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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–Radial Velocity Spectrometer (RVS) data to inform galactic archeology pursuits. We fit a quadratic model of four primary sources of variability, described by labels of T_eff, log g, [Fe/H], and [α/Fe], to the normalized flux of 10,802 red-clump stars from the Gaia-RVS-like Abundances and Radial velocity Galactic Origins Survey (ARGOS). 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 Radial Velocity Experiment survey with models of T_eff, log g, [Fe/H], and [Mg/Fe]. We find that we can nearly entirely predict these abundances. Using high-precision Apache Point Observatory Galactic Evolution Experiment 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 an approximate signal-to-noise ratio <200 per pixel, in Gaia-RVS spectra.