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In the Mpemba effect, a warm liquid freezes faster than a cold one. Three studies investigate quantum versions of this effect, challenging our understanding of quantum thermodynamics.

Under certain conditions, warm water can freeze faster than cold water. This phenomenon was named the Mpemba effect after Erasto Mpemba, a Tanzanian high schooler who described the effect in the 1960s [1]. The phenomenon has sparked intense debates for more than two millennia and continues to do so [2]. Similar processes, in which a system relaxes to equilibrium more quickly if it is initially further away from equilibrium, are being intensely explored in the microscopic world. Now three research teams provide distinct perspectives on quantum versions of Mpemba-like effects, emphasizing the impact of strong interparticle correlations, minuscule quantum fluctuations, and initial conditions on these relaxation processes [3– 5]. The teams’ findings advance quantum thermodynamics and have potential implications for technologies, ranging from information processors to engines, powered by quantum resources.

In top-down strategies, physicists use observations of macroscopic (classical) phenomena to infer fundamental microscopic (quantum) processes; in bottom-up strategies, they use studies of those fundamental processes to predict classical phenomena. Historically, studies of the Mpemba effect began with empirical observations and ad hoc assumptions about the microscopic world. Despite descriptions of the effect by Aristotle and Descartes, and modern attention from Mpemba, the phenomenon has not influenced the field of thermodynamics. The Mpemba effect is complex, lacks a precise definition, and has reproducibility issues. As a result, experimental observations and explanations have been debated for decades without consensus, making the effect often seem like just a curiosity.

Researchers have successfully controlled the quantum mechanical properties of Andreev bound states in bilayer graphene-based Josephson junctions using gate voltage. Their research is published in Physical Review Letters. The research team includes Professors Gil-Ho Lee and Gil Young Cho from the Department of Physics at Pohang University of Science and Technology (POSTECH) in South Korea in collaboration with Dr. Kenji Watanabe and Dr. Takashi Taniguchi from National Institute for Materials Science (NIMS) in Japan.

Superconductors are materials that exhibit zero electrical resistance under specific conditions such as extremely low temperatures or high pressures. When a very thin normal conductor is placed between two superconductors, a supercurrent flows through the normal conductor due to the proximity effect where superconductivity extends into the normal conductor. This device is known as a Josephson junction.

Within the normal conductor, new quantum states called Andreev bound states are formed, which are crucial for mediating the supercurrent flow.

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The development of alternative platforms for computing has been a longstanding goal for physics, and represents a particularly pressing concern as conventional transistors approach the limit of miniaturization. A potential alternative paradigm is that of reservoir computing, which leverages unknown, but highly nonlinear transformations of input-data to perform computations. This has the advantage that many physical systems exhibit precisely the type of nonlinear input-output relationships necessary for them to function as reservoirs. Consequently, the quantum effects which obstruct the further development of silicon electronics become an advantage for a reservoir computer. Here we demonstrate that even the most basic constituents of matter–atoms–can act as a reservoir for computing where all input-output processing is optical, thanks to the phenomenon of High Harmonic Generation.

What is the future of generative AI compute?

— The future of generative AI compute involves embedding AI algorithms into the physics of the world to push the limits of density, spatial efficiency, and speed for AI, creating a full stack of software and hardware specifically designed for AI from first principles.

The first #Quantum #Supercomputers are here! Quantum enabled supercomputing promises to shed light on new quantum algorithms, hardware innovations, and error mitigation schemes. Large collaborations in the field are kicking off between corporations and supercomputing centers. Companies like NVIDIA, IBM, IQM, QuEra, and others are some of the earliest to participate in these partnerships.

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Thermodynamic computing has the potential to revolutionize AI and machine learning by harnessing thermal fluctuations for faster, more efficient, and lower power computing systems Questions to inspire discussion What is the future revolution in computing? —The future revolution in computing is harnessing thermal fluctuations for physics-based computing systems.

The path to quantum supremacy is complicated by a fairy tale challenge – how do you carry a cloud without changing its shape?

The potential solution sounds almost as fantastical as the problem. You could guide the cloud to dance as it travels, to the beat of a unique material known as a time crystal.

Krzysztof Giergiel and Krzysztof Sacha from Jagiellonian University in Poland and Peter Hannaford from Swinburne University of Technology in Australia propose a novel kind of ‘time’ circuit might be up to the task of preserving the nebulous states of qubits as they’re carried through tempests of quantum logic.

Scientists have produced a rare form of quantum matter known as a Bose-Einstein condensate (BEC) using molecules instead of atoms.

Made from chilled sodium-cesium molecules, these BECs are as chilly as five nanoKelvin, or about −459.66 °F, and stay stable for a remarkable two seconds.

“These molecular BECs open up an new research arenas, from understanding truly fundamental physics to advancing powerful quantum simulations,” noted Columbia University physicist Sebastian Will. “We’ve reached an exciting milestone, but it’s just the kick-off.”

A research team led by Academician Du Jiangfeng and Professor Rong Xing from the University of Science and Technology of China (USTC), part of the Chinese Academy of Sciences (CAS), in collaboration with Professor Jiao Man from Zhejiang University, has used solid-state spin quantum sensors to examine exotic spin-spin-velocity-dependent interactions (SSIVDs) at short force ranges. Their study reports new experimental findings concerning interactions between electron spins and has been published in Physical Review Letters.

The Standard Model is a very successful theoretical framework in particle physics, describing fundamental particles and four basic interactions. However, the Standard Model still cannot explain some important observational facts in current cosmology, such as dark matter and dark energy.

Some theories suggest that new particles can act as propagators, transmitting new interactions between Standard Model particles. At present, there is a lack of experimental research on new interactions related to velocity between spins, especially in the relatively small range of force distance, where experimental verification is almost non-existent.