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Binary neutron star mergers, cosmic collisions between two very dense stellar remnants made up predominantly of neutrons, have been the topic of numerous astrophysics studies due to their fascinating underlying physics and their possible cosmological outcomes. Most previous studies aimed at simulating and better understanding these events relied on computational methods designed to solve Einstein’s equations of general relativity under extreme conditions, such as those that would be present during neutron star mergers.

Researchers at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Yukawa Institute for Theoretical Physics, Chiba University, and Toho University recently performed the longest simulation of binary neutron star mergers to date, utilizing a framework for modeling the interactions between magnetic fields, high-density matter and neutrinos, known as the neutrino-radiation magnetohydrodynamics (MHD) framework.

Their simulation, outlined in Physical Review Letters, reveals the emergence of a magnetically dominated jet from the , followed by the collapse of the binary neutron star system into a black hole.

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Back in 2019, the Event Horizon Telescope (EHT) team revealed the first-ever image of a supermassive black hole in the galaxy M87. In 2022, they followed up with the iconic image of Sagittarius A at the heart of the Milky Way. While these images were groundbreaking, the data behind them held even deeper insights that were hard to decode.

Neural Networks Meet Black Hole Physics

Previous studies by the EHT Collaboration used only a handful of realistic synthetic data files. Funded by the National Science Foundation (NSF) as part of the Partnership to Advance Throughput Computing (PATh) project, the Madison-based CHTC enabled the astronomers to feed millions of such data files into a so-called Bayesian neural network, which can quantify uncertainties. This allowed the researchers to make a much better comparison between the EHT data and the models.

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IN A NUTSHELL 🌟 Anthropic is on a mission to develop artificial general intelligence that remains ethical and benevolent. 🎯 The company’s strategy, known as the Race to the Top, aims to set global standards for safe AI development. 🤖 Claude, Anthropic’s AI model, is designed to embody ethical principles and serve as a constant.

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A newly discovered mechanism that leads to liver dysfunction may be a key factor in type 2 diabetes and other metabolic disorders in individuals with obesity, according to a new study led by Harvard T.H. Chan School of Public Health.

The dysfunction identified—dysregulated hepatic coenzyme Q metabolism—leads to excessive reactive oxygen species (ROS) produced by mitochondria at a single specific site in an enzyme called complex I. The researchers say the discovery offers a potential path for new, precise treatments for metabolic diseases.

“Our findings provide the first step toward solving a complex problem in the field of metabolic disease research that has stood for three decades,” said corresponding author Gökhan S. Hotamisligil, James Stevens Simmons Professor of Genetics and Metabolism.

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Every action in physics is governed by some kind of push or pull. As far as we know, these all fall into one of just four categories; electromagnetism, gravity, and two kinds of nuclear force.

Yet there could well be forces hidden deep within the tiny storms of particle dynamics that have been simply too subtle to easily detect.

Physicists from Germany, Switzerland, and Australia have now placed new restrictions on where one example of a ‘fifth’ force may be hiding in the hearts of atoms, exchanging whispers between electrons and neutrons.

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The Standard Model of particle physics, our best guide to the building blocks of nature, once claimed neutrinos were massless. But that turned out to be wrong. Neutrinos do have mass—just an incredibly tiny one. So far, though, no experiment has measured that mass directly. That’s where the KATRIN experiment comes in.

KATRIN stands for the Karlsruhe Tritium Neutrino Experiment. It’s based in Germany and stretches nearly 70 meters, or about 230 feet—longer than a Boeing 747. Published in the journal, Science, the experiment uses a radioactive form of hydrogen called tritium, which naturally decays into helium. When this happens, it releases an electron and a neutrino.

By measuring the energy of the electron, scientists can figure out how much energy the neutrino took away. This helps them estimate the neutrino’s mass. The trick is, this has to be done with extreme accuracy. That’s why KATRIN includes one of the world’s most advanced spectrometers, which is 10 meters wide and filters out unwanted particles with precision.

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