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Dark matter is an invisible substance that makes up more than eighty percent of the matter content of the universe. We know of its existence due to its gravitational influence, being a key ingredient to understand everything from the large-scale evolution of the universe to the formation of galaxies like the Milky Way, of which we are part of . However, very little is known about its nature, which constitutes one of the greatest unsolved problems in contemporary physics. The fuzzy dark matter model has recently been studied as a promising candidate. In this model , it is postulated that dark
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Stellar ages are key to several fields of astrophysics such as exoplanet research, galactic-archeology, and of course stellar physics. Obtaining the ages of stars is however not straightforward and requires stellar modeling. The most widely used technique only requires stellar colors or temperature and surface gravity, but the uncertainties are quite large. This technique is most efficient for stars belonging to clusters, as they were born from the same molecular cloud and share the same ages. In the last decades, based on the study of stellar acoustic waves, asteroseismology became the most
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The amount and complexity of data delivered by modern galaxy surveys has been steadily increasing over the past years. New facilities will soon provide imaging and spectra of hundreds of millions of galaxies. Extracting coherent scientific information from these large and multi-modal data sets remains an open issue for the community and data-driven approaches such as deep learning have rapidly emerged as a potentially powerful solution to some long lasting challenges. This enthusiasm is reflected in an unprecedented exponential growth of publications using neural networks, which have gone
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