Abstract
Observations of the interstellar medium are key to deciphering the physical processes regulating star formation in galaxies. However, observational uncertainties and detection limits can bias the interpretation unless carefully modeled. Here I re-analyze star formation rates and gas masses of a representative sample of nearby galaxies with the help of multi-dimensional Bayesian modeling. Typical star forming galaxies are found to lie in a ‘star forming plane’ largely independent of their stellar mass. Their star formation activity is tightly correlated with the molecular and total gas content, while variations of the molecular-gas-to-star conversion efficiency are shown to be significantly smaller than previously reported. These data-driven findings suggest that physical processes that modify the overall galactic gas content, such as gas accretion and outflows, regulate the star formation activity in typical nearby galaxies, while a change in efficiency triggered by, e.g., galaxy mergers or gas instabilities, may boost the activity of starbursts.
Highlights
Observations of the interstellar medium are key to deciphering the physical processes regulating star formation in galaxies
A ‘representative sample’ of 1012 galaxies with stellar masses 9 ≤ lgMstar ≤ 11 selected from the extended GALEX Arecibo SDSS Survey[14]
All galaxies within a given stellar mass range are included in the analysis, i.e., there is no ad hoc selection of galaxies according to their star formation activity
Summary
Observations of the interstellar medium are key to deciphering the physical processes regulating star formation in galaxies. Typical star forming galaxies are found to lie in a ‘star forming plane’ largely independent of their stellar mass Their star formation activity is tightly correlated with the molecular and total gas content, while variations of the molecular-gas-tostar conversion efficiency are shown to be significantly smaller than previously reported. Recent observations of carbon-monoxide (CO) and 21 cm line emission make it possible to study the molecular and neutral gas content of representative samples of nearby galaxies[13,14] enabling a more comprehensive analysis of galactic star formation, the ISM composition, and the link to gas accretion. Bayesian modeling offers a way to mitigate biases arising from such detection limits and other observational limitations[18,19,20]
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