Measuring chemical likeness of stars with RSCA

TL;DR

RSCA is a novel data-driven method that maps stellar spectra to a representation optimizing chemical similarity detection, outperforming traditional abundance-based methods in identifying stellar siblings.

Contribution

The paper introduces RSCA, a new spectral analysis technique that enhances chemical similarity measurement by reducing non-chemical systematic effects, validated on APOGEE data.

Findings

RSCA effectively identifies known stellar siblings from spectra.

Almost all spectral information used by RSCA reduces to two key chemical parameters.

Using spectra with RSCA improves chemical tagging over traditional abundance measurements.

Abstract

Identification of chemically similar stars using elemental abundances is core to many pursuits within Galactic archaeology. However, measuring the chemical likeness of stars using abundances directly is limited by systematic imprints of imperfect synthetic spectra in abundance derivation. We present a novel data-driven model that is capable of identifying chemically similar stars from spectra alone. We call this Relevant Scaled Component Analysis (RSCA). RSCA finds a mapping from stellar spectra to a representation that optimizes recovery of known open clusters. By design, RSCA amplifies factors of chemical abundance variation and minimizes those of non-chemical parameters, such as instrument systematics. The resultant representation of stellar spectra can therefore be used for precise measurements of chemical similarity between stars. We validate RSCA using 185 cluster stars in 22 open clusters in the APOGEE survey. We quantify our performance in measuring chemical similarity using a reference set of 151,145 field stars. We find that our representation identifies known stellar siblings more effectively than stellar abundance measurements. Using RSCA, 1.8% of pairs of field stars are as similar as birth siblings, compared to 2.3% when using stellar abundance labels. We find that almost all of the information within spectra leveraged by RSCA fits into a two-dimensional basis, which we link to [Fe/H] and alpha-element abundances. We conclude that chemical tagging of stars to their birth clusters remains prohibitive. However, using the spectra has noticeable gain, and our approach is poised to benefit from larger datasets and improved algorithm designs.