In August 2006 a new planetary transit was discovered from data from the TrES network. The discovery was confirmed using radial velocity curves obtained with the Keck and characterised with light curves in different filters obtained using two telescopes at the Observatorio del Teide: "IAC80" and "TELAST" (the first result of scientific interest obtained from the latter). The planet discovered, TrES-2, is more massive and somewhat larger than its quasi-homonym TrES-1 (the first exoplanet discovered using the transit method), and follows the expected patterns for this type of object. Its main importance is that it is the first object discovered in the area of observation of the future Kepler satellite, which will be able to track it in a degree of detail never before achieved.
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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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Accretion disks around compact objects are expected to enter an unstable phase at high luminosity. One instability may occur when the radiation pressure generated by accretion modifies the disk viscosity, resulting in the cyclic depletion and refilling of the inner disk on short timescales. Such a scenario, however, has only been quantitatively verified for a single stellar-mass black hole. Although there are hints of these cycles in a few isolated cases, their apparent absence in the variable emission of most bright accreting neutron stars and black holes has been a continuing puzzle. Here
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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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