How Well Can We Measure the Stellar Mass of a Galaxy: The Impact of the Assumed Star Formation History Model in SED Fitting. (arXiv:2006.03599v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Lower_S/0/1/0/all/0/1">Sidney Lower</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Narayanan_D/0/1/0/all/0/1">Desika Narayanan</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Leja_J/0/1/0/all/0/1">Joel Leja</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Johnson_B/0/1/0/all/0/1">Benjamin D. Johnson</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Conroy_C/0/1/0/all/0/1">Charlie Conroy</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Dave_R/0/1/0/all/0/1">Romeel Davé</a>
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 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 star
formation history (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 under-reported uncertainties on results. We demonstrate that
flexible nonparametric star formation histories outperform traditional
parametric forms in capturing variations in galaxy star formation histories,
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 of just under 0.05 dex for the nonparametric model. Similarly, using
nonparametric star formation histories in SED fitting result in increased
accuracy in recovered galaxy star formation rates (SFRs) and stellar ages.
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 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 star
formation history (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 under-reported uncertainties on results. We demonstrate that
flexible nonparametric star formation histories outperform traditional
parametric forms in capturing variations in galaxy star formation histories,
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 of just under 0.05 dex for the nonparametric model. Similarly, using
nonparametric star formation histories in SED fitting result in increased
accuracy in recovered galaxy star formation rates (SFRs) and stellar ages.
http://arxiv.org/icons/sfx.gif
