TY - JOUR
T1 - The Art of Measuring Physical Parameters in Galaxies
T2 - A Critical Assessment of Spectral Energy Distribution Fitting Techniques
AU - Pacifici, Camilla
AU - Iyer, Kartheik G.
AU - Mobasher, Bahram
AU - da Cunha, Elisabete
AU - Acquaviva, Viviana
AU - Burgarella, Denis
AU - Calistro Rivera, Gabriela
AU - Carnall, Adam C.
AU - Chang, Yu Yen
AU - Chartab, Nima
AU - Cooke, Kevin C.
AU - Fairhurst, Ciaran
AU - Kartaltepe, Jeyhan
AU - Leja, Joel
AU - Małek, Katarzyna
AU - Salmon, Brett
AU - Torelli, Marianna
AU - Vidal-García, Alba
AU - Boquien, Médéric
AU - Brammer, Gabriel G.
AU - Brown, Michael J.I.
AU - Capak, Peter L.
AU - Chevallard, Jacopo
AU - Circosta, Chiara
AU - Croton, Darren
AU - Davidzon, Iary
AU - Dickinson, Mark
AU - Duncan, Kenneth J.
AU - Faber, Sandra M.
AU - Ferguson, Harry C.
AU - Fontana, Adriano
AU - Guo, Yicheng
AU - Haeussler, Boris
AU - Hemmati, Shoubaneh
AU - Jafariyazani, Marziye
AU - Kassin, Susan A.
AU - Larson, Rebecca L.
AU - Lee, Bomee
AU - Mantha, Kameswara Bharadwaj
AU - Marchi, Francesca
AU - Nayyeri, Hooshang
AU - Newman, Jeffrey A.
AU - Pandya, Viraj
AU - Pforr, Janine
AU - Reddy, Naveen
AU - Sanders, Ryan
AU - Shah, Ekta
AU - Shahidi, Abtin
AU - Stevans, Matthew L.
AU - Triani, Dian Puspita
AU - Tyler, Krystal D.
AU - Vanderhoof, Brittany N.
AU - de la Vega, Alexander
AU - Wang, Weichen
AU - Weston, Madalyn E.
N1 - Publisher Copyright:
© 2023. The Author(s). Published by the American Astronomical Society.
PY - 2023/2/1
Y1 - 2023/2/1
N2 - The study of galaxy evolution hinges on our ability to interpret multiwavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models, which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to wide and deep multiwave band galaxy surveys, the volume of high-quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED-fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply 14 of the most commonly used SED-fitting codes on samples from the CANDELS photometric catalogs at z ∼ 1 and z ∼ 3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust-attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust and active galactic nucleus models) on the derived stellar masses, SFRs, and A V values. We then assess the difference among the codes on the SFR-stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (∼0.1 dex), SFR (∼0.3 dex), and dust attenuation (∼0.3 mag). Finally, we present some resources summarizing best practices in SED fitting.
AB - The study of galaxy evolution hinges on our ability to interpret multiwavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models, which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to wide and deep multiwave band galaxy surveys, the volume of high-quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED-fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply 14 of the most commonly used SED-fitting codes on samples from the CANDELS photometric catalogs at z ∼ 1 and z ∼ 3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust-attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust and active galactic nucleus models) on the derived stellar masses, SFRs, and A V values. We then assess the difference among the codes on the SFR-stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (∼0.1 dex), SFR (∼0.3 dex), and dust attenuation (∼0.3 mag). Finally, we present some resources summarizing best practices in SED fitting.
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U2 - 10.3847/1538-4357/acacff
DO - 10.3847/1538-4357/acacff
M3 - Article
AN - SCOPUS:85148867957
SN - 0004-637X
VL - 944
JO - Astrophysical Journal
JF - Astrophysical Journal
IS - 2
M1 - 141
ER -