The Astrophysical Variance in Gaia-RVS Spectra

TL;DR

This study investigates the chemical abundance information in Gaia-RVS spectra, demonstrating that a four-label model captures most variance and that elemental abundances can be predicted with high accuracy, informing galactic archaeology.

Contribution

The paper shows that a four-label model effectively describes Gaia-RVS spectral variance and that elemental abundances can be accurately inferred from these spectra.

Findings

Models capture 85% of flux variability across spectra.

Residual variance concentrated in Ca-triplet features.

Abundances can be predicted with <0.03 dex uncertainty.

Abstract

Large surveys are providing a diversity of spectroscopic observations with Gaia alone set to deliver millions of Ca-triplet-region spectra across the Galaxy. We aim to understand the dimensionality of the chemical abundance information in the Gaia-RVS data to inform galactic archaeology pursuits. We fit a quadratic model of four primary sources of variability, described by labels of $T_{\rm eff}$, $\log g$, [Fe/H], and [$\alpha$/Fe], to the normalized flux of 10,802 red-clump stars from the Gaia-RVS-like ARGOS survey. We examine the residuals between ARGOS spectra and the models and find that the models capture the flux variability across $85\%$ of the wavelength region. The remaining residual variance is concentrated to the Ca-triplet features, at an amplitude up to $12\%$ of the normalized flux. We use principal component analysis on the residuals and find orthogonal correlations in the Ca-triplet core and wings. This variability, not captured by our model, presumably marks departures from the completeness of the 1D-LTE label description. To test the indication of low-dimensionality, we turn to abundance-space to infer how well we can predict measured [Si/H], [O/H], [Ca/H], [Ni/H], and [Al/H] abundances from the Gaia-RVS-like RAVE survey with models of $T_{\rm eff}$, $\log g$, [Fe/H], and [Mg/Fe]. We find that we can near-entirely predict these abundances. Using high-precision APOGEE abundances, we determine that a measurement uncertainty of $<$ 0.03 dex is required to capture additional information from these elements. This indicates that a four-label model sufficiently describes chemical abundance variance for $\approx$ S/N $<$ 200 per pixel, in Gaia-RVS spectra.