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تسجيل مستخدم جديدO/IR Polarimetry for the 2010 Decade (CGT): Science at the Edge, Sharp Tools for All
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Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the field of extragalactic astrophysics. Community-based White Paper to Astro2010 in response to the call for such papers.
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Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the field of Galactic science. Community-based White Paper to Astro2010 in response to the call for such papers.
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Gammapy is a Python package for high-level gamma-ray data analysis built on Numpy, Scipy and Astropy. It enables us to analyze gamma-ray data and to create sky images, spectra and lightcurves, from event lists and instrument response information, and
to determine the position, morphology and spectra of gamma-ray sources. So far Gammapy has mostly been used to analyze data from H.E.S.S. and Fermi-LAT, and is now being used for the simulation and analysis of observations from the Cherenkov Telescope Array (CTA). We have proposed Gammapy as a prototype for the CTA science tools. This contribution gives an overview of the Gammapy package and project and shows an analysis application example with simulated CTA data.
Over the past decade, research in resolved stellar populations has made great strides in exploring the nature of dark matter, in unraveling the star formation, chemical enrichment, and dynamical histories of the Milky Way and nearby galaxies, and in
probing fundamental physics from general relativity to the structure of stars. Large surveys have been particularly important to the biggest of these discoveries. In the coming decade, current and planned surveys will push these research areas still further through a large variety of discovery spaces, giving us unprecedented views into the low surface brightness Universe, the high surface brightness Universe, the 3D motions of stars, the time domain, and the chemical abundances of stellar populations. These discovery spaces will be opened by a diverse range of facilities, including the continuing Gaia mission, imaging machines like LSST and WFIRST, massively multiplexed spectroscopic platforms like DESI, Subaru-PFS, and MSE, and telescopes with high sensitivity and spatial resolution like JWST, the ELTs, and LUVOIR. We do not know which of these facilities will prove most critical for resolved stellar populations research in the next decade. We can predict, however, that their chance of success will be maximized by granting use of the data to broad communities, that many scientific discoveries will draw on a combination of data from them, and that advances in computing will enable increasingly sophisticated analyses of the large and complex datasets that they will produce. We recommend that Astro2020 1) acknowledge the critical role that data archives will play for stellar populations and other science in the next decade, 2) recognize the opportunity that advances in computing will bring for survey data analysis, and 3) consider investments in Science Platform technology to bring these opportunities to fruition.
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