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Milky Way’s own gravity can mimic dark matter clues, stellar stream simulations suggest

Most of the stars in our Milky Way galaxy sit neatly on a flat plane. But the space around our galaxy is much more chaotic. Rogue bands of stars called “stellar streams” orbit the Milky Way much like planets in our solar system orbit the sun.

Astronomers have long been fascinated by the possibility that stellar streams could indirectly reveal the presence of dark matter, that mysterious theorized substance that doesn’t interact with light or normal matter—except via gravity. However, a new University of Washington study casts doubt on a leading theory linking dark matter and stellar streams and raises new questions about both galactic phenomena.

“Dark matter makes up most of the mass in the universe and forms the scaffolding that galaxies grow on, but we still don’t know what it is,” said co-author Nora Shipp, a UW assistant professor of astronomy. “The Milky Way is one of the best laboratories we have for figuring that out, and stellar streams are one of the sharpest tools inside it.”

Light particles reveal critical scaling in a two-dimensional photon gas

A team of researchers from the University of Bonn, Heidelberg University and the National Autonomous University of Mexico has studied the critical behavior of light particles (photons) close to a phase transition. This critical scaling behavior, which sees thermodynamic quantities grow extremely large or diverge shortly prior to Bose-Einstein condensation, had never before been seen in photon gases until the researchers successfully secured precisely this proof.

In the research published in the journal Science Advances, the team measured the spatial correlations of a nearly non-interacting 2D photon gas trapped in a mirror box at the moment of condensation, determining the critical exponent—a quantity describing the rapid increase in the correlation length as the temperature changes near the phase transition.

The physics of kiiking, Estonia’s extreme sport of swinging

When an athlete swings upside down atop a 7-meter (23-foot) pendulum, it may seem like a feat of strength, courage or technique. A new study suggests it is something more fundamental: a striking demonstration of how intelligence emerges from the interaction of brain, body and environment.

In a paper published in the Journal of Nonlinear Science, Harvard researchers use mathematics, physics and control theory to analyze kiiking, an extreme sport invented in Estonia in which athletes pump a giant swing until they complete a full rotation.

At one level, the problem appears straightforward. The athlete repeatedly stands and squats to inject energy into the swing. Yet this simple action inspires a question that reaches far beyond sport, touching neuroscience, robotics, biology and human performance: How does an organism learn to exploit the dynamics of its environment to achieve a goal?

Geomimicry offers a new framework for engineering sustainable materials

When engineers look to nature for inspiration, they often turn to living systems. The flight of birds has influenced aircraft design, gecko feet inspired new adhesives and lotus leaves led to the development of self-cleaning surfaces.

Researchers at the University of Pennsylvania now argue that engineers should look somewhere else in nature as well: the ground beneath their feet.

In a perspective paper published in Physical Review E, the team introduces geomimicry, a framework that asks how soils, sediments and other Earth-mediated materials have been shaped over geologic time and how those processes can inspire the next generation of sustainable materials.

ATLAS and CMS narrow in on twin Higgs production

Finding one Higgs boson was hard enough, but physicists at the Large Hadron Collider (LHC) are hunting for something even more elusive: pairs of Higgs bosons. At the recent International Conference on High Energy Physics 2026, the ATLAS and CMS collaborations presented new constraints on the double-Higgs production rate, providing insight into how the Higgs boson interacts with itself.

The discovery of the Higgs boson in 2012 at the LHC marked the beginning of a new era in particle physics. Since then, researchers at the LHC have investigated and measured how the Higgs boson interacts with other particles, an important mechanism by which these particles get their mass.

However, physicists have yet to observe the Higgs boson interact with itself. Understanding this process would not only test the limits of the Standard Model, our current best working theory for particle physics, but also help shed light on whether the vacuum of our universe is stable.

Low oxygen could limit insects’ uphill escape from climate warming

Reduced oxygen levels and air pressure at higher elevations may limit insects’ ability to move upslope to escape a warming climate, with potential consequences for the essential services they provide, like pollination, according to a new review in the journal, Functional Ecology.

Under a warming climate, many species are shifting their ranges to higher elevations to remain in suitable temperature zones. However, conditions at higher elevations, such as thinner air and less oxygen, pose unique challenges to insects because of their size, life cycle and way of breathing.

To understand how moving to higher elevations could affect different insect species, researchers from the University of Montana reviewed research on the physiological effects of hypoxia (low oxygen levels) and hypobaria (low pressure) on insects.

Fast but error-prone AI assists in solving a decades-old fluid mechanics problem in five weeks

An AI assistant helped University of Colorado Boulder researchers solve a mathematical problem that had challenged their lab for a year and a half, though it made subtle errors along the way. The breakthrough could improve how scientists study nanoparticles—tiny particles about 1,000 times thinner than a human hair—but it reveals both the promise and limitations of AI as a scientific research partner.

The new study, published in the Journal of Fluid Mechanics, details the solution to a decades-old fluid mechanics problem and explains how researchers combined AI with human expertise to reach the answer.

The research was led by Ankur Gupta, an assistant professor of chemical and biological engineering, and his graduate student, Arkava Ganguly, who spent a year and a half working on the problem. With help from Anthropic’s Claude AI, they discovered that changing a nanoparticle’s shape, such as by stretching it from a circle to a football shape, changes how fast it moves in an electric field, while adding finer features, such as bumps or ripples, does not.

Deep underground, SuperCDMS begins hunting light dark matter with 24 cryogenic crystals

In the hunt for one of nature’s most elusive substances—dark matter, which makes up 85% of all matter in the universe—scientists are going to extremes. Deep underground and chilled to near absolute zero, the Super Cryogenic Dark Matter Search (SuperCDMS) SNOLAB—one of the world’s most sensitive dark matter searches—has begun collecting its first scientific data.

During this early-science phase, the team will fine-tune the system for its full-scale search, set to begin in 2027. Although the experiment isn’t yet operating at full sensitivity, it could still deliver meaningful results.

“The search for dark matter at SuperCDMS SNOLAB is finally underway,” said Tina Cartaro, SuperCDMS operations manager at the Department of Energy’s SLAC National Accelerator Laboratory.

From cartwheels to backflips, motion-imitation framework teaches three robots dynamic movements

Legged robots, robotic systems with legs that typically resemble those of animals or humans, could be advantageous for completing tasks in home environments or populated, dynamic spaces. These robots may look like humans or animals, yet they often cannot reliably replicate complex whole-body movements in a short time.

Training robots on new movements typically entails designing a controller or policy—the software that decides how a robot will move—and adjusting it to produce desired motions. This process can be time-consuming and is not ideal for rapidly teaching robots various agile movements.

Researchers at the Robotics and AI (RAI) Institute and Boston Dynamics recently developed a new framework that can translate recorded or animated movements into robot control strategies. The new framework, introduced in a paper published in Science Robotics, was successfully used to teach two humanoids and one four-legged robot new dynamic movements.

Mirror-image molecules steer electron spins and lift perovskite solar cell efficiency

Some molecules come in two “handed” forms. This property, called chirality, can influence not only how molecules interact with light but also which electron spins they allow to pass. Researchers at the University of Osaka have developed novel chiral hole-transport materials that shed new light on this unusual effect while also improving the interfaces of perovskite solar cells.

The research is published in the journal Small.

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