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NishMath - #cosmology
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Siôn Geschwindt@The Next Web
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The European Space Agency's Euclid space telescope has released its first major data set, offering new insights into dark matter and the universe's expansion. This initial data comprises one week's worth of deep field images from three points in space, representing just a small fraction (0.4%) of the area Euclid is designed to capture. Despite this limited scope, Euclid has already identified 26 million galaxies, each potentially containing millions of stars and billions of planets.
Euclid's data release includes mosaics covering 63 square degrees of the sky, revealing galaxy clusters, active galactic nuclei, and transient phenomena. Significantly, it provides the first classification survey of over 380,000 galaxies and identifies 500 gravitational lens candidates. One rare phenomenon captured in the new batch of data is double gravitational lensing, where light from two distant galaxies passes through the same galaxy, causing a double lensing effect. These early observations promise significant advancements in our understanding of cosmology and astrophysics, particularly regarding dark matter and dark energy.
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Charlie Wood@Quanta Magazine
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Recent data from the Dark Energy Spectroscopic Instrument (DESI) suggests that dark energy, the mysterious force driving the accelerating expansion of the universe, may be weakening over time. This challenges the standard model of cosmology, which assumes dark energy has a constant density and pressure. Researchers, including Seshadri Nadathur from the DESI collaboration, have analyzed significantly more data than in previous studies, strengthening the conclusion that the engine driving cosmic expansion might be sputtering.
The findings are also supported by evidence from the Dark Energy Survey (DES), which also observed a vast expanse of the cosmos and reported indications of varying dark energy. Miguel Zumalacárregui notes that Euclid's capabilities could better determine the universe's expansion rate through gravitational-wave observations. If confirmed, this would rewrite our understanding of the universe's fate, potentially leading to alternative scenarios beyond the current model of endless expansion and eventual cosmic emptiness.
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@astro.theoj.org
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Computational simulations are advancing rapidly across various scientific domains, leveraging sophisticated techniques in applied mathematics. A new project explores implementing electromagnetic wave simulations using array languages like APL, J, or K, focusing on the Finite-Difference Time-Domain (FDTD) method. This method discretizes space into a grid, using magnetic and electric field vectors to simulate wave behavior through array arithmetic.
This method is also being applied to cosmological simulations, as evidenced by a recent publication in The Open Journal of Astrophysics titled "AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations" by Xiaowen Zhang, Patrick Lachance, and others. The study develops an emulator that uses deep learning to enhance low-resolution simulations with statistically correct details, producing accurate simulations and mock observations for large galaxy surveys. Additionally, research is being conducted on disaggregating log replication protocols for state machine replication, improving the efficiency and reliability of distributed data systems, as highlighted in Jack Vanlightly's analysis.
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