Closing the stellar labels gap: Stellar label independent evidence for [$alpha$/M] information in $textit{Gaia}$ BP/RP spectra
Alexander Laroche, Joshua S. Speagle
arXiv:2404.07316v1 Announce Type: new
Abstract: Data-driven models for stellar spectra which depend on stellar labels suffer from label systematics which decrease model performance: the “stellar labels gap”. To close the stellar labels gap, we present a stellar label independent model for $textit{Gaia}$ BP/RP (XP) spectra. We develop a novel implementation of a variational auto-encoder; a $textit{scatter}$ VAE, which learns to generate an XP spectrum and intrinsic scatter without relying on stellar labels. We demonstrate that our model achieves competitive XP spectra reconstructions in comparison to stellar label dependent models. We find that our model learns stellar properties directly from the data itself. We then apply our model to XP/APOGEE giant stars to study the [$alpha$/M] information in $textit{Gaia}$ XP. We provide strong evidence that the XP spectra contain meaningful [$alpha$/M] information by demonstrating that our model learns the $alpha$-bimodality $textit{without relying on stellar label correlations}$, for stars with $T_{rm eff} arXiv:2404.07316v1 Announce Type: new
Abstract: Data-driven models for stellar spectra which depend on stellar labels suffer from label systematics which decrease model performance: the “stellar labels gap”. To close the stellar labels gap, we present a stellar label independent model for $textit{Gaia}$ BP/RP (XP) spectra. We develop a novel implementation of a variational auto-encoder; a $textit{scatter}$ VAE, which learns to generate an XP spectrum and intrinsic scatter without relying on stellar labels. We demonstrate that our model achieves competitive XP spectra reconstructions in comparison to stellar label dependent models. We find that our model learns stellar properties directly from the data itself. We then apply our model to XP/APOGEE giant stars to study the [$alpha$/M] information in $textit{Gaia}$ XP. We provide strong evidence that the XP spectra contain meaningful [$alpha$/M] information by demonstrating that our model learns the $alpha$-bimodality $textit{without relying on stellar label correlations}$, for stars with $T_{rm eff}