分类： 天文学 >> 天文学 提交时间： 2023-02-19
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
摘要： 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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