Monday, September 28, 2026

 

Waves find order in the chaos of an oddly shaped cavity



CUNY ASRC researchers discover stable, repeating wave patterns in a metamaterial system, opening new possibilities for controlling light and sound




Advanced Science Research Center, GC/CUNY

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Artistic rendering of a hyperbolic wave attractor forming in an odd-shaped cavity inside a hyperbolic material.

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Credit: Andrea Alu






NEW YORK, September 28, 2026 — When light or sound bounces around inside an oddly shaped room, its reflections can quickly become difficult to predict. But new research led by scientists at the Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) shows that waves can behave very differently when they travel through a special class of materials.

The study, published in Nature Physics, demonstrates that waves inside an irregularly shaped cavity made from hyperbolic materials (which are named after the hyperbola mathematical curve because of the unique shape these materials force light waves to take) can organize into stable, repeating paths rather than scattering chaotically. The researchers call these structures “hyperbolic wave attractors,” and their findings could eventually help scientists and engineers design new ways to control light, radio waves, and sound in complex environments.

“This work shows how geometry and the properties of a material can work together to produce wave behavior that is both surprising and useful,” said Andrea Alù, the study’s principal investigator, director of the Photonics Initiative at the CUNY ASRC, and Distinguished Professor of Physics at the CUNY Graduate Center. “By understanding how waves organize themselves in these hyperbolic media, we can begin to explore new approaches to controlling energy, information, and communication signals in complex environments.”

When waves take an unusual turn

In everyday materials, waves generally reflect from a surface in a familiar way: The angle at which a wave arrives matches the angle at which it leaves. In an irregularly shaped room, repeated reflections can send waves in many directions, creating complex chaotic patterns. This is the basis of a classic physics problem known as a dynamical billiard, in which the motion of a ball — or, in the wave version, light — inside a curved or irregular container quickly becomes unpredictable.

Hyperbolic materials can drastically change this picture. These materials have unusual properties that force waves to travel along narrow, highly defined directions instead of spreading freely in all directions. As a result, when a wave encounters a tilted wall, its outgoing direction can differ from what would be expected in an ordinary material.

Alù’s team wanted to understand what would happen when these unusual reflection rules were combined with an irregularly shaped cavity.

“Normally, we expect a complicated cavity to produce complicated, chaotic wave patterns,” said Simon Yves, a postdoctoral researcher in Alù’s lab and a first author of the study. “Here, the opposite happens. The unusual propagation and reflection of waves create a strong geometric organization, producing well-defined paths that can persist across a broad range of wavelengths.”

From chaos to wave attractors

The researchers found that the waves inside their cavity can progressively organize into closed trajectories. These paths are stable and scale-invariant, meaning their underlying geometric structure persists across different scales.

The effect arises from a breaking of mirror symmetry in the wave-reflection process. As waves bounce around the cavity, their wavelengths progressively shrink, helping create the conditions for the formation of the attractors.

The resulting wave patterns also have a property called handedness. This describes whether the defined wave’s trajectory inside the cavity rotates clockwise or counterclockwise. The attractors’ handedness and stability are connected to the unusual geometry of wave propagation in the hyperbolic material.

The team demonstrated these effects by engineering vibrations in a mechanical metamaterial, a human-made structure designed to control how waves move through it.

“The most exciting aspect of these results is that they connect a simple geometric idea with a rich set of wave phenomena,” said Enrico Renzi, a doctoral student in Alù’s lab and a first author of the study. “We can observe how the waves become organized, and we can connect that organization to properties such as stability and handedness. This gives us a framework for designing wave behavior rather than simply observing it.”

A bridge from ocean waves to nanophotonics

The researchers’ findings have intriguing parallels with internal wave attractors studied in oceanography and fluid dynamics. In oceans and other stratified fluids, waves traveling through water with density gradients can reflect unusually from underwater slopes. These reflections can focus energy into closed paths and contribute to wave turbulence.

The new study translates a related phenomenon into a tabletop, solid-state metamaterial platform, showing how concepts from geophysical fluid dynamics can be explored in engineered materials and in simple linear settings.

The framework that the scientists introduced can also extend to hyperbolic phonon polaritons — hybrid light-matter excitations that can arise in natural two-dimensional anisotropic crystals such as hexagonal boron nitride and molybdenum trioxide, which support similarly odd propagation and reflection properties. These materials can support light confined to tiny regions, offering opportunities for low-loss nanophotonic circuits, enhanced interactions between light and matter, and control of infrared light.

In the future, hyperbolic wave attractors could inform the design of compact optical chips, devices that separate optical signals, particle-trapping systems, analog wave-computing platforms, and highly sensitive biological sensors.

“This research opens a path toward engineering stable and robust wave patterns in systems where waves would normally be expected to rapidly become chaotic,” Alù said. “Our goal is to understand how these effects can be harnessed to create new functionalities for photonics, phononics, and wave-based technologies.”

The research was supported by the Simons Foundation and the National Science Foundation Science and Technology Center “New Frontiers of Sound.” The research team included scientists affiliated with the CUNY ASRC and Institut Langevin at ESPCI Paris PSL in France, as well as the University of Amsterdam in the Netherlands.

About the Advanced Science Research Center at the CUNY Graduate Center

The Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) is a world-leading center of scientific excellence that elevates STEM inquiry and education at CUNY and beyond. The CUNY ASRC’s research initiatives span five distinctive, but broadly interconnected disciplines: nanoscience, photonics, neuroscience, structural biology, and environmental sciences. The center promotes a collaborative, interdisciplinary research culture where renowned and emerging scientists advance their discoveries using state-of-the-art equipment and cutting-edge core facilities.

About the Graduate Center of The City University of New York
The CUNY Graduate Center is a leader in public graduate education devoted to enhancing the public good through pioneering research, serious learning, and reasoned debate. The Graduate Center offers ambitious students over 50 doctoral, master’s, and certificate programs of the highest caliber, taught by top faculty from throughout CUNY — the nation’s largest urban public university. Through its nearly 40 centers, institutes, initiatives, and the Advanced Science Research Center, the Graduate Center influences public policy and discourse and shapes innovation. The Graduate Center’s extensive public programs make it a home for culture and conversation. 

 

Foods with shorter shelf life are seen as more natural and healthier: UBC study




University of British Columbia





For years nutrition experts have warned about the many risks of eating ultra-processed foods: among them obesity, cardiovascular disease and diabetes. Instead, they advise that consumers opt for more natural offerings.  

So how, then, are shoppers determining the naturalness of a food? According to a fascinating new study from the UBC Sauder School of Business, they’re using product shelf lives as a shorthand, even when they aren’t a reliable indicator. 

For the study, titled Naturalness against environment-friendliness: The impact of shelf life on food perceptions and purchase decisions, researchers performed a series of experiments. In one, participants compared potato chips that had five-month and nine-month shelf lives, and rated the five-month chips as more natural and healthier, while those with the longer shelf life were considered more environmentally friendly and better for reducing waste.  

In another, participants chose between pasta sauces that had one- and three-year shelf lives. When the researchers emphasized the importance of consuming natural foods, nearly 70 per cent chose the item with the one-year shelf life; when they emphasized the importance of protecting the environment, that number plummeted to 43 per cent. 

Amazingly, even when participants were shown the only reason behind a product’s longer shelf life was better packaging (a high-performance seal on a mayonnaise jar), when naturalness mattered, they still opted for the mayo with a shorter life. Likewise, even when participants were shown two granola bars with nearly identical ingredients and nutritional information but different shelf lives, when naturalness mattered, they still opted for the granola with a shorter life. 

The researchers believe consumers are using shelf life as a kind of mental shortcut to determine naturalness, and in the process may choose foods that are more likely to be wasted.   

“We provide all the necessary information to make a rational choice. We provide ingredient lists. We provide nutritional facts. But it's a lot to process,” explains UBC Sauder Associate Professor Dr. Yann Cornil, who co-authored the study with Dr. Dan Liu of Jinan University and Dr. Xiaobing Xu of Hainan University. Like shoppers in a supermarket, he says, study participants instead tend to rely on “peripheral cues,” including shelf life, packaging and marketing, to reach conclusions about whether a product is natural or not. 

The study is especially timely, given that roughly 46 per cent of Canadians’ daily caloric intake is from ultra-processed foods. In the U.S. that number is even higher, at roughly 55 per cent. Often made from substances extracted from sugars, oils and starches, the foods are dramatically altered from their natural state and can be high in sodium, saturated fat, or added sugar, and lower in nutrients. 

Dr. Cornil says there’s been a shift in nutrition science, from concern over foods that are high in fat and sugar to ones that are highly processed. Now, when consumers think of a food as natural, they will generally consider it healthy, and they see foods with longer shelf life as less natural. 

“To some extent they are correct, because the more you extend the shelf life of a food, the more likely it went through this ultra-processing technique… but not necessarily,” says Dr. Cornil. Packaging has improved dramatically, he explains, and better packaging has improved conservation, just like refrigeration did 60 years ago.  

Still, consumers overestimate the relationship between shelf life and naturalness, and that can lead to unnecessary food waste.  

“By looking for natural foods, consumers tend to prefer foods with a shorter shelf life, even though foods with a longer shelf life could be just as good, and just as healthy and natural, as we show in the paper,” says Dr. Cornil. “So by trying to choose natural foods, they might run the risk of choosing foods they will eventually waste because they have too little time to consume them.” 

Dr. Cornil says consumers regularly misunderstand shelf life, and toss foods that are still fine to eat. As a result, some manufacturers are even indicating on their packaging that foods can still be safely consumed after their best before dates, although he notes that less scrupulous manufacturers might take advantage of the fact that consumers have to repurchase their products more often. Improvements to packaging are also reducing waste, but as the paper shows, consumers aren’t always sold on the idea. 

The study is the first of its kind to demonstrate the tension between environmental friendliness and naturalness, as well as the power of the shelf-life heuristic, that is, the mental shortcut consumers use to determine naturalness. 

“The fact that we still find this effect even when we provide nutrition information, and even when we make consumers understand that packaging is responsible for the longer shelf life and not processing, is really interesting,” says Dr. Cornil. “And we go pretty far in showing the strength of this misleading heuristic.” 

 

File-notification systems leave Windows, Linux, Android and macOS vulnerable


A research team at Graz University of Technology has demonstrated that the file notification systems of various operating systems can be exploited to spy on users' activities and forge password prompts.




Graz University of Technology

The File Notification Systems of popular operating systems allow spying

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The File Notification Systems of popular operating systems allow spying

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Credit: Brinda Neela; CC BY 4.0; https://inoti.fyi/






Researchers at the Institute of Information Security at Graz University of Technology (TU Graz) have uncovered security risks in the file notification systems of the widely used operating systems Windows, Linux, Android and macOS. Through so-called side-channel attacks, system-wide changes to files, keystrokes and visited websites can be tracked, and password prompt windows can be spoofed to intercept password entries. The researchers summarised their findings in the paper “File Notification Attacks: Templating and Exploiting Side-Channel Leakage from the File-Notification Systems on Linux, Windows, and macOS, which they have published on a dedicated website: https://inoti.fyi

A workaround via readable folders

File notification systems monitor whether files are created, deleted, opened, closed or modified, and automatically deliver system notifications so that applications or the system can react to the change. The research team discovered that apps or other users on the same system can monitor these notifications, even without administrator rights. This makes it possible to track what other users on the system are doing. Read access to specific folders is all that is required to read all files stored in a folder, as well as the subfolders and their contents – even if they do not actually permit read access. One thing that applies to all systems: file contents cannot be read; only file names and changes can be detected. However, this is sufficient to monitor user, system and application behaviour.

Browsing history can be tracked

The research team uses case studies to illustrate what such attacks could actually look like. To bypass the read-access restrictions on folders and files in Windows, the researchers simply tapped into the file notification system of the parent directory that was not read-protected. Using notifications of the main directory C:\, the researchers discovered that it was possible to track all file system events in all subfolders, including filenames. As browsers such as Firefox create a separate folder for every visited website that requires local storage, with the folder name containing the name of the website, attackers can easily trace where users have been on the internet in real time.

Intercepting keystrokes and passwords

On Linux, the researchers used the “inotify” file notification system to track keystrokes within a read-protected file. Although Linux initially prevented direct monitoring on the file, it became possible as it was located in a readable folder, which allowed to spy on everything in it via the notification system. This made the keystrokes in the read-protected file visible. While the team could not see which keys had been pressed, inter-keystroke timing attacks have been around for more than two decades. Thanks to knowledge accumulated over the years, the time elapsing between individual keystrokes now reveals plenty of information.

On KDE Plasma, a popular desktop environment on Linux, the security researchers managed to overlay fake password entry windows on top of the genuine ones as soon as an authentication prompt was called up, even when the secure Wayland display server protocol was in use. To achieve this, they monitored the executable file of the “polkit” programming interface, which carries out authorisation checks. As soon as they detected an access attempt that opened a password window, the test attackers superimposed a fake password window over it so that users would enter their details there and reveal their passwords.

Data exchange via WhatsApp

On Android, the “FUSE” system is actually intended to prevent apps from accessing each other's folders. Not even the folders’ contents should be visible. However, an app without special permissions was still able to spy on activity within another app’s folder by using file notifications as a workaround. The team was thus able to observe whether images, videos and files were arriving in, being sent from or deleted from WhatsApp's folders. The researchers emphasize that they could not see the contents of these files, but they could read the file names, which might reveal something about the file’s contents and the behaviour of the user using the Android phone.

While macOS exposes the least amount of information via globally readable files, the team found that user, application, and system behaviour can still be tracked, pointing out that the macOS “FSEvents” application programming interface (API) still yields meaningful insight into user activity.

As is customary in such cases, the research team alerted the relevant teams at Linux, KDE, Android, Microsoft and Apple to the potential vulnerabilities at an early stage so they could respond before the paper was published. In collaboration with the Linux security team, patches have already been rolled out to address some of the vulnerabilities.

Publication: File Notification Attacks: Templating and Exploiting Side-Channel Leakage from the File-Notification Systems on Linux, Windows, and macOS
Authors: Sudheendra Raghav Neela, Xufan Zhao, Jeanette Angelika Wultsch, Hannes Weissteiner, Florian Draschbacher, Stefan Gast and Daniel Gruss
Available at: https://inoti.fyi 

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AI chatbots give us a narrow slice of knowledge: Researchers warn of ‘knowledge collapse’





University of Copenhagen






“Let me just ask the chatbot.” For many of us, this has become an everyday phrase. Where we used to turn to Google to find information, AI chatbots have become a common way of getting answers to everything from what to make for dinner and how to word that difficult email to the boss, to what it actually means when interest rates rise.

But the large language models underpinning AI chatbots give us a significantly narrower range of information than a conventional web search. This is the finding of a new study led by researchers at the Department of Computer Science (DIKU) at the University of Copenhagen.

“Every language model we tested provides users with more uniform information than a simple Google search across all the topics we looked at. In other words, people are to a large extent exposed to the same information over and over again. So AI chatbots are not just changing how we find knowledge, but also which knowledge we have access to,” says first author Dustin Wright, a former postdoctoral researcher at DIKU who is now an assistant professor at Aalborg University.

At least 18% less diverse than Google

The researchers tested 27 different large language models on 155 topics. For each topic, they used 200 different prompt formulations based on questions from real users. This generated a dataset containing around 70 million individual claims produced by the models.

The results show that even the language model producing the most diverse answers – OpenAI’s GPT-5 – provides at least 18.7 per cent less varied information than Google. The topics tested by the researchers ranged from nuclear weapons, marriage, pornography, racism and genocide to more country-specific topics such as Marine Le Pen, the Falklands War and K-pop.

According to the researchers, the fact that people are increasingly using AI models as their primary gateway to information could have significant consequences:

“We risk exposing people to fewer perspectives and a narrower range of knowledge. This could create a vicious cycle in which the most popular content becomes even more dominant, while other content is increasingly overlooked,” says Professor at DIKU and senior author Isabelle Augenstein, adding:

“It’s similar to globalisation. Today, you can buy the same products and find the same coffee chains almost everywhere in the world. That has many advantages, but it has also reduced diversity.”

Why is diversity so low?

According to the researchers, the low level of diversity in language models is partly a result of how the models basically work. They compress the vast amount of text they are trained on and learn the patterns that occur most frequently. In the process, information that deviates from the most common patterns is filtered out.

The effect could be amplified if language models are increasingly trained on text produced by other AI models – something the researchers expect to happen. In that case, models would learn from their own outputs, which are already less diverse than the human-written texts on which they were originally trained.

If this process is repeated over several generations of models, the range of information could gradually become narrower. This is what the researchers refer to as ‘knowledge collapse’.

“It’s a worrying thought. However, we can see that the more recent models produce slightly more diverse answers than older models, so knowledge collapse is not happening yet. But the mechanism that could trigger it in the longer term is already there. So it is something we should be aware of,” says Isabelle Augenstein.

Seek out different sources

The researchers therefore also hope that people will use AI thoughtfully:

“AI chatbot summaries can of course be useful – that is why so many people use them. But it is still important to seek out different sources in order to understand the nuances and get a broader picture – especially for the younger generation growing up with AI. We must not become so dependent on the technology that we stop understanding and thinking for ourselves,” says Isabelle Augenstein.

The AI industry should also pay attention to the issue, the researchers argue:

“We hope AI developers will build language models in a way that preserves the breadth of knowledge available to us. We have developed a method that they can use to measure diversity in models, which could help ensure that future language models do not become less diverse,” says Dustin Wright.

 

[FACT BOX] ABOUT THE STUDY

  • The researchers analysed 27 large language models from OpenAI, Meta, Google and Alibaba.
  • The models were tested on 155 topics relating to 12 different countries.
  • The analysis covered around 1.7 million AI-generated answers and approximately 70 million individual claims.
  • The results show, among other things, that smaller AI models generate more diverse content than larger models, and that newer models are more diverse than older models. Overall, however, all the models had significantly lower diversity than traditional web search engines.
  • The research was conducted by researchers from the University of Copenhagen, Aalborg University, Stanford University, the University of Colorado Boulder and the University of Texas at Austin.
  • The study has been accepted for the international research conference EMNLP 2026, which takes place in October 2026. Read the research paper on arXiv.

 

[FACT BOX] HOW DOES AN AI CHATBOT WORK?

An AI chatbot is a service such as ChatGPT, Gemini or Claude that you can communicate with by typing or speaking and that provides answers in return. The chatbot uses a so-called large language model to understand questions and formulate responses.

A large language model is the underlying AI model that powers the chatbot. It is trained on very large amounts of text and learns patterns in how words and sentences relate to one another.

When you type a question into an AI chatbot, the chatbot sends it to the underlying large language model, which generates a response by predicting which words are most likely to fit your question.