Computers Math

An international team of authors led by Ilka Agricola, professor of mathematics at the University of Marburg, Germany, has investigated fraudulent practices in the publication of research results in mathematics on behalf of the German Mathematical Society (DMV) and the International Mathematical Union (IMU), documenting systematic fraud over many years. The results of the study were recently published on the preprint server arxiv.org and in the Notices of the American Mathematical Society (AMS) and have since caused a stir among mathematicians.
To solve the problem, the study also provides recommendations for the publication of research results in mathematics.
Nowadays, research quality is often no longer measured directly by the content of publications, but increasingly by commercial indicators such as the number of publications/citations by authors or the “reputation” (impact factor) of journals. These indicators are calculated in a non-transparent manner and without the involvement of the scientific community by commercial providers, who use them to boost sales of their databases worldwide. Fraudulent companies offer their services specifically to optimize these metrics. This is worthwhile for both individuals and institutions, because a higher ranking, e.g., in a university ranking, means better access to funding and (in an international context) the possibility of charging higher tuition fees and attracting more applicants. The collateral damage is a high percentage of publications whose sole purpose is to boost the indicators, but which no one reads because they contain no new scientific findings or are even flawed.
The study cites some striking examples. For example, based on its database, the market leader for metrics, Clarivate Inc., calculated in 2019 that the university with the most world-class researchers in mathematics is a university in Taiwan — where mathematics is not even offered as a subject. Megajournals, which print anything as long as the authors pay for it, now publish more articles per year than all reputable mathematics journals (which do not require payment) combined. Fraudsters anonymously offer everything that influences key figures for sale, from articles to citations, in exchange for payment.
“‘Fake science’ is not only annoying, it is a danger to science and society,” emphasizes IMU Secretary General Prof. Christoph Sorger. “Because you don’t know what is valid and what is not. Targeted disinformation undermines trust in science and also makes it difficult for us mathematicians to decide which results can be used as a basis for further research.” DMV President Prof. Jürg Kramer added: “The recommendations developed by the commission are a call to all of us to work toward a system change.” More

If you think a galaxy is big, compare it to the size of the Universe: it’s just a tiny dot which, together with a huge number of other tiny dots, forms clusters that aggregate into superclusters, which in turn weave into filaments threaded with voids — an immense 3D skeleton of our Universe.
If that gives you vertigo and you’re wondering how one can understand or even “see” something so vast, the answer is: it isn’t easy. Scientists combine the physics of the Universe with data from astronomical instruments and build theoretical models, such as EFTofLSS (Effective Field Theory of Large-Scale Structure). Fed with observations, these models describe the “cosmic web” statistically and allow its key parameters to be estimated.
Models like EFTofLSS, however, demand a lot of time and computing resources. Since the astronomical datasets at our disposal are growing exponentially, we need ways to lighten the analysis without losing precision. This is why emulators exist: they “imitate” how the models respond, but operate much faster.
Since this is a kind of “shortcut,” what’s the risk of losing accuracy? An international team including, among others, INAF (Italy), The University of Parma (Italy) and the University of Waterloo (Canada) has published in the Journal of Cosmology and Astroparticle Physics (JCAP) a study testing the emulator Effort.jl, which they designed. It shows that Effort.jl delivers essentially the same correctness as the model it imitates — sometimes even finer detail — while running in minutes on a standard laptop instead of a supercomputer.
“Imagine wanting to study the contents of a glass of water at the level of its microscopic components, the individual atoms, or even smaller: in theory you can. But if we wanted to describe in detail what happens when the water moves, the explosive growth of the required calculations makes it practically impossible,” explains Marco Bonici, a researcher at the University of Waterloo and first author of the study. “However, you can encode certain properties at the microscopic level and see their effect at the macroscopic level, namely the movement of the fluid in the glass. This is what an effective field theory does, that is, a model like EFTofLSS, where the water in my example is the Universe on very large scales and the microscopic components are small-scale physical processes.”
The theoretical model statistically explains the structure that gives rise to the data collected: the astronomical observations are fed to the code, which computes a “prediction.” But this requires time and substantial compute. Given today’s data volume — and what is expected from surveys just begun or coming soon (such as DESI, which has already released its first batch of data, and Euclid) — it’s not practical to do this exhaustively every time.
“This is why we now turn to emulators like ours, which can drastically cut time and resources,” Bonici continues. An emulator essentially mimics what the model does: its core is a neural network that learns to associate the input parameters with the model’s already-computed predictions. The network is trained on the model’s outputs and, after training, can generalize to combinations of parameters it hasn’t seen. The emulator doesn’t “understand” the physics itself: it knows the theoretical model’s responses very well and can anticipate what it would output for a new input. Effort.jl’s originality is that it further reduces the training phase by building into the algorithm knowledge we already have about how predictions change when parameters change: instead of making the network “re-learn” these, it uses them from the start. Effort.jl also uses gradients — i.e., “how much and in which direction” predictions change if you tweak a parameter by a tiny amount — another element that helps the emulator learn from far fewer examples, cutting compute needs and allowing it to run on smaller machines.
A tool like this needs extensive validation: if the emulator doesn’t know the physics, how sure are we that its shortcut yields correct answers (i.e., the same ones the model would give)? The newly published study answers exactly this, showing that Effort.jl’s accuracy — on both simulated and real data — is in close agreement with the model. “And in some cases, where with the model you have to trim part of the analysis to speed things up, with Effort.jl we were able to include those missing pieces as well,” Bonici concludes. Effort.jl thus emerges as a valuable ally for analyzing upcoming data releases from experiments like DESI and Euclid, which promise to greatly deepen our knowledge of the Universe on large scales.
The study “Effort.jl: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe” by Marco Bonici, Guido D’Amico, Julien Bel and Carmelita Carbone is available in the Journal of Cosmology and Astroparticle Physics (JCAP). More

Researchers at Michigan State University have figured out how to use a fast laser to wiggle atoms in a way that temporarily changes the behavior of their host material. Their novel approach could lead to smaller, and more efficient electronics — like smartphones — in the future.
Tyler Cocker, an associate professor in the College of Natural Science, and Jose L. Mendoza-Cortes, an assistant professor in the colleges of Engineering and Natural Science, have combined the experimental and theoretical sides of quantum mechanics — the study of the strange ways atoms behave at a very small scale — to push the boundaries of what materials can do to improve electronic technologies we use every day.
“This experience has been a reminder of what science is really like because we found materials that are working in ways that we didn’t expect,” said Cocker. “Now, we want to look at something that is going to be technologically interesting for people in the future.”
Using a material called tungsten ditelluride, or WTe2,which is made up of a layer of tungsten, or W atoms, sandwiched between two layers of tellurium, or Te atoms, Cocker’s team conducted a series of experiments where they placed this material under a specialized microscope they built. While microscopes are typically used to look at things that are hard for the human eye to see, like individual cells, Cocker’s scanning tunneling microscope can show individual atoms on the surface of a material. It does this by moving an extremely sharp metal tip over the surface, “feeling” atoms through an electrical signal, like reading braille. While looking at the atoms on the surface of WTe2, Cocker and his team used a super-fast laser to create terahertz pulses of light that were moving at speeds of hundreds of trillions of times per second. These terahertz pulses were focused onto the tip. At the tip, the strength of the pulses was increased enormously, allowing the researchers to wiggle the top layer of atoms directly beneath the tip and gently nudge that layer out of alignment from the remaining layers underneath it. Think of it like a stack of papers with the top sheet slightly crooked.
While the laser pulses illuminated the tip and WTe2,the top layer of the material behaved differently, exhibiting new electronic properties not observed when the laser was turned off. Cocker and his team realized the terahertz pulses together with the tip could be used like a nanoscale switch to temporarily change the electrical properties of WTe2 to upscale the next generation of devices. Cocker’s microscope could even see the atoms moving during this process and photograph the unique “on” and “off” states of the switch they had created.
When Cocker and Mendoza-Cortes realized that they were working on similar projects from different perspectives, Cocker’s experimental side joined with Mendoza’s theoretical side of quantum mechanics. Mendoza-Cortes’ research focuses on creating computer simulations. By comparing the results of Mendoza’s quantum calculations to Cocker’s experiments, both labs yielded the same results — independently and by using different tools.
“Our research is complementary; it’s the same observations but through different lenses,” said Mendoza-Cortes. “When our model matched the same answers and conclusions they found in their experiments, we have a better picture of what is going on.”
The Mendoza lab computationally found that the layers of WTe2 shift by 7 picometers while they are wiggling, which is hard to observe by the specialized microscope alone. Also, they were able to confirm that the frequencies at which the atoms wiggle match between the experiment and theory, but the quantum calculations can tell which way they wiggle and by how much.

“The movement only occurs on the topmost layer, so it is very localized,” said Daniel Maldonado-Lopez, a fourth-year graduate student in Mendoza’s lab. “This can potentially be applied in building faster and smaller electronics.”
Cocker and Mendoza-Cortes hope this research will lead to the use of new materials, lower costs, faster speeds and greater energy efficiency for future phones and computer technology.
“When you think about your smartphone or your laptop, all of the components that are in there are made out of a material,” said Stefanie Adams, a fourth-year graduate student in Cocker’s lab. “At some point, someone decided that’s the material we’re going use.”
The research appeared in Nature Photonics and was supported in part through computational resources and services provided by the Institute for Cyber-Enabled Research at Michigan State University.
Why this matters: Wiggling atoms in new quantum materials could lead to more efficient electronics that are smaller and faster. These new materials have surprising properties and could be key elements for next-generation quantum computers. More

Researchers at the University of Gothenburg have made light-powered gears on a micrometer scale. This paves the way for the smallest on-chip motors in history, which can fit inside a strand of hair.
Gears are everywhere – from clocks and cars to robots and wind turbines. For more than 30 years, researchers have been trying to create even smaller gears in order to construct micro-engines. But progress stalled at 0.1 millimeters, as it was not possible to build the drive trains needed to make them move any smaller.
Researchers from Gothenburg University, among others, have now broken through this barrier by ditching traditional mechanical drive trains and instead using laser light to set the gears in motion directly.
Gears powered by light
In their new study, the researchers shows that microscopic machines can be driven by optical metamaterials – small, patterned structures that can capture and control light on a nanoscale. Using traditional lithography, gears with an optical metamaterial are manufactured with silicon directly on a microchip, with the gear having a diameter of a few tens of micrometers. By shining a laser on the metamaterial, the researchers can make the gear wheel spin. The intensity of the laser light controls the speed, and it is also possible to change the direction of the gear wheel by changing the polarization of the light.
The researchers are thus close to creating micromotors.
A new way of thinking
“We have built a gear train in which a light-driven gear sets the entire chain in motion. The gears can also convert rotation into linear motion, perform periodic movements and control microscopic mirrors to deflect light,” says the study’s first author, Gan Wang, a researcher in soft matter physics at the University of Gothenburg.

The ability to integrate such machines directly onto a chip and drive them with light opens up entirely new possibilities. Since laser light does not require any fixed contact with the machine and is easy to control, the micromotor can be scaled up to complex microsystems.
“This is a fundamentally new way of thinking about mechanics on a microscale. By replacing bulky couplings with light, we can finally overcome the size barrier,” says Gan Wang.
Cell size
With these advances, researchers are beginning to imagine micro- and nanomachines that can control light, manipulate small particles or be integrated into future lab-on-a-chip systems. A gear wheel can be as small as 16-20 micrometers, and there are human cells of that size. Medicine is a field that is within reach, believes Gan Wang.
“We can use the new micromotors as pumps inside the human body, for example to regulate various flows. I am also looking at how they function as valves that open and close.” More

Scientists at NYU Abu Dhabi (NYUAD) have developed an artificial intelligence (AI) model that can forecast solar wind speeds up to four days in advance, significantly more accurately than current methods. The study is published in The Astrophysical Journal Supplement Series.
Solar wind is a continuous stream of charged particles released by the Sun. When these particles speed up, they can cause “space weather” events that disrupt Earth’s atmosphere and drag satellites out of orbit, damage their electrons, and interfere with power grids. In 2022, a strong solar wind event caused SpaceX to lose 40 Starlink satellites, showing the urgent need for better forecasting.
The NYUAD team, led by Postdoctoral Associate Dattaraj Dhuri and Co-Principal Investigator at the Center for Space Science (CASS) Shravan Hanasoge, trained their AI model using high-resolution ultraviolet (UV) images from NASA’s Solar Dynamics Observatory, combined with historical records of solar wind. Instead of analyzing text, like today’s popular AI language models, the system analyzes images of the Sun to identify patterns linked to solar wind changes. The result is a 45 percent improvement in forecast accuracy compared to current operational models, and a 20 percent improvement over previous AI-based approaches.
“This is a major step forward in protecting the satellites, navigation systems, and power infrastructure that modern life depends on,” said Dhuri, lead author of the study. “By combining advanced AI with solar observations, we can give early warnings that help safeguard critical technology on Earth and in space.”
The breakthrough demonstrates how AI can solve one of space science’s toughest challenges: predicting the solar wind. With more reliable forecasts, scientists and engineers can better prepare for space weather events, strengthening resilience against disruptions to critical infrastructure.
NYU Abu Dhabi has established more than 90 faculty labs and projects, producing over 9,200 internationally recognized research publications. Times Higher Education ranks NYU among the world’s top 35 universities, making NYUAD the highest globally ranked university in the UAE. More

Spintronics, or spin-electronics, is a revolutionary approach to information processing that utilizes the intrinsic angular momentum (spin) of electrons, rather than solely relying on electric charge flow. This technology promises faster, more energy-efficient data storage and logic devices. A central challenge in fully realizing spintronics has been the development of materials that can precisely control electron spin direction.
In a groundbreaking development for spin-nanotechnology, researchers led by Professor Young Keun Kim of Korea University and Professor Ki Tae Nam of Seoul National University have successfully created magnetic nanohelices that can control electron spin. This technology, which utilizes chiral magnetic materials to regulate electron spin at room temperature, has been published in Science.
“These nanohelices achieve spin polarization exceeding ~80% — just by their geometry and magnetism,” stated Professor Young Keun Kim of Korea University, a co-corresponding author of the study. He further emphasized, “This is a rare combination of structural chirality and intrinsic ferromagnetism, enabling spin filtering at room temperature without complex magnetic circuitry or cryogenics, and provides a new way to engineer electron behavior using structural design.”
The research team successfully fabricated left- and right-handed chiral magnetic nanohelices by electrochemically controlling the metal crystallization process. A critical innovation involved introducing trace amounts of chiral organic molecules, such as cinchonine or cinchonidine, which guided the formation of helices with precisely defined handedness — a feat rarely achieved in inorganic systems. Also, the team experimentally demonstrated that when these nanohelices exhibit a right-handedness, they preferentially allow one direction of spin to pass, while the opposite spin cannot. The above marks the discovery of a 3D inorganic helical nanostructure capable of electron spin control.
“Chirality is well-understood in organic molecules, where the handedness of a structure often determines its biological or chemical function,” noted Professor Ki Tae Nam of Seoul National University, also a co-corresponding author. “But in metals and inorganic materials, controlling chirality during synthesis is extremely difficult, especially at the nanoscale. The fact that we could program the direction of inorganic helices simply by adding chiral molecules is a breakthrough in materials chemistry.”
To confirm the chirality of nanohelices, the researchers developed an electromotive force (emf)-based chirality evaluation method and measured the emf generated by the helices under rotating magnetic fields. The left- and right-handed helices produced opposite emf signals, allowing for quantitative verification of chirality even in materials that do not strongly interact with light.
The research team also found that the magnetic material itself, through its inherent magnetization (spin alignment), enables long-distance spin transport at room temperature. This effect, maintained by strong exchange energy, is constant regardless of the angle between the chiral axis and the spin injection direction, and was not observed in non-magnetic nanohelices of the same scale. The above marks the first measurement of asymmetric spin transport in a relatively macro-scaled chiral body. The team also demonstrated a solid-state device that showed chirality-dependent conduction signals, paving the way for practical spintronic applications.
Professor Kim highlighted the potential impact: “We believe this system could become a platform for chiral spintronics and architecture of chiral magnetic nanostructures.” This work represents a powerful convergence of geometry, magnetism, and spin transport, built from scalable, inorganic materials. The ability to control the handedness (left/right) and even the number of strands (double, multiple helices) using this versatile electrochemical method is expected to contribute significantly to new application areas. More

Johns Hopkins researchers have discovered new materials and a new process that could advance the ever-escalating quest to make smaller, faster and affordable microchips used across modern electronics — in everything from cellphones to cars, appliances to airplanes.
The team of scientists has discovered how to create circuits that are so small they’re invisible to the naked eye using a process that is both precise and economical for manufacturing.
The findings are published on September 11 in the journal Nature Chemical Engineering.
“Companies have their roadmaps of where they want to be in 10 to 20 years and beyond,” said Michael Tsapatsis, a Bloomberg Distinguish Professor of chemical and biomolecular engineering at Johns Hopkins University. “One hurdle has been finding a process for making smaller features in a production line where you irradiate materials quickly and with absolute precision to make the process economical.”
The advanced lasers required for imprinting on the miniscule formats already exist, Tsapatsis added, but researchers needed new materials and new processes to accommodate ever smaller microchips.
Microchips are flat pieces of silicon with imprinted circuitries that execute basic functions. During production, manufacturers coat silicon wafers with a radiation-sensitive material to create a very fine coating called a “resist.” When a beam of radiation is pointed at the resist, it sparks a chemical reaction that burns details into the wafer, drawing patterns and circuitry.
However, the higher-powered radiation beams that are needed to carve out ever-smaller details on chips do not interact strongly enough with traditional resists.

Previously, researchers from Tsapatsis’s lab and the Fairbrother Research Group at Johns Hopkins found that resists made of a new class of metal-organics can accommodate that higher-powered radiation process, called “beyond extreme ultraviolet radiation” (B-EUV), which has the potential to make details smaller than the current standard size of 10 nanometers. Metals like zinc absorb the B-EUV light and generate electrons that cause chemical transformations needed to imprint circuit patterns on an organic material called imidazole.
This research marks one of the first times scientists have been able to deposit these imidazole-based metal-organic resists from solution at silicon-wafer scale, controlling their thickness with nanometer precision. To develop the chemistry needed to coat the silicon wafer with the metal-organic materials, the team combined experiments and models from Johns Hopkins University, East China University of Science and Technology, École Polytechnique Fédérale de Lausanne, Soochow University, Brookhaven National Laboratory and Lawrence Berkeley National Laboratory. The new methodology, which they call chemical liquid deposition (CLD), can be precisely engineered and lets researchers quickly explore various combinations of metals and imidazoles.
“By playing with the two components (metal and imidazole), you can change the efficiency of absorbing the light and the chemistry of the following reactions. And that opens us up to creating new metal-organic pairings,” Tsapatsis said. “The exciting thing is there are at least 10 different metals that can be used for this chemistry, and hundreds of organics.”
The researchers have started experimenting with different combinations to create pairings specifically for B-EUV radiation, which they say will likely be used in manufacturing in the next 10 years.
“Because different wavelengths have different interactions with different elements, a metal that is a loser in one wavelength can be a winner with the other,” Tsapatsis said. “Zinc is not very good for extreme ultraviolet radiation, but it’s one of the best for the B-EUV.”
Authors include Yurun Miao, Kayley Waltz, and Xinpei Zhou from Johns Hopkins University; Liwei Zhuang, Shunyi Zheng, Yegui Zhou, and Heting Wang from East China University of Science and Technology; Mueed Ahmad and J. Anibal Boscoboinik from Brookhaven National Laboratory; Qi Liu from Soochow University; Kumar Varoon Agrawal from École Polytechnique Fédérale de Lausanne; and Oleg Kostko from Lawrence Berkeley National Laboratory. More

Unlike conventional phases of matter, the so-called non-equilibrium quantum phases are defined by their dynamical and time-evolving properties — a behavior that cannot be captured by traditional equilibrium thermodynamics. One particularly rich class of non-equilibrium states arises in Floquet systems — quantum systems that are periodically driven in time. This rhythmic driving can give rise to entirely new forms of order that cannot exist under any equilibrium conditions, revealing phenomena that are fundamentally beyond the reach of conventional phases of matter.
Using a 58 superconducting qubit quantum processor, the team from the Technical University of Munich (TUM), Princeton University, and Google Quantum AI realized a Floquet topologically ordered state, a phase that had been theoretically proposed but never before observed. They directly imaged the characteristic directed motions at the edge and developed a novel interferometric algorithm to probe the system’s underlying topological properties. This allowed them to witness the dynamical “transmutation” of exotic particles – a hallmark that has been theoretically predicted for these exotic quantum states.
Quantum computer as a laboratory
“Highly entangled non-equilibrium phases are notoriously hard to simulate with classical computers,” said the first author Melissa Will, PhD student at the Physics Department of the TUM School of Natural Sciences. “Our results show that quantum processors are not just computational devices – they are powerful experimental platforms for discovering and probing entirely new states of matter.”
This work opens the door to a new era of quantum simulation, where quantum computers become laboratories for studying the vast and largely unexplored landscape of out-of-equilibrium quantum matter. The insights gained from these studies could have far-reaching implications, from understanding fundamental physics to designing next-generation quantum technologies. More