How Well Can We Measure the Stellar Mass of a Galaxy: The Impact of the Assumed Star Formation History Model in SED Fitting
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How Well Can We Measure the Stellar Mass of a Galaxy : The Impact of the Assumed Star Formation History Model in SED Fitting. / Lower, Sidney; Narayanan, Desika; Leja, Joel; Johnson, Benjamin D.; Conroy, Charlie; Dave, Romeel.
In: Astrophysical Journal, Vol. 904, No. 1, 33, 19.11.2020.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - How Well Can We Measure the Stellar Mass of a Galaxy
T2 - The Impact of the Assumed Star Formation History Model in SED Fitting
AU - Lower, Sidney
AU - Narayanan, Desika
AU - Leja, Joel
AU - Johnson, Benjamin D.
AU - Conroy, Charlie
AU - Dave, Romeel
PY - 2020/11/19
Y1 - 2020/11/19
N2 - The primary method for inferring the stellar mass (M-*) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history (SFH) and dust attenuation law that can severely impact the accuracy of derived physical properties from SED modeling. Here we examine the effect that the assumed SFH has on the stellar properties inferred from SED fitting by ground-truthing them against mock observations of high-resolution cosmological hydrodynamic galaxy formation simulations. Classically, SFHs are modeled with simplified parameterized functional forms, but these forms are unlikely to capture the true diversity of galaxy SFHs and may impose systematic biases with underreported uncertainties on results. We demonstrate that flexible nonparametric SFHs outperform traditional parametric forms in capturing variations in galaxy SFHs and, as a result, lead to significantly improved stellar masses in SED fitting. We find a decrease in the average bias of 0.4 dex with a delayed-tau model to a bias under 0.1 dex for the nonparametric model, though this is heavily dependent on the choice of prior for the nonparametric model. Similarly, using nonparametric SFHs in SED fitting results in increased accuracy in recovered galaxy star formation rates and stellar ages.
AB - The primary method for inferring the stellar mass (M-*) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history (SFH) and dust attenuation law that can severely impact the accuracy of derived physical properties from SED modeling. Here we examine the effect that the assumed SFH has on the stellar properties inferred from SED fitting by ground-truthing them against mock observations of high-resolution cosmological hydrodynamic galaxy formation simulations. Classically, SFHs are modeled with simplified parameterized functional forms, but these forms are unlikely to capture the true diversity of galaxy SFHs and may impose systematic biases with underreported uncertainties on results. We demonstrate that flexible nonparametric SFHs outperform traditional parametric forms in capturing variations in galaxy SFHs and, as a result, lead to significantly improved stellar masses in SED fitting. We find a decrease in the average bias of 0.4 dex with a delayed-tau model to a bias under 0.1 dex for the nonparametric model, though this is heavily dependent on the choice of prior for the nonparametric model. Similarly, using nonparametric SFHs in SED fitting results in increased accuracy in recovered galaxy star formation rates and stellar ages.
KW - Astronomy data modeling
KW - Hydrodynamical simulations
KW - Stellar masses
KW - Galaxy properties
KW - Spectral energy distribution
KW - Radiative transfer simulations
KW - PHYSICAL-PROPERTIES
KW - INFRARED-EMISSION
KW - INTERSTELLAR DUST
KW - SPECTRA
KW - GAS
KW - UNCERTAINTIES
KW - EVOLUTION
KW - DISTRIBUTIONS
KW - PROPAGATION
KW - POPULATIONS
U2 - 10.3847/1538-4357/abbfa7
DO - 10.3847/1538-4357/abbfa7
M3 - Journal article
VL - 904
JO - Astrophysical Journal
JF - Astrophysical Journal
SN - 0004-637X
IS - 1
M1 - 33
ER -
ID: 252832743