The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques
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The Art of Measuring Physical Parameters in Galaxies : A Critical Assessment of Spectral Energy Distribution Fitting Techniques. / Pacifici, Camilla; Iyer, Kartheik G.; Mobasher, Bahram; da Cunha, Elisabete; Acquaviva, Viviana; Burgarella, Denis; Rivera, Gabriela Calistro; Carnall, Adam C.; Chang, Yu-Yen; Chartab, Nima; Cooke, Kevin C.; Fairhurst, Ciaran; Kartaltepe, Jeyhan; Leja, Joel; Malek, Katarzyna; Salmon, Brett; Torelli, Marianna; Vidal-Garcia, Alba; Boquien, Mederic; Brammer, Gabriel G.; Brown, Michael J. I.; Capak, Peter L.; Chevallard, Jacopo; Circosta, Chiara; Croton, Darren; Davidzon, Iary; Dickinson, Mark; Duncan, Kenneth J.; Faber, Sandra M.; Ferguson, Harry C.; Fontana, Adriano; Guo, Yicheng; Haeussler, Boris; Hemmati, Shoubaneh; Jafariyazani, Marziye; Kassin, Susan A.; Larson, Rebecca L.; Lee, Bomee; Mantha, Kameswara Bharadwaj; Marchi, Francesca; Nayyeri, Hooshang; Newman, Jeffrey A.; Pandya, Viraj; Pforr, Janine; Reddy, Naveen; Sanders, Ryan; Shah, Ekta; Shahidi, Abtin; Stevans, Matthew L.; Triani, Dian Puspita; Tyler, Krystal D.; Vanderhoof, Brittany N.; de la Vega, Alexander; Wang, Weichen; Weston, Madalyn E.
In: Astrophysical Journal, Vol. 944, No. 2, 141, 01.02.2023.Research output: Contribution to journal › Journal article › Research › peer-review
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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 - Rivera, Gabriela Calistro
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 - Malek, Katarzyna
AU - Salmon, Brett
AU - Torelli, Marianna
AU - Vidal-Garcia, Alba
AU - Boquien, Mederic
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.
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 similar to 1 and z similar to 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 (similar to 0.1 dex), SFR (similar to 0.3 dex), and dust attenuation (similar to 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 similar to 1 and z similar to 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 (similar to 0.1 dex), SFR (similar to 0.3 dex), and dust attenuation (similar to 0.3 mag). Finally, we present some resources summarizing best practices in SED fitting.
KW - STAR-FORMING GALAXIES
KW - STELLAR POPULATION SYNTHESIS
KW - ACTIVE GALACTIC NUCLEI
KW - MASS-METALLICITY RELATION
KW - DUST ATTENUATION CURVES
KW - FAR-INFRARED SURVEY
KW - PHOTOMETRIC REDSHIFTS
KW - MAIN-SEQUENCE
KW - FORMATION HISTORIES
KW - LEGACY SURVEY
U2 - 10.3847/1538-4357/acacff
DO - 10.3847/1538-4357/acacff
M3 - Journal article
VL - 944
JO - Astrophysical Journal
JF - Astrophysical Journal
SN - 0004-637X
IS - 2
M1 - 141
ER -
ID: 341013852