Just in time for Christmas, a vast star-forming region shaped like a Christmas tree is lighting up space 2,700 light-years from Earth.
NGC 2,264 is a vast region of space where new stars are actively forming, located about 2,700 light-years from Earth in the faint constellation Monoceros, also known as the Unicorn. Astronomers use catalog names like NGC 2,264 to identify and track objects beyond our solar system, and this particular one stands out for its intricate mix of glowing clouds and young stars. Positioned near the celestial equator and close to the flat disk of the Milky Way, this region is visible at certain times of year from much of the world.
How young stars light up space
Uranus and Neptune may not be the icy worlds we’ve long imagined. A new Swiss-led study uses innovative hybrid modeling to reveal that these planets could just as easily be dominated by rock as by water-rich ices. The findings also help explain their bizarre, multi-poled magnetic fields and open the door to a wider range of possible interior structures. But major uncertainties remain, and only future space missions will The Solar System is commonly grouped by planetary composition: four rocky terrestrial planets (Mercury, Venus, Earth and Mars), two massive gas giants (Jupiter and Saturn), and a pair of ice giants (Uranus and Neptune). However, new research from a scientific team at the University of Zurich (UZH) suggests that Uranus and Neptune may contain far more rock than previously assumed. The study does not argue that these planets must be either water-rich or rock-rich. Instead, it questions the long-standing idea that an ice-heavy interior is the only conclusion supported by available data. This broader interpretation also aligns with the finding that Pluto, a dwarf planet, is dominated by rock.
To better understand what lies inside Uranus and Neptune, the researchers created a specialized simulation technique. “The ice giant classification is oversimplified as Uranus and Neptune are still poorly understood,” says Luca Morf, PhD student at the University of Zurich and lead author of the work. “Models based on physics were too assumption-heavy, while empirical models are too simplistic. We combined both approaches to get interior models that are both “agnostic” or unbiased and yet, are physically consistent.”
The process begins with a randomly generated density profile representing the interior of each planet. The team then determines the gravitational field that would match observational measurements and uses that information to infer the possible composition. The cycle is repeated until the model best fits all available data.
Step inside the strange world of a superfluid, a liquid that can flow endlessly without friction, defying the common-sense rules we experience every day, where water pours, syrup sticks and coffee swirls and slows under the effect of viscosity. In these extraordinary fluids, motion often organizes itself into quantized vortices: tiny, long-lived whirlpools that act as the fundamental building blocks of superfluid flow.
An international study conducted at the European Laboratory for Non-Linear Spectroscopy (LENS), involving researchers from CNR-INO, the Universities of Florence, Bologna, Trieste, Augsburg, and the Warsaw University of Technology, has embarked on this journey by investigating the dynamics of vortices within strongly interacting superfluids, uncovering the fundamental mechanisms that govern their behavior.
Using ultracold atomic gases, the scientists open a unique window into this exotic realm, recreating conditions similar to those found in superfluid helium-3, the interiors of neutron stars, and superconductors.
Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving their explainability and reliability is constrained by massive resource requirements for examining and adjusting their behavior.
To tackle this challenge, a Manchester research team led by Dr. Danilo S. Carvalho and Dr. André Freitas have developed new software frameworks—LangVAE and LangSpace—that significantly reduce both hardware and energy resource needs for controlling and testing LLMs to build explainable AI. Their paper is published on the arXiv preprint server.
Their technique builds compressed language representations from LLMs, making it possible to interpret and control these models using geometric methods (essentially treating the model’s internal language patterns as points and shapes in space that can be measured, compared and adjusted), without altering the models themselves. Crucially, their approach reduces computer resource usage by more than 90% compared with previous techniques.
Researchers from the High Energy Nuclear Physics Laboratory at the RIKEN Pioneering Research Institute (PRI) in Japan and their international collaborators have made a discovery that bridges artificial intelligence and nuclear physics. By applying deep learning techniques to a vast amount of unexamined nuclear emulsion data from the J-PARC E07 experiment, the team identified, for the first time in 25 years, a new double-Lambda hypernucleus.
This marks the world’s first AI-assisted observation of such an exotic nucleus—an atomic nucleus containing two strange quarks. The finding, published in Nature Communications, represents a major advance in experimental nuclear physics and provides new insight into the composition of neutron star cores, one of the most extreme environments in the universe.
The region also plays a role in the gradual loss of hydrogen, a key component of water, or H2O. Tracking how hydrogen escapes from Earth may help explain why our planet has managed to hold onto its water while others have not, offering valuable clues in the search for potentially habitable exoplanets, or planets beyond our solar system.
NASA’s Carruthers Geocorona Observatory, named in honor of George Carruthers, is designed to capture the first continuous movies of Earth’s exosphere, revealing its full expanse and internal dynamics.
“We’ve never had a mission before that was dedicated to making exospheric observations,” said Alex Glocer, the Carruthers mission scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “It’s really exciting that we’re going to get these measurements for the first time.”
Two icons of discovery, NASA’s James Webb Space Telescope and NASA’s Curiosity rover, have earned places in TIME’s “Best Inventions Hall of Fame,” which recognizes the 25 groundbreaking inventions of the past quarter century that have had the most global impact, since TIME began its annual Best Inventions list in 2000. The inventions are celebrated in TIME’s December print issue.
“NASA does the impossible every day, and it starts with the visionary science that propels humanity farther than ever before,” said Nicky Fox, associate administrator, Science Mission Directorate, NASA Headquarters in Washington. “Congratulations to the teams who made the world’s great engineering feats, the James Webb Space Telescope and the Mars Curiosity Rover, a reality. Through their work, distant galaxies feel closer, and the red sands of Mars are more familiar, as they expanded and redefined the bounds of human achievement in the cosmos for the benefit of all.”
Decades in the making and operating a million miles from Earth, Webb is the most powerful space telescope ever built, giving humanity breathtaking views of newborn stars, distant galaxies, and even planets orbiting other stars. The new technologies developed to enable Webb’s science goals – from optics to detectors to thermal control systems – now also touch Americans’ everyday lives, improving manufacturing for everything from high-end cameras and contact lenses to advanced semiconductors and inspections of aircraft engine components.
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Warm dense matter is a state of matter that forms at extreme temperatures and pressures, like those found at the center of most stars and many planets, including Earth. It also plays a role in the generation of Earth’s magnetic field and in the process of nuclear fusion.
Although warm dense matter is found all over the universe, researchers don’t have many good theories to describe the physics of materials under those conditions. Measurements of a material’s electrical conductivity would help test and refine models of warm dense matter. However, classic probes for such measurements require contact with the material. These can’t be used because materials in a warm dense matter state are very hot, often as hot or even hotter than the surface of the sun. Consequently, information about the electrical conductivity has so far been inferred indirectly.
In other words, without direct measurements, “there’s a lot of stuff in the universe happening that we as physicists are still struggling to understand,” said Ben Ofori-Okai, assistant professor at the Department of Energy’s SLAC National Accelerator Laboratory and Stanford University and a researcher at the Stanford PULSE Institute.