Abstract

Abstract We investigate star-forming scaling relations using Bayesian inference on a comprehensive data sample of low- (z < 0.1) and high-redshift (1 < z < 5) star-forming regions. This full data set spans a wide range of host galaxy stellar mass (M * ∼ 106–1011 ) and clump star formation rates (SFR ∼ 10−5 −102 yr−1). We fit the power-law relationship between the size ( ) and luminosity ( ) of the star-forming clumps using the Bayesian statistical modeling tool Stan, which makes use of Markov Chain Monte Carlo (MCMC) sampling techniques. Trends in the scaling relationship are explored for the full sample and subsets based on redshift and selection effects between samples. In our investigation, we find neither evidence of redshift evolution of the size–luminosity scaling relationship nor a difference in slope between lensed and unlensed data. There is evidence of a break in the scaling relationship between high and low SFR surface density ( ) clumps. The size–luminosity power-law fit results are ∼ 2.8 and ∼ 1.7 for low and high clumps, respectively. We present a model where star-forming clumps form at locations of gravitational instability and produce an ionized region represented by the Strömgren radius. A radius smaller than the scale height of the disk results in a scaling relationship of L ∝ r 3 (high clumps), and a scaling of L ∝ r 2 (low clumps) if the radius is larger than the disk scale height.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call