Photo-Met: a non-parametric method for estimating stellar metallicity from photometric observations

TL;DR

This paper introduces a non-parametric photometric method to estimate stellar metallicity efficiently from photometric data, enabling larger sample analysis with reliable error estimates, surpassing some limitations of spectroscopic methods.

Contribution

The paper presents a novel non-parametric approach for stellar metallicity estimation from photometry, extending applicability across stellar types and providing error estimates.

Findings

Performs well for brighter stars and higher metallicities

Enables metallicity estimation for larger stellar samples

Provides reliable error estimates for predictions

Abstract

Getting spectra at good signal-to-noise ratios takes orders of magnitudes more time than photometric observations. Building on the technique developed for photometric redshift estimation of galaxies, we develop and demonstrate a non-parametric photometric method for estimating the chemical composition of galactic stars. We investigate the efficiency of our method using spectroscopically determined stellar metallicities from SDSS DR7. The technique is generic in the sense that it is not restricted to certain stellar types or stellar parameter ranges and makes it possible to obtain metallicities and error estimates for a much larger sample than spectroscopic surveys would allow. We find that our method performs well, especially for brighter stars and higher metallicities and, in contrast to many other techniques, we are able to reliably estimate the error of the predicted metallicities.