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Published July 29, 2016 | Published
Book Section - Chapter Open

Enabling science with Gaia observations of naked-eye stars

Abstract

ESA's Gaia space astrometry mission is performing an all-sky survey of stellar objects. At the beginning of the nominal mission in July 2014, an operation scheme was adopted that enabled Gaia to routinely acquire observations of all stars brighter than the original limit of G∼6, i.e. the naked-eye stars. Here, we describe the current status and extent of those observations and their on-ground processing. We present an overview of the data products generated for G<6 stars and the potential scientific applications. Finally, we discuss how the Gaia survey could be enhanced by further exploiting the techniques we developed.

Additional Information

© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE). The authors wish to thank the Gaia Science Team and Data Processing and Analysis Consortium (DPAC) for their support. We also kindly acknowledge the Gaia Data Processing Centre Spain (DPCE), Gaia Science Operations (SOC), and Mission Operations Centre (MOC) teams for their continuous support. J.S. is supported by an ESA Research Fellowship in Space Science. This work has made use of results from the ESA space mission Gaia, the data from which were processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. The Gaia mission website is: http://www.cosmos.esa.int/gaia. This research made use of the databases at the Centre de Données astronomiques de Strasbourg (http://cds.u-strasbg. fr), NASA's Astrophysics Data System Service (http://adsabs.harvard.edu/abstract_service.html), the paper repositories at arXiv, of APLpy, an open-source plotting package for Python hosted at http://aplpy.github.com, and of Astropy, a community-developed core Python package for Astronomy. The authors also made use of SCIPY, NUMPY,IPYTHON, and MATPLOTLIB.

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