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Category: physics – Page 8

In 2024 a shockwave rippled through the astronomical world, shaking it to the core. The disturbance didn’t come from some astral disaster at the solar system’s doorstep, however. Rather it arrived via the careful analysis of many far-distant galaxies, which revealed new details of the universe’s evolution across eons of cosmic history. Against most experts’ expectations, the result suggested that dark energy —the mysterious force driving the universe’s accelerating expansion—was not an unwavering constant but rather a more fickle beast that was weakening over time.

The shocking claim’s source was the Dark Energy Spectroscopic Instrument (DESI), run by an international collaboration at Kitt Peak National Observatory in Arizona. And it was so surprising because cosmologists’ best explanations for the universe’s observed large-scale structure have long assumed that dark energy is a simple, steady thing. But as Joshua Frieman, a physicist at the University of Chicago, says: “We tend to stick with the simplest theory that works—until it doesn’t.” Heady with delight and confusion, theorists began scrambling to explain DESI’s findings and resurfaced old, more complex ideas shelved decades ago.

In March 2025 even more evidence accrued in favor of dark energy’s dynamic nature in DESI’s latest data release—this time from a much larger, multimillion-galaxy sample. Dark energy’s implied fading, it seemed, was refusing to fade away.

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Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence (AI) model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data.

AI often struggles with analyzing complex information that unfolds over long periods of time, such as climate trends, biological signals, or financial data. One new type of AI model called “state-space models” has been designed specifically to understand these sequential patterns more effectively. However, existing state-space models often face challenges—they can become unstable or require a significant amount of computational resources when processing long data sequences.

To address these issues, CSAIL researchers T. Konstantin Rusch and Daniela Rus have developed what they call “linear oscillatory state-space models” (LinOSS), which leverage principles of forced harmonic oscillators—a concept deeply rooted in physics and observed in .

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Four physicists at the Hebrew University of Jerusalem, in Israel, have unraveled the mechanical process behind the growth of roses as they blossom into their unique shape. In their study published in the journal Science, Yafei Zhang, Omri Cohen, Michael Moshe and Eran Sharon adopted a multipronged approach to learn the secrets behind rose blossom growth. Qinghao Cui and Lishuai Jin, with the University of Hong Kong have published a Perspective piece in the same journal issue outlining the work.

Roses have been prized for their beauty and sweet aromas for thousands of years, but until now, the mechanics behind growth have not been explored. To gain a better understanding of the process, the research team undertook a three-pronged approach. First, they conducted a theoretical analysis of the process. Then they created computer models to simulate the ways the flowers might grow and ; finally, they created real-world bendable plastic disks to simulate and the possible ways they could grow given the constraints of real roses.

They found that the shape of the petals is strongly influenced by the frustration known as the Mainardi-Codazzi-Peterson incompatibility, in which geometric compatibility conditions inherent on a surface made of a particular material are violated, leading to forces that generate rolling and sharp edges.

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Using ALMA, Teague’s team captured images of 15 young star systems sprinkled in space between a few hundred to 1,000 light-years from Earth. Rather than rely on direct detection of a young planet’s faint light, Teague’s team looked for the subtle clues these infant worlds imprint on their surroundings — such as gaps and rings in dusty disks, swirling gas motions caused by a planet’s gravity, and other physical disturbances that hint at a planet’s presence. To uncover these signatures, the researchers used ALMA to map the motion of gas within over a dozen protoplanetary disks.

“It’s like trying to spot a fish by looking for ripples in a pond, rather than trying to see the fish itself,” Christophe Pinte, an astrophysicist at the Institute for Planetary sciences and Astrophysics in France, who was also a principal investigator of the project, said in the statement.

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This extensive catalog spanning 11 billion years of cosmic history allows scientists to compare ancient galaxy structures with more recent ones, revealing evolutionary patterns in galaxy groups and their brightest central galaxies. The observations show a dramatic transformation: distant galaxies from the early universe appear irregular with active star formation, while those closer to our time have “quenched” star formation and developed more organised elliptical or spiral structures.

This groundbreaking JWST survey marks the beginning of a new era in understanding galactic evolution. With 1,700 galaxy groups identified across nearly the entire history of our universe, astronomers now have an unprecedented roadmap for further investigation. Future studies will explore the physics driving these transformations—from dark matter’s role in structural formation to how supermassive black holes influence their host galaxies. As researchers analyze this rich data, we can expect significant revisions to existing theories about galaxy formation and evolution.

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Polarization, along with intensity, wavelength, and phase, is a fundamental property of light. It enhances contrast and resolution in imaging compared to traditional intensity-based methods. On-chip polarization devices rely on complex four-pixel arrays or external polarizers.

Current solutions face two key challenges: limited spectral response in plasmonic and metasurface-based devices, and difficulty in simultaneously detecting the angle (AoLP) and degree (DoLP) of linear in low-dimensional anisotropic materials. Achieving wide-spectrum, high-precision polarization detection remains a critical challenge in the field.

To address this, a research team led by Prof. Li Liang from the Institute of Solid State Physics, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, in collaboration with Prof. Zhai Tianyou from Huazhong University of Science and Technology, has developed a novel “torsion unipolar barrier heterojunction” device.

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Recently, a research team achieved real-time tracking of electronic/magnetic structure evolution in Li-rich Mn-based materials during the initial cycling through the self-developed operando magnetism characterization device.

Their study, published in Advanced Materials, elucidated the critical mechanism underlying the oxygen reaction. The research team was led by Prof. Zhao Bangchuan from the Institute of Solid State Physics, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, in collaboration with Prof. Zhong Guohua from the Shenzhen Institute of Advanced Technology and Prof. Li Qiang from Qingdao University.

With the rise of electric vehicles and the low-altitude economy, the demand for high-energy-density batteries is growing. Li-rich Mn-based materials stand out due to their high capacity, wide voltage range, and .

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