Abstract
GSP-Phot (Generalized Stellar Parametrizer—Photometry) is a software package in the Gaia Astrophysical parameters processing chain (Apsis) which estimates the astrophysical parameters of all stars in the Gaia catalogue. The inputs of GSP-Phot are the low-resolution spectra from the Gaia photometers as well as parallaxes, while the outputs consist of effective temperatures (T eff), extinction parameters (A 0), metallicities ([Fe/H] and surface gravities (logg). Three algorithms are developed in GSP-Phot: (a) support vector machine regression (SVR), a pattern recognition method; (b) ILIUM, a forward model based on discrete synthetic parameter grid; and (c) q-method, a Bayesian method which combines a forward model with parallaxes and the Hertzsprung–Russell diagram (HRD) as a prior. The performance of the three algorithms is investigated for a range of spectral types with arbitrary apparent magnitudes.
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Notes
- 1.
Extinction law is defined as \({A}_{\lambda } = {A}_{0}(a(\lambda ) + b(\lambda )/{R}_{0})\) [6].
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Acknowledgements
The authors thank Kester Smith and Paraskevi Tsalmantza for their assistance and comments on GSP-Phot and the DPAC CU8 community for their contribution to the development, integration and testing of GSP-Phot and the simulation data generation. This work makes use of Gaia simulated observations, and we thank the members of the Gaia DPAC Coordination Unit 2 for their work. The generation of the simulation data was done on the MareNostrum supercomputer at Barcelona Supercomputing Center—Centro Nacional de Supercomputación (The Spanish National Supercomputing Center).
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Liu, C., Bailer-Jones, C.A.L. (2012). Generalized Stellar Parametrizer with Gaia Photometry Data. In: Sarro, L., Eyer, L., O'Mullane, W., De Ridder, J. (eds) Astrostatistics and Data Mining. Springer Series in Astrostatistics, vol 2. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3323-1_15
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DOI: https://doi.org/10.1007/978-1-4614-3323-1_15
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