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Physicists employ AI labmates to supercharge LED light control

In 2023, a team of physicists from Sandia National Laboratories announced a major discovery: a way to steer LED light. If refined, it could mean someday replacing lasers with cheaper, smaller, more energy-efficient LEDs in countless technologies, from UPC scanners and holographic projectors to self-driving cars. The team assumed it would take years of meticulous experimentation to refine their technique.

Now the same researchers have reported that a trio of artificial intelligence labmates has improved their best results fourfold. It took about five hours.

The resulting paper, now published in Nature Communications, shows how AI is advancing beyond a mere automation tool toward becoming a powerful engine for clear, comprehensible scientific discovery.

New method reveals quantum states using indirect measurements of particle flows

A team from UNIGE shows that it is possible to determine the state of a quantum system from indirect measurements when it is coupled to its environment.

What is the state of a quantum system? Answering this question is essential for exploiting quantum properties and developing new technologies. In practice, this characterization generally relies on direct measurements, which require extremely well-controlled systems, as their sensitivity to external disturbances can distort the results. This constraint limits their applicability to specific experimental contexts.

A team from the University of Geneva (UNIGE) presents an alternative approach, tailored to open quantum systems, in which the interaction with the environment is turned into an advantage rather than an obstacle. Published in Physical Review Letters —with the “Editor’s Suggestion” label—this work brings quantum technologies a step closer to real-world conditions.

Bridging theories across physics helps reconcile controversy about thin liquid layer on icy surfaces

The ice in a domestic freezer is remarkably different from the single crystals that form in snow clouds, or even those formed on a frozen pond. As temperatures drop, ice crystals can grow in a variety of shapes: from stocky hexagonal prisms to flat plates, to Grecian columns.

Why this structural roller coaster happens, though, is a mystery. When first observed, researchers thought it must relate to a hypothesis proposed by famed physicist Michael Faraday—ice below its melting point has a microscopically thin liquid layer of water across its surface.

This “premelting film” of ice, however, is the subject of significant scientific controversy. For years, researchers have provided contradictory evidence about its thickness and whether it even exists.

AI-driven ultrafast spectrometer-on-a-chip advances real-time sensing

For decades, the ability to visualize the chemical composition of materials, whether for diagnosing a disease, assessing food quality, or analyzing pollution, depended on large, expensive laboratory instruments called spectrometers. These devices work by taking light, spreading it out into a rainbow using a prism or grating, and measuring the intensity of each color. The problem is that spreading light requires a long physical path, making the device inherently bulky.

A recent study from the University of California Davis (UC Davis), reported in Advanced Photonics, tackles the challenge of miniaturization, aiming to shrink a lab-grade spectrometer down to the size of a grain of sand, a tiny spectrometer-on-a-chip that can be integrated into portable devices. The traditional approach of spatially spreading light is abandoned in favor of a reconstructive method.

Instead of physically separating each color, the new chip uses only 16 distinct silicon detectors, each engineered to respond slightly differently to incoming light. This is analogous to giving a handful of specialized sensors a mixed drink, with each sensor sampling a different aspect of the drink. The key to deciphering the original recipe is the second part of the invention: artificial intelligence (AI).

Direct visualization captures hidden spatial order of electrons in a quantum material

The mystery of quantum phenomena inside materials—such as superconductivity, where electric current flows without energy loss—lies in when electrons move together and when they break apart. KAIST researchers have succeeded in directly observing the moments when electrons form and dissolve ordered patterns.

Research teams led by Professors Yongsoo Yang, SungBin Lee, Heejun Yang, and Yeongkwan Kim of the Department of Physics, in an international collaboration with Stanford University, have become the first in the world to spatially visualize the formation and disappearance of charge density waves (CDWs) inside quantum materials.

The research is published in Physical Review Letters.

DNA Breakthrough Solves Decade-Old Mystery of the Beachy Head Woman

New research suggests the mysterious Roman-era “Beachy Head Woman” was likely from Britain, not the Mediterranean or sub-Saharan Africa. Advances in DNA sequencing are helping researchers resolve a mystery that has surrounded the Beachy Head Woman for more than ten years. The remains of a youn

Depression’s impact on fairness perceptions depends on socioeconomic status

Depression may make unfair offers seem fairer, but only if you perceive yourself as having high social status. New research explores how socioeconomic status moderates the cognitive distortions associated with depression in financial decision-making.

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