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Search results for “XMM-Newton”

681 results for "XMM-Newton"

How large language models need symbolism

Experts argue that large language models require symbolic representation to excel in complex tasks, citing examples like the Pirahá people and Leibniz's calculus notation. The proposed approach, known as neuro-symbolic synthesis, combines statistical intuition with human-designed symbol systems for efficient reasoning.

SourceScience China Press·JournalNational Science Review·DateAug 20, 2025

Solved: 90-year-old mystery in quantum physics

Researchers at the University of Vermont found an exact solution to a model that behaves as a damped quantum harmonic oscillator. This discovery has significant implications for ultra-precision sensor technologies and the measurement of quantum distances.

SourceUniversity of Vermont·JournalPhysical Review Research·TypeExperimental study·DateAug 15, 2025

Connect or reject: Extensive rewiring builds binocular vision in the brain

A study published in Nature Communications reveals that neurons in mice brain rewire and refine their connections to integrate visual signals from both eyes over a 10-day period. The researchers found that only 40% of the initial synapses survived, with 24% added and 27% removed, indicating an extensive process of synaptic turnover.

SourcePicower Institute at MIT·JournalNature Communications·TypeExperimental study·DateJul 3, 2025

New AI tool set to speed quest for advanced superconductors

A new study published in Newton uses artificial intelligence to identify complex quantum phases in materials, significantly speeding up research into quantum materials. The breakthrough applies machine-learning techniques to detect clear spectral signals, allowing for a fast and accurate snapshot of phase transitions.

SourceEmory University·JournalNewton·TypeComputational simulation/modeling·DateApr 10, 2025

A hot droplet can bounce across a cool pan, too

Researchers discovered that hot and burning droplets can bounce off cool surfaces due to the formation of an invisible air cushion. This phenomenon has potential applications in slowing fire spread and improving engine efficiency.

SourceCell Press·JournalNewton·TypeExperimental study·DateMar 3, 2025

Even after learning the right idea, humans and animals still seem to test other approaches, study suggests

A new MIT study finds that humans and marmosets retain a tendency to test other approaches to tasks, even when they have learned the optimal strategy. This behavior could help reveal needed adjustments in uncertain environments. The findings also add weight to the use of marmoset models for autism studies.

SourcePicower Institute at MIT·JournalCurrent Biology·TypeExperimental study·DateFeb 18, 2025

Einstein Probe catches X-ray odd couple

Scientists discovered a rare binary system consisting of a massive Be star and a compact white dwarf, with the Einstein Probe catching the X-ray signal from its initial flare-up to its fading away. The analysis revealed clues about the elements present in the exploding material, including nitrogen, oxygen, and neon.

SourceEuropean Space Agency·JournalThe Astrophysical Journal Letters·TypeObservational study·DateFeb 18, 2025

Australian researchers enhance next-generation gene-editing technologies for cancer and medical research

Researchers at La Trobe University's Olivia Newton-John Cancer Research Institute have developed a novel pre-clinical model expressing an enhanced version of the Cas12a enzyme, which can delete multiple genes simultaneously with high efficiency. This breakthrough enables complex genetic disorders to be modeled and interrogated.

SourceLa Trobe University·JournalNature Communications·TypeExperimental study·DateJan 30, 2025

Electrically tunable planar liquid-crystal singlets for simultaneous spectrometry and imaging

Researchers have developed a new planar spectral singlet lens that unifies optical imaging and spectrometry, enabling simultaneous data acquisition. The device uses planar liquid crystal optics to achieve precise phase controls and spectral filtering, resulting in high-quality hyperspectral images.

"islands" of regularity discovered in the famously chaotic three-body problem

Astronomers have discovered patterns of regularity within the chaotic three-body problem, which is a fundamental challenge in physics. The researcher's findings suggest that certain configurations of three massive objects can lead to predictable outcomes, offering new insights into astrophysics and the behavior of black holes.

SourceUniversity of Copenhagen - Faculty of Science·JournalAstronomy and Astrophysics·DateOct 10, 2024

Precision instrument bolsters efforts to find elusive dark energy

Researchers have built the most precise experiment yet to look for gravitational anomalies caused by dark energy, using a lattice atom interferometer that can hold atoms in place for up to 70 seconds. While no deviation from predicted theory was found, the improved precision opens up possibilities for probing gravity at the quantum level.

SourceUniversity of California - Berkeley·JournalNature·TypeExperimental study·DateJun 26, 2024

AI as a physicist

Researchers at Forschungszentrum Jülich have programmed an AI that can recognize patterns in complex data sets and formulate them in a physical theory. The AI uses physics for machine learning to simplify complex interactions and build up a new theory.

SourceForschungszentrum Juelich·JournalPhysical Review X·DateFeb 7, 2024

“All_Aboard” app effectively aids blind and visually impaired commuters in finding bus stops

A new smartphone app called All_Aboard has been developed to aid blind and visually impaired individuals in finding bus stops. The app uses artificial intelligence and camera technology to detect street signs and provide auditory cues, achieving a success rate of 93% compared to Google Maps' 52%.

SourceMass Eye and Ear·JournalTranslational Vision Science & Technology·TypeExperimental study·DateJan 29, 2024

Hybrid machine learning method boosts resolution of electrical impedance tomography for structural imaging

Researchers developed a novel hybrid approach combining traditional mathematical methods and cutting-edge machine learning to improve EIT analysis of building structures. The new method, called AND, reduces errors in reconstructing foreign objects' position and size compared to conventional EIT methods.

SourceTokyo University of Science·JournalAIP Advances·TypeExperimental study·DateJan 22, 2024

Machine learning models can produce reliable results even with limited training data

Researchers from University of Cambridge and Cornell University have developed a method to build machine learning models that can understand complex equations using far less training data. This breakthrough enables the construction of more time- and cost-efficient models for physics, engineering, and climate modeling applications.

SourceUniversity of Cambridge·JournalProceedings of the National Academy of Sciences·DateSep 19, 2023