Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics
Scientific paper
2011-09-13
Astronomy and Astrophysics
Astrophysics
Cosmology and Extragalactic Astrophysics
15 pages, 11 Figures. Accepted for publication in ApJ
Scientific paper
We consider the effects of non-constant star formation histories (SFHs) on Halpha and GALEX far ultra-violet (FUV) star formation rate (SFR) indicators. Under the assumption of a fully populated Chabrier IMF, we compare the distribution of Halpha-to-FUV flux ratios from ~ 1500 simple, periodic model SFHs with observations of 185 galaxies from the Spitzer Local Volume Legacy survey. We find a set of SFH models that are well matched to the data, such that more massive galaxies are best characterized by nearly constant SFHs, while low mass systems experience bursts amplitudes of ~ 30 (i.e., an increase in the SFR by a factor of 30 over the SFR during the inter-burst period), burst durations of tens of Myr, and periods of ~ 250 Myr; these SFHs are broadly consistent with the increased stochastic star formation expected in systems with lower SFRs. We analyze the predicted temporal evolution of galaxy stellar mass, R-band surface brightness, Halpha-derived SFR, and blue luminosity, and find that they provide a reasonable match to observed flux distributions. We find that our model SFHs are generally able to reproduce both the observed systematic decline and increased scatter in Halpha-to-FUV ratios toward low mass systems, without invoking other physical mechanisms. We also compare our predictions with those from the Integrated Galactic IMF theory with a constant SFR. We find that while both predict a systematic decline in the observed ratios, only the time variable SFH models are capable of producing the observed population of low mass galaxies ($M_{*}$ < 10$^{7}$ Msun) with normal Halpha-to-FUV ratios. These results demonstrate that a variable IMF alone has difficulty explaining the observed scatter in the Halpha-to-FUV ratios. We conclude by considering the limitations of the model SFHs, and discuss the use of additional empirical constraints to improve future SFH modeling efforts.
Bothwell Matthew
Calzetti Daniela
Dalcanton Julianne J.
Dale Daniel A.
Johnson Benjamin D.
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