Kavli Affiliate: Yingjie Peng
| First 5 Authors: Zeyu Gao, Yingjie Peng, Kai Wang, Luis C. Ho, Alvio Renzini
| Summary:
The spectral energy distribution (SED) of galaxies is essential for deriving
fundamental properties like stellar mass and star formation history (SFH).
However, conventional methods, including both parametric and non-parametric
approaches, often fail to accurately recover the observed cosmic star formation
rate (SFR) density due to oversimplified or unrealistic assumptions about SFH
and their inability to account for the complex SFH variations across different
galaxy populations. To address this issue, we introduce a novel approach that
improves galaxy broad-band SED analysis by incorporating physical priors
derived from hydrodynamical simulations. Tests using IllustrisTNG simulations
demonstrate that our method can reliably determine galaxy physical properties
from broad-band photometry, including stellar mass within 0.05 dex, current SFR
within 0.3 dex, and fractional stellar formation time within 0.2 dex, with a
negligible fraction of catastrophic failures. When applied to the SDSS main
photometric galaxy sample with spectroscopic redshift, our estimates of stellar
mass and SFR are consistent with the widely-used MPA-JHU and GSWLC catalogs.
Notably, using the derived SFHs of individual SDSS galaxies, we estimate the
cosmic SFR density and stellar mass density with remarkable consistency to
direct observations up to $z sim 6$. This marks the first time SFHs derived
from SEDs can accurately match observations. Consequently, our method can
reliably recover observed spectral indices such as $rm D_{rm n}(4000)$ and
$rm Hdelta_{rm A}$ by synthesizing the full spectra of galaxies using the
estimated SFHs and metal enrichment histories, relying solely on broad-band
photometry as input. Furthermore, this method is extremely computationally
efficient compared to conventional approaches.
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