Gaia Data Release 3: Analysis of RVS spectra using the General Stellar Parametriser from spectroscopy
A. Recio-Blanco, P. de Laverny, P. A. Palicio, G. Kordopatis, M. A., \'Alvarez, M. Schultheis, G. Contursi, H. Zhao, G. Torralba Elipe, C., Ordenovic, M. Manteiga, C. Dafonte, I. Oreshina-Slezak, A. Bijaoui, Y., Fremat, G. Seabroke, F. Pailler, E. Spitoni, E. Poggio

TL;DR
Gaia DR3's GSP-spec module provides the largest space-based catalogue of stellar chemo-physical parameters, enabling advanced studies of Galactic populations and stellar evolution with high homogeneity and quality.
Contribution
This work introduces the first large-scale, space-based chemo-physical stellar parameter catalogue from Gaia DR3, utilizing novel analysis workflows and quality control methods.
Findings
Largest all-sky stellar parameter catalogue from space data
Provides detailed chemical abundances for over 5.6 million stars
Demonstrates the catalogue's utility for Galactic and stellar evolution studies
Abstract
The chemo-physical parametrisation of stellar spectra is essential for understanding the nature and evolution of stars and of Galactic stellar populations. Gaia DR3 contains the parametrisation of RVS data performed by the General Stellar Parametriser-spectroscopy, module. Here we describe the parametrisation of the first 34 months of RVS observations. GSP-spec estimates the chemo-physical parameters from combined RVS spectra of single stars. The main analysis workflow described here, MatisseGauguin, is based on projection and optimisation methods and provides the stellar atmospheric parameters; the individual chemical abundances of N, Mg, Si, S, Ca, Ti, Cr, FeI, FeII, Ni, Zr, Ce and Nd; the differential equivalent width of a cyanogen line; and the parameters of a DIB feature. Another workflow, based on an artificial neural network, provides a second set of atmospheric parameters that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
