# The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques

**Authors:** 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  
**arXiv:** [2212.01915](https://arxiv.org/abs/2212.01915)  
**Date:** 2022-12-04  
**Summary page:** https://www.summarizepaper.com/en/paper/2212.01915v1/

## Key points

- Spectral energy distribution (SED) models are used to infer physical parameters from spectrophotometric data in galaxy evolution studies
- Algorithms performing SED fitting have improved with better modeling prescriptions, newer templates, and more extensive sampling in wavelength space
- This paper presents a comprehensive analysis of different SED fitting codes and their output to measure uncertainties caused by modeling assumptions
- Fourteen commonly used SED fitting codes were applied to samples from the CANDELS photometric catalogs at z~1 and z~3
- While there was agreement on the stellar mass, some discrepancies were observed in the star formation rate (SFR) and dust attenuation results among the codes
- The impact of various modeling assumptions such as star formation histories, nebular, dust, and AGN models were assessed on derived stellar masses, SFRs, and A_V values
- The difference among the codes on the SFR-stellar mass relation was also evaluated while measuring contributions to uncertainties by modeling choices for stellar mass (~0.1dex), SFR (~0.3dex), and dust attenuation (~0.3mag)
- Best practices in SED fitting are summarized using a cosmology with ΩM = 0.3, Λ = 0.7, and h = H0/100 km s−1 Mpc−1 = 0.7 throughout all magnitudes presented in AB system.
- Section 2 provides important working definitions in SED fitting while Section 3 presents three photometric datasets used for analysis.

## Summary

The study of galaxy evolution relies heavily on our ability to interpret multi-wavelength observations of galaxies in terms of their physical properties. Spectral energy distribution (SED) models are used to infer physical parameters from spectrophotometric data, and recent years have seen a significant increase in the volume of high-quality data thanks to wide and deep multi-waveband galaxy surveys. Alongside this increase in data, algorithms performing SED fitting have also improved, with better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. This paper presents a comprehensive analysis of different SED fitting codes and their output with the aim of measuring the uncertainties caused by modeling assumptions. Fourteen commonly used SED fitting codes were applied to samples from the CANDELS photometric catalogs at z~1 and z~3. While there was agreement on the stellar mass, some discrepancies were observed in the star formation rate (SFR) and dust attenuation results. To explore these differences and biases among the codes, the impact of various modeling assumptions such as star formation histories, nebular, dust, and AGN models were assessed on derived stellar masses, SFRs, and A_V values. The difference among the codes on the SFR-stellar mass relation was also evaluated while measuring contributions to uncertainties by modeling choices for stellar mass (~0.1dex), SFR (~0.3dex), and dust attenuation (~0.3mag). The paper also provides resources summarizing best practices in SED fitting while using a cosmology with ΩM = 0.3, Λ = 0.7, and h = H0/100 km s−1 Mpc−1 = 0.7 throughout all magnitudes presented in AB system. In Section 2 important working definitions in SED fitting are provided while Section 3 presents three photometric datasets used for analysis.