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