. To test that hypothesis, the scientists placed juvenile sea turtles into two large tanks of water outfitted with large coils to create magnetic signatures at specific locations within the tanks. One tank features such a location that had food; the other had a similar location without food.

They found that the sea turtles in the first tank performed distinctive “dancing” moves when they arrived at the area associated with food: tilting their bodies, dog-paddling, spinning in place, or raising their head near or above the surface of the water. When they ran a second experiment using different radio frequencies, they found that the change interfered with the turtles’ internal compass, and they could not orient themselves while swimming. The authors concluded that this is compelling evidence that the sea turtles can distinguish between magnetic fields, possibly relying on complex chemical reactions, i.e., “magnetoreception.” The map sense, however, likely relies on a different mechanism.

Nature, 2025. DOI: 10.1038/s41586-024-08554-y (About DOIs).

Long-lost tomb of Thutmose II

Archaeologists found a simple tomb near Luxor and identified it as the 3,500-year-old burial site of King Thutmose II. Credit: Egypt’s Ministry of Tourism and Antiquities

Thutmose II was the fourth pharaoh of the Tutankhamun (18th) dynasty. He reigned only about 13 years and married his half-sister Hatshepsut (who went on to become the sixth pharaoh in the dynasty). Archaeologists have now confirmed that a tomb built underneath a waterfall in the mountains in Luxor and discovered in 2022 is the final resting place of Thutmose II. It’s the last of the 18th dynasty royal tombs to be found, more than a century after Tutankhamun’s tomb was found in 1922.

When it was first found, archaeologists thought the tomb might be that of a king’s wife, given its close proximity to Hatshepsut’s tomb and those of the wives of Thutmose III. But they found fragments of alabaster vases inscribed with Thutmose II’s name, along with scraps of religious burial texts and plaster fragments on the partially intact ceiling with traces of blue paint and yellow stars—typically only found in kings’ tombs. Something crucial was missing, however: the actual mummy and grave goods of Thutmose II.

It’s long been assumed that the king’s mummy was discovered in the 19th century at another site called Deir el-Bahari. But archaeologist Piers Litherland, who headed the British team that discovered the tomb, thinks that identification was in error. An inscription stated that Hatshepsut had the tomb’s contents relocated due to flooding. Litherland believes the pharaoh’s actual mummy is buried in a second tomb. Confirmation (or not) of his hypothesis won’t come until after archaeologists finish excavating what he thinks is the site of that second tomb, which is currently buried under multiple layers of rock and plaster.

Hidden images in Pollock paintings

“Troubled Queen” reveals a “hidden” figure, possibly a soldier. Credit: D.A. Morrissette et al., CNS Spectrums 2025

Physicists have long been fascinated by the drip paintings of “splatter master” Jackson Pollock, pondering the presence of fractal patterns (or lack thereof), as well as the presence of curls and coils in his work and whether the artist deliberately exploited a well-known fluid dynamics effect to achieve them—or deliberately avoided them. Now psychiatrists are getting into the game, arguing in a paper published in CNS Spectrums that Pollock—known to incorporate images into his early pre-drip paintings—also used many of the same images repeatedly in his later abstract drip paintings.

People have long claimed to see images in those drip paintings, but the phenomenon is usually dismissed by art critics as a trick of human perception, much like the fractal edges of Rorschach ink blots can fool the eye and mind. The authors of this latest paper analyzed Pollock’s early painting “Troubled Queen” and found multiple images incorporated into the painting, which they believe establishes a basis for their argument that Pollock also incorporated such images into his later drip painting, albeit possibly subconsciously.

“Seeing an image once in a drip painting could be random,” said co-author Stephen M. Stahl of the University of California, San Diego. “Seeing the same image twice in different paintings could be a coincidence. Seeing it three or more times—as is the case for booze bottles, monkeys and gorillas, elephants, and many other subjects and objects in Pollock’s paintings—makes those images very unlikely to be randomly provoked perceptions without any basis in reality.”

CNS Spectrums, 2025. DOI: 10.1017/S1092852924001470

Solving a fluid dynamics mystery

Soap opera in the maze: Geometry matters in Marangoni flows.

Every fall, the American Physical Society exhibits a Gallery of Fluid Motion, which recognizes the innate artistry of images and videos derived from fluid dynamics research. Several years ago, physicists at the University of California, Santa Barbara (UCSB) submitted an entry featuring a pool of red dye, propelled by a few drops of soap acting as a surfactant, that seemed to “know” how to solve a maze whose corridors were filled with milk. This is unusual since one would expect the dye to diffuse more uniformly. The team has now solved that puzzle, according to a paper published in Physical Review Letters.

The key factor is surface tension, specifically a phenomenon known as the Marangoni effect, which also drives the “coffee ring effect” and the “tears of wine” phenomenon. If you spread a thin film of water on your kitchen counter and place a single drop of alcohol in the center, you’ll see the water flow outward, away from the alcohol. The difference in their alcohol concentrations creates a surface tension gradient, driving the flow.

In the case of the UCSB experiment, the soap reduces local surface tension around the red dye to set the dye in motion. There are also already surfactants in the milk that work in combination with the soapy surfactant to “solve” the maze. The milk surfactants create varying points of resistance as the dye makes its way through the maze. A dead end or a small space will have more resistance, redirecting the dye toward routes with less resistance—and ultimately to the maze’s exit. “That means the added surfactant instantly knows the layout of the maze,” said co-author Paolo Luzzatto-Fegiz.

Physical Review Letters, 2025. DOI: 10.1073/pnas.1802831115

How to cook a perfectly boiled egg

There’s more than one way to boil an egg, whether one likes it hard-boiled, soft-boiled, or somewhere in between. The challenge is that eggs have what physicists call a “two-phase” structure: The yolk cooks at 65° Celsius, while the white (albumen) cooks at 85° Celsius. This often results in overcooked yolks or undercooked whites when conventional methods are used. Physicists at the Italian National Research Council think they’ve cracked the case: The perfectly cooked egg is best achieved via a painstaking process called “periodic cooking,” according to a paper in the journal Communications Engineering.

They started with a few fluid dynamics simulations to develop a method and then tested that method in the laboratory. The process involves transferring a cooking egg every two minutes—for 32 minutes—between a pot of boiling water (100° Celsius) and a bowl of cold water (30° Celsius). They compared their periodically cooked eggs with traditionally prepared hard-boiled and soft-boiled eggs, as well as eggs prepared using sous vide. The periodically cooked eggs ended up with soft yolks (typical of sous vide eggs) and a solidified egg white with a consistency between sous vide and soft-boiled eggs. Chemical analysis showed the periodically cooked eggs also contained more healthy polyphenols. “Periodic cooking clearly stood out as the most advantageous cooking method in terms of egg nutritional content,” the authors concluded.

Communications Engineering, 2025. DOI: 10.1038/s44172-024-00334-w

More progress on deciphering Herculaneum scrolls

X-ray scans and AI reveal the inside of ancient scroll — X-ray scans and AI reveal the inside of an ancient scroll. Credit: Vesuvius Challenge

The Vesuvius Challenge is an ongoing project that employs “digital unwrapping” and crowd-sourced machine learning to decipher the first letters from previously unreadable ancient scrolls found in an ancient Roman villa at Herculaneum. The 660-plus scrolls stayed buried under volcanic mud until they were excavated in the 1700s from a single room that archaeologists believe held the personal working library of an Epicurean philosopher named Philodemus. The badly singed, rolled-up scrolls were so fragile that it was long believed they would never be readable, as even touching them could cause them to crumble.

In 2023, the Vesuvius Challenge made its first award for deciphering the first letters, and last year, the project awarded the grand prize of $700,000 for producing the first readable text. The latest breakthrough is the successful generation of the first X-ray image of the inside of a scroll (PHerc. 172) housed in Oxford University’s Bodleian Libraries—a collaboration with the Vesuvius Challenge. The scroll’s ink has a unique chemical composition, possibly containing lead, which means it shows up more clearly in X-ray scans than other Herculaneum scrolls that have been scanned.

The machine learning aspect of this latest breakthrough focused primarily on detecting the presence of ink, not deciphering the characters or text. Oxford scholars are currently working to interpret the text. The first word to be translated was the Greek word for “disgust,” which appears twice in nearby columns of text. Meanwhile, the Vesuvius Challenge collaborators continue to work to further refine the image to make the characters even more legible and hope to digitally “unroll” the scroll all the way to the end, where the text likely indicates the title of the work.

What ancient Egyptian mummies smell like

mummified bodies in the exhibition area of the Egyptian museum in Cairo. — Mummified bodies in the exhibition area of the Egyptian Museum in Cairo. Credit: Emma Paolin

Much of what we know about ancient Egyptian embalming methods for mummification comes from ancient texts, but there are very few details about the specific spices, oils, resins, and other ingredients used. Science can help tease out the secret ingredients. For instance, a 2018 study analyzed organic residues from a mummy’s wrappings with gas chromatography-mass spectrometry and found that the wrappings were saturated with a mixture of plant oil, an aromatic plant extract, a gum or sugar, and heated conifer resin. Researchers at University College London have now identified the distinctive smells associated with Egyptian mummies—predominantly”woody,” “spicy,” and “sweet,” according to a paper published in the Journal of the American Chemical Society.

The team coupled gas chromatography with mass spectrometry to measure chemical molecules emitted by nine mummified bodies on display at the Egyptian Museum in Cairo and then asked a panel of trained human “sniffers” to describe the samples smells, rating them by quality, intensity, and pleasantness. This enabled them to identify whether a given odor molecule came from the mummy itself, conservation products, pesticides, or the body’s natural deterioration. The work offers additional clues into the materials used in mummification, as well as making it possible for the museum to create interactive “smellscapes” in future displays so visitors can experience the scents as well as the sights of ancient Egyptian mummies.

Journal of the American Chemical Society, 2025. DOI: 10.1021/jacs.4c15769

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.

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Amazon uses quantum “cat states” with error correction

Amazon, cat state, Computer science, Physics, quantum computing, quantum mechanics, qubits, Science, transmon / Paul Patrick / February 27, 2025

The company shows off a mix of error-resistant hardware and error correction.

Following up on Microsoft’s announcement of a qubit based on completely new physics, Amazon is publishing a paper describing a very different take on quantum computing hardware. The system mixes two different types of qubit hardware to improve the stability of the quantum information they hold. The idea is that one type of qubit is resistant to errors, while the second can be used for implementing an error-correction code that catches the problems that do happen.

While there have been more effective demonstrations of error correction in the past, a number of companies are betting that Amazon’s general approach is the best route to getting logical qubits that are capable of complex algorithms. So, in that sense, it’s an important proof of principle.

Herding cats

The basic idea behind Amazon’s approach is to use one type of qubit to hold data and a second to enable error correction. The data qubit is extremely resistant to one type of error, but prone to a second. Those errors are where the second type of qubit comes in; it’s used to run an error-correction code that’s effective at picking up the problems the data qubits are prone to. Combined, the two are hoped to allow error correction to be handled by far fewer hardware qubits.

In a standard computer, there’s really only one type of error to worry about: a bit that no longer holds the value it was set to. This is called a bit flip, since the value goes from either zero to one, or one to zero. As with most things quantum computing, things are considerably more complicated with qubits. Since they don’t hold binary values, but rather probabilities, you can’t just flip the value of the qubit. Instead, bit flips in quantum land involve inverting the probabilities—going from 60: 40 to 40: 60 or similar.

But bit flips aren’t the only problems that can occur. Qubits can also suffer from what are called phase flip errors. These have no equivalent in classical computers, but they can also keep quantum computers from operating as expected.

In the past, Amazon demonstrated qubits that made it trivially easy to detect when a bit flip error occurred. For the new work, they moved on to something different: a qubit that greatly reduces the probability of bit flip errors.

They do this by using what are called “cat qubits,” after the famed Schrödinger’s cat, which existed in two states at once. While most qubits are based on a single quantum object being placed in this sort of superposition of states, a cat qubit has a collection of objects in a single superposition. (Put differently, the superposition state is distributed across the collection of objects.) In the case of the cat qubits demonstrated so far by companies like Alice and Bob, the objects are photons, which are all held in a single resonator, and Amazon is using similar tech.

Cat qubits have a distinctive feature compared to other options: bit flips are improbable, and get even less probable as you pump more photons into the resonator. But this has a drawback: more photons mean that phase flips become more probable.

Flipping cats

Those phase flips are why a second set of qubits, called transmons were brought in. (Transmons are a commonly used type of qubit based on a loop of superconducting wire linked to a microwave resonator and used by companies like IBM and Google.) These were used to create a chain of qubits, alternating between cat and transmon. This allowed the team to create a logical, error-corrected qubit using a simple error-correction code called a repetition code.

Image of a zig-zagging chain of alternating orange and blue circles. — The layout of Amazon’s hardware. Data-holding cat qubits (blue) alternate with transmons (orange), which can be measured to detect errors. Credit: Putterman et. al.

Here, each of the cat qubits starts off in the same state and is entangled with its neighboring transmons. This allowed the transmons to track what was going on in the cat qubits by performing what are called weak measurements. These don’t destroy the quantum state like a full measurement would but can allow the detection of changes in the neighboring cat qubits and provide the information needed to fix any errors.

So, the combination of the two means that almost all the errors that occur are phase flips, and the phase flips are detected and fixed.

In more typical error-correction schemes, you need enough qubits around to do measurements to identify both the location of an error and the nature of the error (phase or bit flip). Here, Amazon is assuming all errors are phase flips, and its team can identify the location of the flip based on which of the transmons detects an error, as shown by the red flags in the diagram above. It allows for a logical qubit that uses far fewer hardware qubits and measurements to get a given level of error correction.

The challenge of any error-correction setup is that each hardware qubit involved is error-prone. Adding too many into the error-correction system will mean that multiple errors are likely to occur simultaneously in a way that causes error correction to become impossible. Once the error rate of the hardware qubits gets low enough, however, adding additional qubits will bring the error rate down.

So, the key measurement done here is comparing a chain that has three cat qubits and two transmons to one that has five cat qubits and four transmons. These measurements showed that the five qubit chain had a lower error rate than the smaller one. This shows that the hardware is now at a state where error correction provides a benefit.

The characterization of the system indicated a couple of major limits, though. Cat qubits make bit flips extremely unlikely, but not impossible. By focusing error correction only on phase flips, any bit flips that do occur inescapably trigger the failure of the entire logical, error-corrected qubit. “Achieving long logical bit-flip times is challenging because any single cat qubit bit flip event in any part of the repetition code directly causes a logical bit flip error,” the authors note. The other issue is that the transmons used for error correction still suffer from both bit and phase flips, which can also mess up the entire error-corrected qubit.

Where does this leave us?

There are a number of companies like Amazon that are betting that using a somehow less error-prone hardware qubit will allow them to get effective error correction using fewer total hardware qubits. If they’re correct, they’ll be able to build error-corrected quantum computers using far fewer qubits, and so potentially perform useful computation sooner. For them, this paper is an important validation of the idea. You can do a sort of mixed-mode error correction, with a robust hardware qubit paired with a compact error-correction code.

But beyond that, the messages are pretty mixed. The hardware still had to rely on less robust hardware qubits (the transmons) to do error correction, and the very low error rate was still not low enough to avoid having occasional bit flips. And, ultimately, the error rate improvements gained by increasing the size of the logical qubit aren’t on a trajectory that would get you a useful level of error correction without needing an unrealistically large number of hardware qubits.

In short, the underlying hardware isn’t currently good enough to enable any sort of complex calculation, and it would need radical improvements before it can be. And there’s not an obvious alternate route to effective error correction. The potential of this approach is still there, but it’s not obvious how we’re going to build hardware that lives up to that potential.

As for Amazon, the picture is even less clear, given that this is the second qubit technology that it has talked about publicly. It’s unclear whether the company is going to go all-in on this approach, or is still looking for a technology that it’s willing to commit to.

Nature, 2025. DOI: 10.1038/s41586-025-08642-7 (About DOIs).

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Scientists unlock vital clue to strange quirk of static electricity

electromagnetism, Physics, Science, static electricity, triboelectric effect / Mike M. / February 19, 2025

Scientists can now explain the prevailing unpredictability of contact electrification, unveiling order from what has long been considered chaos.

Static electricity—specifically the triboelectric effect, aka contact electrification—is ubiquitous in our daily lives, found in such things as a balloon rubbed against one’s hair or styrofoam packing peanuts sticking to a cat’s fur (as well as human skin, glass tabletops, and just about anywhere you don’t want packing peanuts to be). The most basic physics is well understood, but long-standing mysteries remain, most notably how different materials exchange positive and negative charges—sometimes ordering themselves into a predictable series, but sometimes appearing completely random.

Now scientists at the Institute of Science and Technology Austria (ISTA) have identified a critical factor explaining that inherent unpredictability: It’s the contact history of given materials that controls how they exchange charges in contact electrification. They described their findings in a new paper published in the journal Nature.

Johan Carl Wilcke published the first so-called “triboelectric series” in 1757 to describe the tendency of different materials to self-order based on how they develop a positive or negative charge. A material toward the bottom of the list, like hair, will acquire a more negative charge when it comes into contact with a material near the top of the list, like a rubber balloon.

The issue with all these lists is that they are inconsistent and unpredictable—sometimes the same scientists don’t get the same ordering results twice when repeating experiments—largely because there are so many confounding factors that can come into play. “Understanding how insulating materials exchanged charge seemed like a total mess for a very long time,” said co-author Scott Waitukaitis of ISTA. “The experiments are wildly unpredictable and can sometimes seem completely random.”

A cellulose material’s charge sign, for instance, can depend on whether its curvature is concave or convex. Two materials can exchange charge from positive (A) to negative (B), but that exchange can reverse over time, with B being positive and A being negative. And then there are “triangles”: Sometimes one material (A) gains a positive charge when rubbed up against another material (B), but B will gain a positive charge when rubbed against a third material (C), and C, in turn, will gain positive charge when in contact with A. Even identical materials can sometimes exchange charge upon contact.

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Microsoft demonstrates working qubits based on exotic physics

Apple, Computer science, Majorana, Physics, quantum computing, quantum mechanics, quasiparticles, Science / Kris Guyer / February 19, 2025

Microsoft’s first entry into quantum hardware comes in the form of Majorana 1, a processor with eight of these qubits.

Given that some of its competitors have hardware that supports over 1,000 qubits, why does the company feel it can still be competitive? Nayak described three key features of the hardware that he feels will eventually give Microsoft an advantage.

The first has to do with the fundamental physics that governs the energy needed to break apart one of the Cooper pairs in the topological superconductor, which could destroy the information held in the qubit. There are a number of ways to potentially increase this energy, from lowering the temperature to making the indium arsenide wire longer. As things currently stand, Nayak said that small changes in any of these can lead to a large boost in the energy gap, making it relatively easy to boost the system’s stability.

Another key feature, he argued, is that the hardware is relatively small. He estimated that it should be possible to place a million qubits on a single chip. “Even if you put in margin for control structures and wiring and fan out, it’s still a few centimeters by a few centimeters,” Nayak said. “That was one of the guiding principles of our qubits.” So unlike some other technologies, the topological qubits won’t require anyone to figure out how to link separate processors into a single quantum system.

Finally, all the measurements that control the system run through the quantum dot, and controlling that is relatively simple. “Our qubits are voltage-controlled,” Nayak told Ars. “What we’re doing is just turning on and off coupling of quantum dots to qubits to topological nano wires. That’s a digital signal that we’re sending, and we can generate those digital signals with a cryogenic controller. So we actually put classical control down in the cold.”

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Quantum teleportation used to distribute a calculation

Computer science, Physics, quantum computing, quantum mechanics, Science, teleportation / Tim Belzer / February 5, 2025

The researchers showed that this setup allowed them to teleport with a specific gate operation (controlled-Z), which can serve as the basis for any other two-qubit gate operation—any operation you might want to do can be done by using a specific combination of these gates. After performing multiple rounds of these gates, the team found that the typical fidelity was in the area of 70 percent. But they also found that errors typically had nothing to do with the teleportation process and were the product of local operations at one of the two ends of the network. They suspect that using commercial hardware, which has far lower error rates, would improve things dramatically.

Finally, they performed a version of Grover’s algorithm, which can, with a single query, identify a single item from an arbitrarily large unordered list. The “arbitrary” aspect is set by the number of available qubits; in this case, having only two qubits, the list maxed out at four items. Still, it worked, again with a fidelity of about 70 percent.

While the work was done with trapped ions, almost every type of qubit in development can be controlled with photons, so the general approach is hardware-agnostic. And, given the sophistication of our optical hardware, it should be possible to link multiple chips at various distances, all using hardware that doesn’t require the best vacuum or the lowest temperatures we can generate.

That said, the error rate of the teleportation steps may still be a problem, even if it was lower than the basic hardware rate in these experiments. The fidelity there was 97 percent, which is lower than the hardware error rates of most qubits and high enough that we couldn’t execute too many of these before the probability of errors gets unacceptably high.

Still, our current hardware error rates started out far worse than they are today; successive rounds of improvements between generations of hardware have been the rule. Given that this is the first demonstration of teleported gates, we may have to wait before we can see if the error rates there follow a similar path downward.

Nature, 2025. DOI: 10.1038/s41586-024-08404-x (About DOIs).

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Research Roundup: 7 cool science stories we almost missed

Archaeology, Physics, Science / Tim Belzer / February 1, 2025

Peruvian mummy tattoos, the wobbly physics of spears and darts, quantum “cat states,” and more.

Lasers revealed tattoos on the hand of a 1200-year-old Peruvian mummy. Credit: Michael Pittman and Thomas G Kaye

It’s a regrettable reality that there is never time to cover all the interesting scientific stories each month. In the past, we’ve featured year-end roundups of cool science stories we missed. This year, we’re experimenting with a monthly collection. January’s list includes papers on using lasers to reveal Peruvian mummy tattoos; the physics of wobbly spears and darts; how a black hole changes over time; and quantum “cat states” for error correction in quantum computers, among other fascinating research.

Tracking changes in a black hole over time

Left: EHT images of M87from the 2018 and 2017 observation campaigns. Middle: Example images from a general relativistic magnetohydrodynamic (GRMHD) simulation at two different times. Right: Same simulation snapshots, blurred to match the EHT’s observational resolution. Credit: EHT collaboration

In 2019, the Event Horizon Telescope announced the first direct image ever taken of a black hole at the center of an elliptical galaxy, Messier 87 (M87), located in the constellation of Virgo some 55 million light-years away. Astronomers have now combined earlier observational data to learn more about the turbulent dynamics of plasma near M87*’s event horizon over time, according to a paper published in the journal Astronomy and Astrophysics.

Co-author Luciano Rezzolla of Goethe University Frankfurt in Germany likened the new analysis to comparing two photographs of Mount Everest, one year apart. While the mountain’s basic structure is unlikely to change much in that time, one could observe changes in clouds near the peak and deduce from that properties like wind direction. For instance, in the case of M87*, the new analysis confirmed the presence of a luminous ring that is brightest at the bottom, which in turn confirmed that the rotational axis points away from Earth. “More of these observations will be made in the coming years and with increasing precision, with the ultimate goal of producing a movie of what happens near M87*,” said Rezolla.

Astronomy and Astrophysics, 2025. DOI: 10.1051/0004-6361/202451296 (About DOIs).

Lasers reveal Peruvian mummy tattoos

A tattooed forearm of a Chancay mummy. Credit: Michael Pittman and Thomas G Kaye

Humans across the globe have been getting tattoos for more than 5,000 years, judging by traces found on mummified remains from Europe to Asia and South America. But it can be challenging to decipher details of those tattoos, given how much the ink tends to “bleed” over time, along with the usual bodily decay. Infrared imaging can help, but in an innovative twist, scientists decided to use lasers that make skin glow ever so faintly, revealing many fine hidden details of tattoos found on 1,200-year-old Peruvian mummies, according to a paper published in the Proceedings of the National Academy of Sciences.

It’s the first time the laser-stimulated fluorescence (LSF) technique has been used on mummified human remains. The skin’s fluorescence essentially backlights any tattoos, and after post-processing, the long-exposure photographs showed white skin behind black outlines of the tattoo art—images so detailed it’s possible to measure density differences in the ink and eliminate any bleed effects. The authors determined that the tattoos on four mummies—geometric patterns with triangles and diamonds—were made with carbon-based black ink skillfully applied with a pointed object finer than a standard modern tattoo needle, possibly a cactus needle or sharpened bone.

PNAS, 2025. DOI: 10.1073/pnas.2421517122 (About DOIs).

Sforza Castle’s hidden passages

Ground-penetrating radar reveals new secrets under Milan's Sforza Castle — Ground-penetrating radar reveals new secrets under Milan’s Sforza Castle Credit: Politecnico di Milano

Among the many glories of Milan is the 15th-century Sforza Castle, built by Francesco Sforza on the remnants of an earlier fortification as his primary residence. Legends about the castle abound, most notably the existence of secret underground chambers and passages. For instance, Ludovico il Moro, Duke of Milan from 1494–1499, was so heartbroken over the loss of his wife in childbirth that he used an underground passageway to visit her tomb in the Basilica of Santa Maria delle Grazie—a passageway that appears in the drawings of Leonardo da Vinci, who was employed at the court for a time.

Those underground cavities and passages are now confirmed, thanks to a geophysical survey using ground-penetrating radar and laser scanning, performed as part of a PhD thesis. Various underground cavities and buried passageways were found within the castle’s outer walls, including Ludovico’s passageway and what have may have been secret military passages. Those involved in the project plan to create a “digital twin” of Sforza Castle based on the data collected, one that incorporates both its current appearance and its past. Perhaps it will also be possible to integrate that data with augmented reality to provide an immersive digital experience.

Physics of wobbly spears and darts

Image sequence of a 100-mm long projectile during a typical ejection in experiments. — Image sequence of a 100-mm-long projectile during a typical ejection in experiments. Credit: G. Giombini et al., 2025

Among the things that make humans unique among primates is our ability to throw various objects with speed and precision (with some practice)—spears or darts, for example. That’s because the human shoulder is anatomically conducive to storing and releasing the necessary elastic energy, a quality that has been mimicked in robotics to improve motor efficiency. According to the authors of a paper published in the journal Physical Review E, the use of soft elastic projectiles can improve the efficiency of throws, particularly those whose tips are weighted with a mass like a spearhead.

Guillaume Giombini of the Université Côte d’Azur in Nice, France, and co-authors wanted to explore this “superpropulsion” effect more deeply, using a combination of experimental data, numerical simulation, and theoretical analysis. The projectiles they used in their experiments were inspired by archery bows and consisted of two flat steel cantilevers connected by a string, essentially serving as springs to give the projectile the necessary elasticity. They placed a flat piece of rigid plastic in the middle of the string as a platform. Some of the projectiles were tested alone, while others were weighted with end masses. A fork held each projectile in place before launch, and the scientists measured speed and deformation during flight. They found that the wobble produced by the weighted tip projectiles yielded a kinetic energy gain of 160 percent over more rigid, unweighted projectiles.

Physical Review E, 2025. DOI: 10.1103/PhysRevE.00.005500 (About DOIs).

Quantum “cat states” for error detection

Left to right: UNSW researchers Benjamin Wilhelm, Xi Yu, Andrea Morello, and Danielle Holmes, all seated and each holding a cat on their lap — Left to right: UNSW researchers Benjamin Wilhelm, Xi Yu, Andrea Morello, and Danielle Holmes. Credit: UNSW Sydney/CC BY-NC

The Schrödinger’s cat paradox in physics is an excellent metaphor for the superposition of quantum states in atoms. Over the last 20 years, physicists have managed to build various versions of Schrödinger’s cat in the laboratory whereby two or more particles manage to be in two different states at the same time—so-called “cat states,” such as six atoms in simultaneous “spin up” and “spin down” states, rather like spinning clockwise and counterclockwise at the same time. Such states are fragile, however, and quickly decohere. Physicists at the University of New South Wales came up with a fresh twist on a cat-state that is more robust, according to a paper published in the journal Nature Physics.

They used an antimony atom embedded within a silicon quantum chip. The atom is quite heavy and has a large nuclear spin that can go in eight directions rather than just two (spin up and spin down). This could help enormously with quantum error correction, one of the biggest obstacles in quantum computing, because there is more room for error in the binary code. “As the proverb goes, a cat has nine lives,” said co-author Xi Yu of UNSW. “One little scratch is not enough to kill it. Our metaphorical ‘cat’ has seven lives: it would take seven consecutive errors to turn the ‘0’ into a ‘1.’” And embedding the atom in a silicon chip makes it scalable.

Nature Physics, 2025. DOI: 10.1038/s41567-024-02745-0 (About DOIs).

New twist on chain mail armor

how polycatenated architected materials look in their fluid or granular state, conforming to the shape of the vessel in which it is held. — Credit: Wenjie Zhou

Scientists have developed a new material that is like “chain mail on steroids,” capable of responding as both a fluid or a solid, depending on the kind of stress applied, according to a paper published in the journal Science. That makes it ideal for manufacturing helmets or other protective gear, as well as biomedical devices and robotics components. The technical term is polycatenated architected materials (PAMs). Much like how chain mail is built from small metal rings linked together into a mesh, PAMs are composed of various interlocking shapes that can form a wide range of different 3D patterns.

The authors were partly inspired by the lattice structure of crystals; they just replaced fixed particles with rings or cage-like shapes made out of different materials—such as acrylic polymers, nylon, or metals—to make small 3D-printed structures small enough to fit in the palm of one’s hand. They then subjected these materials to various stressors in the laboratory: compression, a lateral shearing force, and twisting. Some of the materials felt like hard solids, others were squishier, but they all exhibited the same kind of telltale transition, behaving more like a fluid or a solid depending on the stressor applied. PAMs at the microscale can also expand or contract in response to electrical charges. This makes them a useful hybrid material, spanning the gap between granular materials and elastic deformable ones.

W. Zhou et al., Science, 2025. DOI: 10.1126/science.adr9713 (About DOIs).

Kitty robot mimics headbutts

Any cat lover will tell you that cats show humans affection by rubbing their heads against the body (usually shins or hands). It’s called “bunting,” often accompanied by purring, and it’s one of the factors that make companion animal therapy so effective, per the authors of a paper published in ACM Transactions on Human-Robot Interactions. That’s why they built a small robot designed to mimic bunting behavior, conducting various experiments to assess whether human participants found their interactions with the kitty-bot therapeutic. The robot prototypes were small enough to fit on a human lap, featuring a 3D-printed frame and a head covered with furry polyester fabric.

The neck needed to be flexible to mimic the bunting behavior, so the authors incorporated a mechanism that could adjust the stiffness of the neck via wire tension. They then tested various prototypes with university students, setting the neck stiffness to low, high, and variable. The students said they felt less tense after interacting with the robots. There was no significant difference between the settings, although participants slightly preferred the variable setting. We know what you’re thinking: Why not just get an actual cat or visit your local cat cafe? The authors note that many people are allergic to cats, and there is also a risk of bites, scratches, or disease transmission—hence the interest in developing animal-like robots for therapeutic applications.

ACM Transactions on Human-Robot Interactions, 2025. DOI: 10.1145/3700600 (About DOIs).

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Complexity physics finds crucial tipping points in chess games

chess, mathematics, networks, phase transitions, Physics, Science, tipping points / Paul Patrick / January 24, 2025

For his analysis, Barthelemy chose to represent chess as a decision tree in which each “branch” leads to a win, loss, or draw. Players face the challenge of finding the best move amid all this complexity, particularly midgame, in order to steer gameplay into favorable branches. That’s where those crucial tipping points come into play. Such positions are inherently unstable, which is why even a small mistake can have a dramatic influence on a match’s trajectory.

A case of combinatorial complexity

Barthelemy has re-imagined a chess match as a network of forces in which pieces act as the network’s nodes, and the ways they interact represent the edges, using an interaction graph to capture how different pieces attack and defend one another. The most important chess pieces are those that interact with many other pieces in a given match, which he calculated by measuring how frequently a node lies on the shortest path between all the node pairs in the network (its “betweenness centrality”).

He also calculated so-called “fragility scores,” which indicate how easy it is to remove those critical chess pieces from the board. And he was able to apply this analysis to more than 20,000 actual chess matches played by the world’s top players over the last 200 years.

Barthelemy found that his metric could indeed identify tipping points in specific matches. Furthermore, when he averaged his analysis over a large number of games, an unexpected universal pattern emerged. “We observe a surprising universality: the average fragility score is the same for all players and for all openings,” Barthelemy writes. And in famous chess matches, “the maximum fragility often coincides with pivotal moments, characterized by brilliant moves that decisively shift the balance of the game.”

Specifically, fragility scores start to increase about eight moves before the critical tipping point position occurs and stay high for some 15 moves after that. “These results suggest that positional fragility follows a common trajectory, with tension peaking in the middle game and dissipating toward the endgame,” he writes. “This analysis highlights the complex dynamics of chess, where the interaction between attack and defense shapes the game’s overall structure.”

Physical Review E, 2025. DOI: 10.1103/PhysRevE.00.004300 (About DOIs).

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Researchers optimize simulations of molecules on quantum computers

catalysts, Computer science, electrons, Physics, quantum computing, quantum mechanics, Science / Paul Patrick / January 24, 2025

The net result is a much faster operation involving far fewer gates. That’s important because errors in quantum hardware increase as a function of both time and the number of operations.

The researchers then used this approach to explore a chemical, Mn₄O₅Ca, that plays a key role in photosynthesis. Using this approach, they showed it’s possible to calculate what’s called the “spin ladder,” or the list of the lowest-energy states the electrons can occupy. The energy differences between these states correspond to the wavelengths of light they can absorb or emit, so this also defines the spectrum of the molecule.

Faster, but not quite fast enough

We’re not quite ready to run this system on today’s quantum computers, as the error rates are still a bit too high. But because the operations needed to run this sort of algorithm can be done so efficiently, the error rates don’t have to come down very much before the system will become viable. The primary determinant of whether it will run into an error is how far down the time dimension you run the simulation, plus the number of measurements of the system you take over that time.

“The algorithm is especially promising for near-term devices having favorable resource requirements quantified by the number of snapshots (sample complexity) and maximum evolution time (coherence) required for accurate spectral computation,” the researchers wrote.

But the work also makes a couple of larger points. The first is that quantum computers are fundamentally unlike other forms of computation we’ve developed. They’re capable of running things that look like traditional algorithms, where operations are performed and a result is determined. But they’re also quantum systems that are growing in complexity with each new generation of hardware, which makes them great at simulating other quantum systems. And there are a number of hard problems involving quantum systems we’d like to solve.

In some ways, we may only be starting to scratch the surface of quantum computers’ potential. Up until quite recently, there were a lot of hypotheticals; it now appears we’re on the cusp of using one for some potentially useful computations. And that means more people will start thinking about clever ways we can solve problems with them—including cases like this, where the hardware would be used in ways its designers might not have even considered.

Nature Physics, 2025. DOI: 10.1038/s41567-024-02738-z (About DOIs).

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