SDSS-IV MaStar: Theoretical Atmospheric Parameters for the MaNGA Stellar Library
Lewis Hill (1), Daniel Thomas (1, 2), Claudia Maraston (1), Renbin, Yan (3), Justus Neumann (1), Andrew Lundgren (1), Daniel Lazarz (3), Yan-Ping, Chen (4), Michele Cappellari (5), Jon A. Holtzman (6), Julie Imig (6), Katia, Cunha (7, 8), Guy Stringfellow (9), Dmitry Bizyaev (10

TL;DR
This paper derives and validates stellar atmospheric parameters for the MaStar library using spectral fitting, Bayesian methods, and cross-matching with Gaia, providing a comprehensive catalog for stellar population studies.
Contribution
It introduces a new method combining spectral fitting and Bayesian analysis to determine stellar parameters for the large MaStar library, validated against standard stars and literature.
Findings
Parameters agree well with high-resolution spectroscopy
Catalog covers a wide range of stellar types
Method reliably identifies outliers and uncertainties
Abstract
We calculate the fundamental stellar parameters effective temperature, surface gravity and iron abundance - T, log g, [Fe/H] - for the final release of the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar), containing 59,266 per-visit-spectra for 24,290 unique stars at intermediate resolution () and high S/N (median = 96). We fit theoretical spectra from model atmospheres by both MARCS and BOSZ-ATLAS9 to the observed MaStar spectra, using the full spectral fitting code pPXF. We further employ a Bayesian approach, using a Markov Chain Monte Carlo (MCMC) technique to map the parameter space and obtain uncertainties. Originally in this paper, we cross match MaStar observations with Gaia photometry, which enable us to set reliable priors and identify outliers according to stellar evolution. In parallel to the parameter determination, we calculate…
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