Publication: RGB photometric calibration of 15 million Gaia stars
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2021-10
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Wiley
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Abstract
Although the use of RGB photometry has exploded in the last decades due to the advent of high-quality and inexpensive digital cameras equipped with Bayer-like color filter systems, there is surprisingly no catalogue of bright stars that can be used for calibration purposes. Since due to their excessive brightness, accurate enough spectrophotometric measurements of bright stars typically cannot be performed with modern large telescopes, we have employed historical 13-color medium-narrow-band photometric data, gathered with quite reliable photomultipliers, to fit the spectrum of 1346 bright stars using stellar atmosphere models. This not only constitutes a useful compilation of bright spectrophotometric standards well spread in the celestial sphere, the UCM library of spectrophotometric spectra, but allows the generation of a catalogue of reference RGB magnitudes, with typical random uncertainties ∼ 0.01 mag. For that purpose, we have defined a new set of spectral sensitivity curves, computed as the median of 28 sets of empirical sensitivity curves from the literature, that can be used to establish a standard RGB photometric system. Conversions between RGB magnitudes computed with any of these sets of empirical RGB curves and those determined with the new standard photometric system are provided. Even though particular RGB measurements from single cameras are not expected to provide extremely accurate photometric data, the repeatability and multiplicity of observations will allow access to a large amount of exploitable data in many astronomical fields, such as the detailed monitoring of light pollution and its impact on the night sky brightness, or the study of meteors, solar system bodies, variable stars, and transient objects. In addition, the RGB magnitudes presented here make the sky an accessible and free laboratory for the calibration of the cameras themselves.
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© 2021 The Authors. The authors are grateful for the exceptionally careful reading by the referee, whose constructive remarks have helped to improve the paper, making the text more precise and readable. The authors acknowledge financial support from the Spanish Programa Estatal de I+D+i Orientada a los Retos de la Sociedad under grant RTI2018-096188- B-I00, which is partly funded by the European Regional Development Fund (ERDF), S2018/NMT-4291 (TEC2SPACE-CM), and ACTION, a project funded by the European Union H2020-SwafS2018-1-824603. SB acknowledges Xunta de Galicia for financial support under grant ED431B 2020/29. The participation of ASdM was (partially) supported by the EMISSI@N project (NERC grant NE/P01156X/1). This work has been possible thanks to the extensive use of IPython and Jupyter notebooks (Pérez & Granger 2007). This research made use of Astropy,15 a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013, 2018), Numpy (Harris et al. 2020), Scipy (Virtanen et al. 2020), and Matplotlib (Hunter 2007). This research has made use of the Simbad database and the VizieR catalogue access tool, CDS, Strasbourg, France (DOI: 10.26093/cds/vizier). The original description of the VizieR service was published in A&AS 143, 23.