CoSHA: Code for Stellar Properties Heuristic Assignment-for the MaStar Stellar Library

Abstract

We introduce COSHA: a Code for Stellar properties Heuristic Assignment. In order to estimate the stellar properties, COSHA implements a Gradient Tree Boosting algorithm to label each star across the parameter space (T _eff, $\mathrm{log}g$ , [Fe/H], and [α/Fe]). We use COSHA to estimate the stellar atmospheric parameters of 22,000 unique stars in the MaNGA Stellar Library (MaStar). To quantify the reliability of our approach, we run internal tests, using both the Göttingen Stellar Library (a theoretical library) and the first data release of MaStar, and external tests, by comparing the resulting distributions in the parameter space with the APOGEE estimates of the same properties. In summary, our parameter estimates span the ranges T _eff = [2900, 12,000] K, $\mathrm{log}g=[-0.5,5.6]$ , [Fe/H] = [-3.74, 0.81], and α M = [-0.22, 1.17]. We report internal (external) uncertainties of the properties of ${\sigma }_{{T}_{\mathrm{eff}}}\sim 43(240)$ K, ${\sigma }_{\mathrm{log}g}\sim 0.2(0.4)$ , σ _[Fe/H] ~ 0.16(0.24), and σ _[α/Fe] ~ 0.09(0.08). These uncertainties are comparable to those of other methods with similar objectives. Despite the fact that COSHA is not aware of the spatial distributions of these physical properties in the Milky Way, we are able to recover the main trends known in the literature. The catalog of physical properties for MaStar can be accessed online.