In a breakthrough that reshapes our understanding of quantum materials, an international team of physicists has finally solved a decades-old mystery about how certain materials suddenly lose their ability to conduct electricity. The answer lies in an elusive quantum phenomenon known as a polaron — a quasiparticle formed when an electron becomes tightly coupled to the vibrations of the surrounding crystal lattice. This subtle “dance” between electrons and atoms can transform a good conductor into a perfect insulator.
The discovery, made by researchers from Kiel University and the DESY research center in Germany, including Professor Kai Rossnagel and Dr. Chul-Hee Min, provides the first direct evidence of polarons in a rare-earth compound composed of thulium, selenium, and tellurium (TmSe1–x Tex). Their findings, published in Physical Review Letters, illuminate one of quantum physics’ most puzzling phenomena: how subtle atomic vibrations can “kill” electrical conductivity.
A question that has vexed physicists for the past century may finally have a solution – but perhaps not the one everyone was hoping for.
In a new, detailed breakdown of current theory, a team of physicists led by Mir Faizal of the University of British Columbia has shown that there is no universal “Theory of Everything” that neatly reconciles general relativity with quantum mechanics – at least, not an algorithmic one.
A natural consequence of this is that the Universe can’t be a simulation, since any such simulations would have to operate algorithmically.
🌌 Unifying AI Through the Feynman Path Integral: From Deep Learning to Quantum AI https://lnkd.in/g4Cfv6qd I’m pleased to share a framework that brings many areas of AI into a single mathematical structure inspired by the Feynman path integral — a foundational idea in quantum physics. Instead of viewing supervised learning, reinforcement learning, generative models, and quantum machine learning as separate disciplines, this framework shows that they all follow the same underlying principle: Learning is a weighted sum over possible solutions (paths), based on how well each one explains the data. In other words, AI can be viewed the same way Feynman viewed physics: as summing over all possible configurations, weighted by an action functional.
A theoretical framework predicts the emergence of non-reciprocal interactions that effectively violate Newton’s third law in solids using light, report researchers from Japan. They demonstrate that by irradiating light of a carefully tuned frequency onto a magnetic metal, one can induce a torque that drives two magnetic layers into a spontaneous, persistent “chase-and-run” rotation. This work opens a new frontier in non-equilibrium materials science and suggests novel applications in light-controlled quantum materials.
In equilibrium, physical systems obey the law of action and reaction as per the free energy minimization principle. However, in non-equilibrium systems such as biological or active matter—interactions that effectively violate this law—the so-called non-reciprocal interactions are common.
For instance, the brain comprises inhibitory and excitatory neurons that interact non-reciprocally; the interaction between predator and prey is asymmetric, and colloids immersed in an optically active media demonstrate non-reciprocal interactions as well. A natural question arises: Can one implement such non-reciprocal interaction in solid-state electronic systems?
Geiger-mode avalanche photodiodes (GM-APDs) are highly sensitive light detectors, capable of detecting single photons. Photons of certain wavelengths, when absorbed by photodiodes, generate electron-hole pairs in a process called impact ionization which can result in a multiplication of charges when occurring in an electric field.
An avalanche photodiode is biased above its “breakdown voltage,” at which point impact ionizations reach a self-sustaining rate, resulting in a distinct electrical pulse that is readily detectable. To detect single photons in the presence of other mechanisms that generate impact ionization, the avalanche diode must simultaneously have a high probability to absorb incident photons of the desired wavelength, known as the unity-gain quantum efficiency (QE). Both being able to support high fields and having good QE at the desired wavelength are critical factors in determining the device’s sensitivity.
Certain GM-APDs based on 4H-silicon carbide (4H-SiC) have high single-photon detection efficiency in the deep-ultraviolet (DUV) wavelengths around 280 nanometers. To reliably detect photons at higher wavelengths where absorption is weaker, SiC GM-APDs need to improve their baseline photon capture efficiency, as indicated by its unity-gain QE. To accomplish this, researchers often employ APDs with much thicker absorber layers. However, this can often lead to design challenges.
Quantum computers have the potential to model new molecules and weather patterns better than any computer today. They may also one day accelerate artificial intelligence algorithms at a much lower energy footprint. But anyone interested in using quantum computers faces a steep learning curve that starts with getting access to quantum devices and then figuring out one of the many quantum software programs on the market.
Now qBraid, founded by Kanav Setia and Jason Necaise ‘20, is providing a gateway to quantum computing with a platform that gives users access to the leading quantum devices and software. Users can log on to qBraid’s cloud-based interface and connect with quantum devices and other computing resources from leading companies like Nvidia, Microsoft, and IBM. In a few clicks, they can start coding or deploy cutting-edge software that works across devices.
“The mission is to take you from not knowing anything about quantum computing to running your first program on these amazing machines in less than 10 minutes,” Setia says. “We’re a one-stop platform that gives access to everything the quantum ecosystem has to offer. Our goal is to enable anyone—whether they’re enterprise customers, academics, or individual users—to build and ultimately deploy applications.”
Having good neighbors can be very valuable—even in the atomic world. A team of Amsterdam physicists was able to determine an important property of strontium atoms, a highly useful element for modern applications in atomic clocks and quantum computers, to unprecedented precision. To achieve this, they made clever use of a nearby cloud of rubidium atoms. The results were published in the journal Physical Review Letters this week.
Strontium. It is perhaps not the most popularly known chemical element, but among a group of physicists it has a much better reputation—and rightfully so.
Strontium is one of six so-called alkaline earth metals, meaning that it shares properties with better-known cousins like magnesium, calcium and radium. Strontium atoms have 38 protons in their nucleus, and a varying number of neutrons—for the variations (or isotopes) of strontium that can be found in nature, either 46, 48, 49 or 50.
At 4 degrees Kelvin, most electro-optic materials falter. Nanoelectronics R&D center imec has now successfully engineered thin-film strontium titanate (SrTiO₃) that delivers record electro-optic performance with low optical loss, pointing to shorter, faster building blocks for quantum devices.
Quantum computers and detectors run at temperatures close to absolute zero. In these extreme conditions, even the best room-temperature materials struggle to control light efficiently. This feature is essential to encode, route, and convert information in electro-optic networks, which at room temperature are used in data and telecom applications, but also increasingly for ultra-low temperature quantum links.
In a new paper published today in Science, imec researchers, in collaboration with KU Leuven and Ghent University, report how they re-engineered a common crystal, strontium titanate (SrTiO₃), so it behaves with record performance at cryogenic temperatures.
Scientists have designed a topological quantum battery that can charge efficiently without losing energy, using the unique properties of quantum mechanics and topology.
Their research suggests dissipation, long considered harmful, might actually boost power in these next-generation batteries.
Quantum Leap in Energy Storage.