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Categories: Mathematics: Modeling, Space: Structures and Features

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The origin of heavy elements in our universe is theorized to be the result of neutron star collisions, which produce conditions hot and dense enough for free neutrons to merge with atomic nuclei and form new elements in a split-second window of time. Testing this theory and answering other astrophysical questions requires predictions for a vast range of masses of atomic nuclei. Scientists are using machine learning algorithms to successfully model the atomic masses of the entire nuclide chart -- the combination of all possible protons and neutrons that defines elements and their isotopes.

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Physicists often turn to the Rayleigh-Taylor instability to explain why fluid structures form in plasmas, but that may not be the full story when it comes to the ring of hydrogen clumps around supernova 1987A, research suggests. It looks like the same mechanism that breaks up airplane contrails might be at play in forming the clumps of hydrogen gas that ring the remnant of supernova 1987A.

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Existing ship control systems using Model Predictive Control for Maritime Autonomous Surface Ships (MASS) do not consider the various forces acting on ships in real sea conditions. Addressing this gap, researchers developed a novel time-optimal control method, that accounts for the real wave loads acting on a ship, enabling effective planning and control of MASS at sea.

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Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to healthcare. But these networks remain a black box whose inner workings engineers and scientists struggle to understand. Now, a team has given neural networks the equivalent of an X-ray to uncover how they actually learn.

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The formation of stars and the chaotic environments they inhabit is one of the most well-studied, but also mystery-shrouded, areas of cosmic investigation. The intricacies of these processes are now being unveiled like never before by NASA's James Webb Space Telescope.

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When you teach a child how to solve puzzles, you can either let them figure it out through trial and error, or you can guide them with some basic rules and tips. Similarly, incorporating rules and tips into AI training -- such as the laws of physics --could make them more efficient and more reflective of the real world. However, helping the AI assess the value of different rules can be a tricky task.

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A new safety-check technique can prove with 100 percent accuracy that a planned robot motion will not result in a collision. The method can generate a proof in seconds and does so in a way that can be easily verified by a human.

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Neutron star mergers are a treasure trove for new physics signals, with implications for determining the true nature of dark matter, according to physicists.

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A galaxy that suddenly stopped forming new stars more than 13 billion years ago has been observed by astronomers. Using the James Webb Space Telescope, astronomers have spotted a 'dead' galaxy when the universe was just 700 million years old, the oldest such galaxy ever observed.

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Open any astronomy textbook to the section on white dwarf stars and you'll likely learn that they are 'dead stars' that continuously cool down over time. Astronomers are challenging this theory after discovering a population of white dwarf stars that stopped cooling for more than eight billion years.

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Space weather experts are urging regulators and space tourism innovators to work together to protect their passengers and crews from the risks of space weather radiation exposure.

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A new mathematical model has shown, with great precision, the impact that physiological and psychological parameters have on running performance and provides tips for optimized training.

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A team of astronomers has shed new light on the fascinating and complex process of planet formation. The research brings together observations of more than 80 young stars that might have planets forming around them, providing astronomers with a wealth of data and unique insights into how planets arise in different regions of our galaxy.

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It takes more than a galaxy merger to make a black hole grow and new stars form: machine learning shows cold gas is needed too to initiate rapid growth -- new research finds.

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NASA's Juno spacecraft has directly measured charged oxygen and hydrogen molecules from the atmosphere of one of Jupiter's largest moons, Europa. These observations provide key constraints on the potential oxygenation of its subsurface ocean.

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Researchers have developed an artificial intelligence model that can accurately identify tumors and diseases in medical images. The tool draws a map to explain each diagnosis, helping doctors follow its line of reasoning, check for accuracy, and explain the results to patients.

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Looking deeply into space and time, astronomers have studied the exceptionally luminous galaxy GN-z11, which existed when our 13.8 billion-year-old universe was only about 430 million years old.

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Astronomers can use supercomputers to simulate the formation of galaxies from the Big Bang 13.8 billion years ago to the present day. But there are a number of sources of error. An international research team has spent a hundred million computer hours over eight years trying to correct these.

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Up to a certain point, very luminous stars can have a positive effect on the formation of planets, but from that point on the radiation they emit can cause the material in protoplanetary discs to disperse.

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Using archival data from the Gemini North telescope, a team of astronomers has measured the heaviest pair of supermassive black holes ever found. The merging of two supermassive black holes is a phenomenon that has long been predicted, though never observed. This massive pair gives clues as to why such an event seems so unlikely in the Universe.