The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques
Creators: name: Pacifici, Camilla
name: Iyer, Kartheik G.
name: Mobasher, Bahram
name: da Cunha, Elisabete
name: Acquaviva, Viviana
name: Burgarella, Denis
name: Rivera, Gabriela Calistro
name: Carnall, Adam C.
name: Chang, Yu-Yen
name: Chartab, Nima
name: Cooke, Kevin C.
name: Fairhurst, Ciaran
name: Kartaltepe, Jeyhan
name: Leja, Joel
name: Malek, Katarzyna
name: Salmon, Brett
name: Torelli, Marianna
name: Vidal-Garcia, Alba
name: Boquien, Mederic
name: Brammer, Gabriel G.
name: Brown, Michael J. I.
name: Capak, Peter L.
name: Chevallard, Jacopo
name: Circosta, Chiara
name: Croton, Darren
name: Davidzon, Iary
name: Dickinson, Mark
name: Duncan, Kenneth J.
name: Faber, Sandra M.
name: Ferguson, Harry C.
name: Fontana, Adriano
name: Guo, Yicheng
name: Haeussler, Boris
name: Hemmati, Shoubaneh
name: Jafariyazani, Marziye
name: Kassin, Susan A.
name: Larson, Rebecca L.
name: Lee, Bomee
name: Mantha, Kameswara Bharadwaj
name: Marchi, Francesca
name: Nayyeri, Hooshang
name: Newman, Jeffrey A.
name: Pandya, Viraj
name: Pforr, Janine
name: Reddy, Naveen
name: Sanders, Ryan
name: Shah, Ekta
name: Shahidi, Abtin
name: Stevans, Matthew L.
name: Triani, Dian Puspita
name: Tyler, Krystal D.
name: Vanderhoof, Brittany N.
name: de la Vega, Alexander
name: Wang, Weichen
name: Weston, Madalyn E.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences
subject: FOS: Physical sciences

description: The study of galaxy evolution hinges on our ability to interpret multi-wavelength 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 the wide and deep multi-waveband 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 fourteen 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 AGN 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 (~0.1dex), SFR (~0.3dex), and dust attenuation (~0.3mag). Finally, we present some resources summarizing best practices in SED fitting.
description: 25 pages, 11 figures. Accepted for publication in ApJ