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Photometric redshift estimation is a technique to guess the redshift of an extragalactic object (galaxy or quasar) based on its broadband magnitudes, when no spectroscopy is available. Similar techniques can be used to estimate other important physical properties of galaxies such as the start formation rate or total stellar mass.
Deep learning techniques find applications throughout all fields of quantitative science where sufficient data and training samples are available. Astronomy provides a series of problems that are ideal for deep learning, including imaging and spectroscopy.
Distributed and scalable databases and query execution, Spatial techniques for SQL databases, Virtual Observatory, noSQL solutions for distributed in-memory databases.
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