Affiliation:
1. Universidade de São Paulo, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Rua do Matão 1226, 05508-090 São Paulo, Brazil
2. Instituto de Radioastronomía y Astrofísica, UNAM, Campus Morelia, Michoacan, México C.P. 58089, México
3. Sorbonne Université, CNRS, UMR7095, Institut d’Astrophysique de Paris, F-75014 Paris, France
Abstract
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 that 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 versus 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 basis (empirical library)? To study this question, we build a synthetic stellar library mimicking the coverage of an empirical library, and SPS models with different choices of stellar library tailored to these investigations. Through the comparison of model predictions and the spectral fitting of a sample of nearby galaxies, we learned that predicted colours are more affected by the coverage effect than the choice of a synthetic versus empirical library; the effects on predicted spectral indices are multiple and defy simple conclusions; derived galaxy ages are virtually unaffected by the choice of the library, but are underestimated when SPS models with limited parameter coverage are used; metallicities are robust against limited HRD coverage, but are underestimated when using synthetic libraries.
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de São Paulo
National Autonomous University of Mexico
Consejo Nacional de Ciencia y Tecnología
Alfred P. Sloan Foundation
National Science Foundation
U.S. Department of Energy
National Aeronautics and Space Administration
Max Planck Society
Higher Education Funding Council for England
University of Basel
University of Cambridge
Case Western Reserve University
University of Chicago
Drexel University
Institute for Advanced Study
Johns Hopkins University
Chinese Academy of Sciences
Los Alamos National Laboratory
New Mexico State University
Ohio State University
University of Pittsburgh
University of Portsmouth
Princeton University
United States Naval Observatory
University of Washington
Publisher
Oxford University Press (OUP)
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
25 articles.
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