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AI-assisted math advance highlights gap between finding answers and judging their significance

AI models are good at finding answers to mathematical puzzles but are not as good at research judgment, according to theoretical computer scientists.

The researchers, co-led by Princeton’s Pravesh Kothari, documented their use of AI in a case study shared on arXiv, outlining the ways in which AI tools excelled and fell short in reaching an important solution to an open mathematical problem.

AI is excellent at finding answers, they argue, because the models are trained on published papers, textbooks and solved problems. But, as of August 2026, these models were not as good at the process of recognizing the value of a theoretical result over numerical evidence or determining the significance, generality or downstream use of a result, according to the authors. This is because training data rarely includes information on the long process of mathematical discovery, which includes failed approaches, unlikely results and changes in strategy.

Rare particle decays hint at deviations from Standard Model predictions

Studying rare processes is part and parcel of particle physics, providing stringent tests of the Standard Model. At the recent International Conference on High Energy Physics (ICHEP), the CMS and LHCb collaborations presented their latest research into one such process: the transformation of a beauty quark into a strange quark, a muon and the oppositely charged antimuon (b→sμ⁺μ⁻).

Flavor transitions—when one type of quark turns into another—can only take place via the weak interaction, one of the four fundamental forces. Quantum physics describes how other particles, not directly involved in a particular transition, can influence how that transition takes place. If a process happens differently than is predicted by the influence of the particles we know about, which make up the Standard Model, this difference could point to the existence of as-yet-undiscovered particles and interactions.

Some of these transitions are extremely rare, which makes them very sensitive to any potential contributions from particles that may exist beyond the Standard Model. The b→sμ⁺μ⁻ transition is one such process, only occurring approximately once in every 10 million decays of particles containing beauty quarks, known as beauty particles. Over the past decade, signs have begun to appear that this transition may not occur as expected.

Quantum network test checks entanglement without having to trust detectors

Quantum networks are systems that connect different users or devices using principles of quantum mechanics. In the future, these networks could help improve the security of communications.

For entanglement-based quantum networks to work, however, researchers need to be able to verify that particles are entangled and assess the extent of their entanglement. Entanglement is a quantum mechanical effect in which the shared states of distant particles cannot be described as separate or independent.

Researchers at Shandong University recently introduced a new approach for verifying entanglement in a quantum network that does not require trusting the equipment used to analyze and detect photons (i.e., light particles), as most previously developed strategies do.

New framework links magnetic phase boundaries to string-like defects in spin ice

A research team led by Haruki Watanabe, a professor in the Department of Physics and the Jockey Club Institute for Advanced Study (IAS) at The Hong Kong University of Science and Technology (HKUST), in collaboration with professor Yukitoshi Motome and graduate student Sena Watanabe from the University of Tokyo, has developed a unified theory that predicts when two states of matter are genuinely distinct and when they are actually the same.

The work provides a general framework for classifying phases across magnetic systems with different spin values and resolves a long-standing debate surrounding the behavior of water ice under extreme pressure.

The paper, titled “Topological phase transitions and their thermodynamic fate in arbitrary- classical pyrochlore spin ice,” is published in Physical Review X.

IBM executive warns of risk of quantum computing hacks

Organizations are unprepared for the risks posed by quantum computing, IBM’s Europe and Africa vice president Alessandro Curioni told AFP Wednesday, referring to the high-speed technology that could crack security encryptions and enable large-scale cyberattacks.

“If you look at the world, how many organizations became quantum-safe? I would say less than 10% today,” Curioni said on the sidelines of a London conference organized by the American technology pioneer.

IBM, a leader in the field competing against Microsoft and Google, aims to develop a “large-scale, fault-tolerant” quantum computer for commercial clients by 2029.

Software advance brings complex quantum simulations to standard computers

A major software advance could aid the creation of bigger, more reliable quantum computers, a study suggests. Researchers have developed an algorithm that enables off-the-shelf computers to run quantum simulations previously only possible using the world’s most powerful supercomputers.

It means the simulations can be run using around 5% of the computing power previously needed to perform them with a supercomputer, the team says.

The advance could make it cheaper and easier to run experiments vital for understanding the limitations of current quantum computers and informing the design of improved devices, experts say.

New chip-scale gyroscope measures rotation with unprecedented sensitivity

Researchers have developed a chip-scale optical ring-laser gyroscope that can measure rotation as slow as 37 degrees per hour. This record sensitivity, approaching Earth’s rotation rate of 15 degrees per hour, could eventually be useful for precision navigation and orientation systems, particularly where GPS is unavailable.

Gyroscopes measure how an object rotates, helping determine its orientation and movement. The chip-based gyroscopes found in smartphones and other everyday devices tend to have limited sensitivity, making them unsuitable for some demanding applications. This has driven scientists to develop chip-based versions of optical gyroscopes, which are sensitive enough for applications such as aircraft navigation.

“Our new gyroscope combines several advanced technologies to achieve a high level of sensitivity in a format that can be made with standard CMOS chip-processing methods and uses just milliwatts of optical power,” said Daniel J. Blumenthal, who led the research team from the University of California, Santa Barbara. “A fully integrated optical gyroscope would not only be smaller than today’s systems but also have no moving parts and thus be very resilient to vibrations and shocks.”

Storing memory on a chip with flowing water

Like the folds in crumpled sheets or the footprints on recently trodden sand, certain materials mark their histories. Now, Yale researchers show that networks of flowing water and other fluids can store their own memories—similar to how a computer chip does—an innovation that could steer robots and provide insight into some simple organisms. The results are published in Physical Review X.

In Professor Amir Pahlavan’s lab, researchers created a small chip with multiple tiny channels, each with a depth about half the width of a human hair. Inside these channels, they placed a series of flexible microfibers that stand in the way of the fluid flowing through the channels. Pressure from the flow can cause the fibers to switch between two states, affecting how the fluid passes.

This forms a “memory” of past flows, making each fiber’s current state depend on its history and, when coupled, on the states of other fibers. The two stable configurations of each fiber can represent a zero or a one, much like a bit in computer memory.

From spin wave to superconducting circuit: A one-way street for quantum information

Quantum information systems could one day shape everyday life through faster computing, sharper sensing and more secure communication. A new result from the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Illinois Urbana-Champaign (U. of I.) marks an important step toward enabling magnetic spins—a quantum property of matter that can be used to store and manipulate information—to play a role in the future of quantum information processing.

The researchers show that ripples in the magnetic state of a material, called spin waves, can interact with superconducting circuits, tiny electrical circuits that can carry microwave signals. The result is a hybrid system in which these two different ways of carrying information can interact and work together.

One can think of it like a hybrid car: A gasoline engine and an electric motor operate in fundamentally different ways, but a hybrid vehicle connects them so they can work together. Similarly, the new quantum system brings together magnetic spin waves and superconducting circuits, potentially allowing researchers to combine the strengths of both.

Robotic ‘time crystal’ organizes itself into a single rhythm despite random disturbances

Scientists have developed a material that can grow and coordinate its own movement until the entire structure pulses in unison, paving the way for versatile robots that behave more like living systems.

Publishing their findings today (Oct. 14) in Nature, engineers from the University of Birmingham working with the universities of Amsterdam, Lyon, Delft, Leiden and Cambridge reveal that they have created a mechatronic metamaterial that behaves as a ‘time crystal.’ Time crystals are an unusual form of matter in which particles endlessly move in regular, repeating cycles. But here, the “particles” were not the atoms of molecules: they were robots.

The scientists’ experimental material combines elastic structures, sensors, electronics and actuators so that neighboring components can influence one another. The key ingredient to generate the time-crystalline state was making the interactions between components “nonreciprocal,” meaning that one component’s response to another does not have to be mirrored in reverse.