http://arxiv.org/abs/1901.05020
We introduce a method for producing a galaxy sample unbiased by surface brightness and stellar mass, by selecting star-forming galaxies via the positions of core-collapse supernovae (CCSNe). Whilst matching $\sim$2400 supernovae from the SDSS-II Supernova Survey to their host galaxies using IAC Stripe 82 legacy coadded imaging, we find $\sim$150 previously unidentified low surface brightness galaxies (LSBGs). Using a sub-sample of $\sim$900 CCSNe, we infer CCSN-rate and star-formation rate densities as a function of galaxy stellar mass, and the star-forming galaxy stellar mass function. Resultant star-forming galaxy number densities are found to increase following a power-law down to our low mass limit of $\sim10^{6.4}$ M$_{\odot}$ by a single Schechter function with a faint-end slope of $\alpha = -1.41$. Number densities are consistent with those found by the EAGLE simulations invoking a $\Lambda$-CDM cosmology. Overcoming surface brightness and stellar mass biases is important for assessment of the sub-structure problem. In order to estimate galaxy stellar masses, a new code for the calculation of galaxy photometric redshifts, zMedIC, is also presented, and shown to be particularly useful for small samples of galaxies.
T. Sedgwick, I. Baldry, P. James, et. al.
Thu, 17 Jan 19
26/51
Comments: 18 pages, 14 figures, accepted for publication in MNRAS