Accurate estimates of fundamental physical properties of galaxies, such as star formation rates (SFRs) or stellar masses, are essential for testing and constraining models of galaxy formation and evolution. Spectral energy distribution (SED) modeling has become the standard method for deriving these quantities. However, the influence of the underlying stellar population synthesis (SPS) models on the inferred parameters remains poorly quantified. This work investigates how the choice of SPS models affects the estimation of SFRs and stellar masses derived from SED modeling. Four widely used SPS models were applied to a sample of 17,230 galaxies with spectroscopic redshifts, selected from recently published Hubble Space Telescope and James Webb Space Telescope photometric catalogs. SEDs were modeled using the Code for Investigating GALaxy Emission. The analysis was performed in two steps: (i) estimating galaxy properties with each SPS model, and (ii) employing synthetic catalogs to assess the relative impact of model choice on the recovered parameters. Systematic differences are found among the models, with stellar mass estimates varying by up to sim0.6 dex and SFRs by up to sim0.4 dex between certain model pairs. The choice of stellar population model introduces significant systematic uncertainties in derived galaxy properties. This dependence should be accounted for when interpreting SED-based measurements and comparing results across different studies of galaxy evolution.
Stoyanova et al. (Wed,) studied this question.