Deriving stellar parameters from GALANTE photometry: bias and precision

Abstract

In this paper, we analyse how to extract the physical properties from the GALANTE photometry of a stellar sample. We propose a direct comparison between the observational colours (photometric bands normalized to the 515 nm central wavelength) and the synthetic colours derived from different stellar libraries. We use the reduced χ2 as the figure of merit for selecting the best fitting between both colour sets. The synthetic colours of the Next Generation Spectral Library (NGSL) provide a valuable sample for testing the uncertainty and precision of the stellar parameters derived from observational data. Reddening, as an extrinsic stellar physical parameter becomes a crucial variable for accounting for the errors and bias in the derived estimates: the higher the reddenings, the larger the errors and uncertainties in the derived parameters. NGSL colours also enable us to compare different theoretical stellar libraries for the same set of physical parameters, where we see how different catalogues of models can provide very different solutions in a, sometimes, non-linear way. This peculiar behaviour makes us to be cautious with the derived physical parameters obtained from GALANTE photometry without previous detailed knowledge of the theoretical libraries used to this end. In addition, we carry out the experiment of deriving physical stellar parameters from some theoretical libraries, using some other libraries as observational data. In particular, we use the Kurucz and Coelho libraries, as input observational data, to derive stellar parameters from Coelho + TLUSTY and Kurucz + TLUSTY stellar libraries, respectively, for different photometric errors and colour excesses.© 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society ; We thank the Centro de Estudios de F´ısica del Cosmos de Aragon´ (CEFCA) team in Teruel and Javalambre for supporting us in this project, giving us the opportunity to use non-J-PLUS useful nights to develop the GALANTE survey. We also want to recognize the work of the NGSL team (Gregg et al. 2006; Heap & Lindler 2016) whose observational catalogue has been of great help for our work. This research made use of PYTHON (http://www.python.org); NUMPY (van der Walt, Colbert & Varoquaux 2011); SCIPY (Jones et al. 2001); and MATPLOTLIB (Hunter 2007), a suite of open-source PYTHON modules that provides a framework for creating scientific plots. We also acknowledge the use of STILTS and TOPCAT tools (Taylor 2005). AL-G, EJA, and JMA acknowledge support from the Spanish Government Ministerio de Ciencia, Innovacion y Universidades ´ though grants AYA2013-40 611-P and AYA2016-75 931-C2-1/2-P. AL-G and EJA also acknowledge support from the State Agency for Research of the Spanish MCIU through the 'Center of Excellence Severo Ochoa' award for the Instituto de Astrof´ısica de Andaluc´ıa (SEV-2017-0709). ; Peer reviewed