“Quantum hybrid light-matter states, something often thought of as highly abstract, can actually make molecules easier to detect in practical conditions.”
Category: quantum physics – Page 23
Machine learning unravels quantum atomic vibrations in materials
Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group focuses on interactions among atomic vibrations, or phonons—interactions that govern a wide range of material properties, including heat transport, thermal expansion, and phase transitions. The new machine learning approach could be extended to compute all quantum interactions, potentially enabling encyclopedic knowledge about how particles and excitations behave in materials.
Scientists like Marco Bernardi, professor of applied physics, physics, and materials science at Caltech, and his graduate student Yao Luo (MS ‘24) have been trying to find ways to speed up the gargantuan calculations required to understand such particle interactions from first principles in real materials—that is, beginning with only a material’s atomic structure and the laws of quantum mechanics.
Last year, Bernardi and Luo developed a data-driven method based on a technique called singular value decomposition (SVD) to simplify the enormous mathematical matrices scientists use to represent the interactions between electrons and phonons in a material.
Machine learning and quantum chemistry unite to simulate catalyst dynamics
Catalysts play an indispensable role in modern manufacturing. More than 80% of all manufactured products, from pharmaceuticals to plastics, rely on catalytic processes at some stage of production. Transition metals, in particular, stand out as highly effective catalysts because their partially filled d-orbitals allow them to easily exchange electrons with other molecules. This very property, however, makes them challenging to model accurately, requiring precise descriptions of their electronic structure.
Designing efficient transition-metal catalysts that can perform under realistic conditions requires more than a static snapshot of a reaction. Instead, we need to capture the dynamic picture—how molecules move and interact at different temperatures and pressures, where atomic motion fundamentally shapes catalytic performance.
To meet this challenge, the lab of Prof. Laura Gagliardi at the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) and Chemistry Department has developed a powerful new tool that harnesses electronic structure theories and machine learning to simulate transition metal catalytic dynamics with both accuracy and speed.
Entanglement of photonic modes from a continuously driven two-level system
The ability to generate entangled states of light is a key primitive for quantum communication and distributed quantum computation. Continuously driven sources, including those based on spontaneous parametric downconversion, are usually probabilistic, whereas deterministic sources require accurate timing of the control fields. Here, we experimentally generate entangled photonic modes by continuously exciting a quantum emitter — a superconducting qubit — with a coherent drive, taking advantage of mode matching in the time and frequency domain. Using joint quantum state tomography and logarithmic negativity, we show that entanglement is generated between modes extracted from the two sidebands of the resonance fluorescence spectrum. Because the entangled photonic modes are perfectly orthogonal, they can be transferred into distinct quantum memories. Our approach can be utilized to distribute entanglement at a high rate in various physical platforms, with applications in waveguide quantum electrodynamics, distributed quantum computing, and quantum networks.
Yang, J., Strandberg, I., Vivas-Viaña, A. et al. Entanglement of photonic modes from a continuously driven two-level system. npj Quantum Inf 11, 69 (2025). https://doi.org/10.1038/s41534-025-00995-1
New laser technique reveals nearly 20 previously hidden states of matter
In 2023, physicist Xiaodong Xu at the University of Washington —working with researchers from Cornell and Shanghai Jiao Tong University —found that twisting atom-thin layers of molybdenum ditelluride into a special pattern called a moiré lattice could produce the fractional quantum anomalous Hall effect without magnets. This was a huge leap, because magnets can disrupt superconducting materials used in quantum technology.
Xu’s team discovered two such magnet-free fractional states. That alone was remarkable. But Zhu and his colleagues suspected there were more waiting to be found. The secret lies in the moiré pattern. When the layers are slightly rotated relative to each other, they form a honeycomb-like grid at the atomic scale.
This structure changes the way electrons move, encouraging them to team up in unusual ways that create fractional charges. In other words, the twist turns the material into a playground for exotic quantum phases.
First-principles simulations reveal quantum entanglement in molecular polariton dynamics
This is what fun looks like for a particular set of theoretical chemists driven to solve extremely difficult problems: Deciding whether the electromagnetic fields in molecular polaritons should be treated classically or quantum mechanically.
Graduate student Millan Welman of the Hammes-Schiffer Group is first author on a new paper that presents a hierarchy of first principles simulations of the dynamics of molecular polaritons. The research is published in the Journal of Chemical Theory and Computation.
Originally 67 pages long, the paper is dense with von Neumann equations and power spectra. It explores dynamics on both electronic and vibrational energy scales. It makes use of time-dependent density functional theory (DFT) in both its conventional and nuclear-electronic orbital (NEO) forms. It spans semiclassical, mean-field-quantum, and full-quantum approaches to simulate polariton dynamics.
Electrons that act like photons reveal a quantum secret
Quantum materials, defined by their photon-like electrons, are opening new frontiers in material science. Researchers have synthesized organic compounds that display a universal magnetic behavior tied to a distinctive feature in their band structures called linear band dispersion. This discovery not only deepens the theoretical understanding of quantum systems but also points toward revolutionary applications in next-generation information and communication technologies that conventional materials cannot achieve.
British Startup Installs New York City’s First Quantum Computer
A British startup has installed New York City’s first quantum computer at a data center in Manhattan.
Oxford Quantum Circuits has placed the system at a data center run by Digital Realty Trust in the Google building in Chelsea, billing the technology to customers of the site as a means of running artificial intelligence programs faster and more efficiently. Oxford Quantum Chief Executive Officer Gerald Mullally said he expects his firm to spend tens of millions of dollars over three to five years, in part to buy Nvidia Corp. chips to integrate into it. He declined to provide the exact costs of the computer.