Physics Magazine
@physicsmagazine.aps.org
Exploring the people, ideas, and stories behind physics research.
Researchers have developed an algorithm that predicts the properties of heatwaves, floods, and other extreme weather events. It does so by integrating fast AI weather forecasts with an accurate climate model.
AI Improves Extreme Weather Simulations
A new algorithm combines AI weather forecasts with a physics-based climate model to efficiently characterize rare and dangerous weather events.
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Colony-wide activity among ants occurs either steadily or in sudden bursts. Researchers have found that switching from one state to the other can be modeled as a phase transition controlled by the speed at which ants travel and other parameters.
Phase Transition in Ant Colonies
Two types of ant colonies—one that experiences sudden bursts of activity and one that doesn’t—exemplify two distinct phases of collective behavior.
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Researchers have demonstrated a tabletop setup that can create radium-containing molecules, cool them to cryogenic temperatures, and measure their properties with high resolution. The technique could lead to new tests of physics beyond the standard model.
Radioactive Molecules Promise Probe of New Physics
A tabletop method for producing cold radioactive molecules enables precise measurement of their properties and could uncover violations of fundamental symmetries.
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The first quantitative measurement of the antineutrino flux from shutdown-reactor cores and nearby spent-fuel pools suggests that antineutrinos could be used to monitor possibly illicit nuclear material even when reactors are not running.
Detecting the Illicit Removal of Nuclear Fuel
Spent nuclear fuel and shutdown nuclear reactors emit antineutrinos, which nuclear watchdogs could use for real-time monitoring of plants.
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A metamaterial can slow down different frequency components of a broadband signal at different positions, thereby sorting the signal in space. This “rainbow trapping” has now been implemented for elastic waves in stiff media.
Catching and Guiding an Elastic Rainbow
Two experiments demonstrate a promising platform for trapping, sorting, and directing vibrational energy.
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Inspired by bone and spider silk, researchers have used machine learning to devise new disordered metamaterials. These structures not only have the properties they were designed for, but they also resist deformation and fracture.
Predicted Noncrystalline Structures Have Bonus Properties
Simulations reveal disordered structures that are also surprisingly resistant to impacts and cracks.
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Researchers have run simulations on a supercomputer to gain insights that could make it easier for ITER and other large tokamaks to attain quasicontinuous exhaust, a mode that removes excess heat while keeping the plasma tightly confined.
Tapping Tokamak Turbulence
Supercomputer simulations reveal how turbulence supports a Goldilocks regime for operating a fusion reactor.
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Researchers have built a CMOS-compatible photodiode for the room-temperature detection of short-wave IR. The new device has the potential to expand the accessibility of SWIR cameras for night vision and other applications.
Hyperdoped Silicon Photodiode Sets Efficiency Record
A new light-trapping architecture could lead to CMOS-compatible night-vision technology.
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A new machine-learning model can predict how inorganic crystals respond to an electric field. Thanks to its accuracy and efficiency, the model could accelerate the discovery and optimization of new functional materials.
Efficient Predictions of Electric Response
An AI model accurately estimates quantities that determine a material’s response to electric fields—at a fraction of the usual computational cost.
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With a novel machine-learning approach, a team of researchers has shown how densely packed, deeply intertwined showers of particles can be distinguished within the deluge of collisions created by the Large Hadron Collider.
Unpacking Particle Showers with Machine Learning
A new AI-powered event-processing algorithm is being readied to cope with the torrent of data that will stream from the Large Hadron Collider upgrade.
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In a Q&A, Nicole Yunger Halpern discusses how she brings her research in quantum thermodynamics to the public via steampunk, a subgenre of science fiction in which Victorian steam engines power modern technologies.
Welcome to the Quantum-Steampunk Laboratory
Nicole Yunger Halpern brings her quantum thermodynamics research to the public via analogies to a futuristic Victorian adventure.
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A new atomic force microscope takes images quickly and doesn’t have to operate at a fixed height. Researchers can use the instrument to watch chemical reactions unfold on surfaces in real time and to probe the structures of complex, 3D molecules.
Molecular Imaging Without the Wait
A new atomic force microscope captures the structures of individual molecules and their chemical bonds at record speeds.
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Researchers have implemented a quantum neural network across two different quantum-computing platforms: trapped ions and superconducting qubits. The feat will help establish whether trainable models can make use of superposition and other quantum effects.
Quantum Neural Networks Face the Hardware Test
By implementing a quantum neural network using two quantum-computing platforms, researchers have taken steps toward determining whether such systems can reliably fulfill their theoretical promise.
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Researchers have proposed a way to realize the Sachdev-Ye-Kitaev (SYK) model in the lab using cold atoms. The proposal provides a practical path to simulating information scrambling in black holes and other quantum phenomena described by the SYK model.
A Map to a Long-Sought Quantum Simulator
Ultracold atoms in an optical lattice could emulate a prominent model of quantum matter linked to black holes and high-temperature superconductors.
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Molecules are exquisitely sensitive to physics beyond the standard model. They are also sensitive to external fields, which can mask new physics. Now researchers have figured out how to better protect molecules from those confounding fields.
Noise Proofing Molecules for New-Physics Searches
Certain molecules can be placed into states that are less sensitive to external noise, offering researchers a quiet system for probing fundamental physics.
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Researchers have found experimental signatures of a fractional topological insulator in a slightly twisted bilayer of molybdenum ditelluride. The state interests physicists because it could conceivably be used for fault-tolerant quantum computing.
Evidence Emerges for a Fractional Topological Insulator
Experiments show signs of a material that conducts electricity in opposite directions along its edges through fractionally charged quasiparticles.
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A new theory encompasses so-called next-generation states of the fractional quantum Hall effect. In principle, the quasiparticles in those states could be harnessed for fault-tolerant quantum computing.
Untangling the Nature of Exotic Hall States
A new theory examines the various ways quasiparticles pair up in two-dimensional semiconductors under high magnetic fields.
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A new study combines seismic data from NASA’s InSight lander with thermodynamic and geophysical modeling to infer that Mars once hosted vast magma chambers capable of supplying a chemically evolved crust.
Evidence Builds for Martian Magma Chambers
A mineral physics interpretation of NASA seismic data hints that Mars has a chemically evolved crust.
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Researchers have calculated what would happen if a mirror were to vanish suddenly while a single photon’s wave packet was in the process of reflecting from it. The surprising answer: a quantum state of countless daughter photons.
Cutting the Tail of a Photon
Removing a mirror while a single photon is in the process of reflecting creates a quantum state of countless photons, theorists say.
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If a fabric unravels in one spot, how likely is it to come fully undone? The question can be posed as one of topological defect propagation in a periodic structure. Now physicists have an answer that could lead to fabrics with controllable damage resistance.
Unraveling the Topology of Knitted Fabrics
A framework based on knot theory links the robustness of textiles to the way defects propagate through them.
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Two independent research teams have devised a new way to sustain a continuous, uninterrupted entangled link between distant qubits. Their goal: creating a large modular quantum system that is greater than the sum of its parts.
Entanglement Goes Steady
Two independent groups have demonstrated ways to entangle quantum bits without the need for precisely timed control pulses.
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The struggle to supply AI models with enough energy to sustain them prompts the questions: how did new technologies overcome similar bottlenecks in the past? and how might they do so in the future, real or imagined?
Horse Manure, Transistors, and AI
What can past bottlenecks and imagined technologies tell us about the future of AI?
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The Moon should jiggle when gravitational waves pass by, and seismometers on the lunar surface could detect them. New research suggests that the signal may be stronger than expected, especially in regions on the Moon's farside where the crust is thicker.
Plans for Moon-Based Gravitational-Wave Detectors Get a Lift from Geology
A proposed gravitational-wave observatory on the Moon might gather more information than previously thought, thanks to geology.
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Researchers have proposed performing quantum simulations using arrays of helium-3 atoms. Because the species is so light, atoms can be shuttled about more quickly than heavier ones, enabling more operations before the atoms lose their quantum coherence.
A Blueprint for a Quantum Simulator Made of Helium Atoms
New theoretical work indicates that an array of helium-3 atoms could enable more complex quantum simulations.
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The male fruit fly produces sperm cells that are as long as its entire 2-mm body. New research has revealed how the fly can store thousands of these cells in a tiny reproductive organ only a tenth as wide as the cells are long.
Videos Reveal the Secret to Giant Sperm Packing
The exceptionally long sperm of fruit flies are able to fit in their small storage organ by swimming in opposite-direction lanes, new experiments show.
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Like other 2D lattices, skyrmion lattices can exhibit defects where one skyrmion has a surfeit or a deficit of neighbors. Now researchers have developed a way to control and study these defects, which could potentially be used to store information.
Stabilizing Magnetic Defects
Researchers have shown that defects in lattices of magnetic quasiparticles called skyrmions can be created, stabilized, and manipulated.
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Whether new words, concepts, and memes spread rapidly depends on how rooted they are in specific communities. The deeper the roots, the slower the spread.
Differences Between Niche and Mainstream Trends
A study of online language shows that niche terms—like the name of a narrowly popular music group—spread less quickly than mainstream words.
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Researchers have inferred that a subset of gravitational wave observations arises from hierarchical mergers. In these events, at least one member of the pair is not the remnant of a dead star but instead the product of a previous black hole merger.
Evidence Mounts for Hierarchical Black Hole Mergers
Different analyses of gravitational-wave observations are converging on evidence for a distinct population of massive black hole binaries produced through repeated mergers.
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Researchers have demonstrated a spectroscopic method for characterizing the geometry and spin configuration of clusters of 3–12 iron atoms. Their technique could improve understanding of iron clusters in interstellar space and industrial catalysis.
Illuminating Iron Clusters’ Magnetism
A technique combining spectroscopy and computational simulations allows the geometry and spin magnetic moment of iron nanoclusters to be determined more precisely.
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The collective behavior of networks of neurons appears to be governed by just a few variables, suggesting that a mean-field theory is applicable. Now researchers have found that they can indeed use mean-field theory to describe a network's activity patterns.
Rethinking Mean-Field Theory for Neural Networks
An extended version of mean-field theory accurately captures activity patterns seen in networks of biological neurons.
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