Abstract
Abstract
Large-scale surveys will provide spectroscopy for ∼50 million resolved stars in the Milky Way and Local Group. However, these data will have a high degree of heterogeneity and most will be low-resolution (R < 10,000), posing challenges to measuring consistent and reliable stellar labels. Here, we introduce a framework for identifying and remedying these issues. By simultaneously fitting the full spectrum and Gaia photometry with the Payne, we measure ∼30 abundances for eight metal-poor red giants in M15. From degraded quality Keck/HIRES spectra, we evaluate trends with resolution and signal-to-noise ratio (S/N) and find that (i) ∼20 abundances are recovered consistently within ≲0.1 dex agreement and with ≲0.05–0.15 dex systematic uncertainties from 10,000 ≲ R ≲ 80,000; (ii) for nine elements (C, Mg, Ca, Sc, Ti, Fe, Ni, Y, and Nd), this systematic precision and accuracy extends down to R ∼ 2500; and (iii) while most elements do not exhibit strong S/N-dependent systematics, there are nonnegligible biases for four elements (C, Mg, Ca, and Dy) below S/N ∼ 10 pixel−1. We compare statistical uncertainties from Markov Chain Monte Carlo sampling to the easier-to-compute Cramér–Rao bounds and find that they agree for ∼85% of elements, indicating the latter to be a reliable and faster way to estimate uncertainties. Our analysis illustrates the great promise of low-resolution spectroscopy for stellar chemical abundance work in the low-metallicity regime, and ongoing improvements to stellar models (e.g., 3D-NLTE physics) will only further extend its viability to more stars, more elements, and higher precision and accuracy.
Funder
National Science Foundation
Space Telescope Science Institute
Department of Education and Training ∣ Australian Research Council
Publisher
American Astronomical Society
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
2 articles.
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