To use or not to use synthetic stellar spectra in population synthesis models?
Paula R. T. Coelho, Gustavo Bruzual, Stephane Charlot

TL;DR
This study compares the impact of using empirical versus synthetic stellar spectral libraries in population synthesis models, finding that spectral coverage affects color predictions more than library type, while galaxy age estimates remain stable.
Contribution
It provides a systematic analysis of how the choice between empirical and synthetic stellar libraries influences population synthesis model predictions.
Findings
Colors are more affected by spectral coverage than library type.
Galaxy ages are robust against library choice.
Metallicities are underestimated with limited coverage or synthetic libraries.
Abstract
Stellar population synthesis (SPS) models are invaluable to study star clusters and galaxies. They provide means to extract stellar masses, stellar ages, star formation histories, chemical enrichment and dust content of galaxies from their integrated spectral energy distributions, colours or spectra. As most models, they contain uncertainties which can hamper our ability to model and interpret observed spectra. This work aims at studying a specific source of model uncertainty: the choice of an empirical vs. a synthetic stellar spectral library. Empirical libraries suffer from limited coverage of parameter space, while synthetic libraries suffer from modelling inaccuracies. Given our current inability to have both ideal stellar-parameter coverage with ideal stellar spectra, what should one favour: better coverage of the parameters (synthetic library) or better spectra on a star-by-star…
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