  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.
