Progenitor Mass Distribution for Core-Collapse Supernova Remnants in M31 and M33.

TLDR: In this article, the authors used the star formation histories (SFHs) near 94 supernova remnants (SNRs) to infer the progenitor mass distribution for core-collapse supernovae.

Abstract: Using the star formation histories (SFHs) near 94 supernova remnants (SNRs), we infer the progenitor mass distribution for core-collapse supernovae. We use Bayesian inference and model each SFH with multiple bursts of star formation (SF), one of which is assumed to be associated with the SNR. Assuming single-star evolution, the minimum mass of CCSNe is $7.33^{+0.02}_{-0.16}$ $\text{M}_\odot$, the slope of the progenitor mass distribution is $\alpha = -2.96^{+0.45}_{-0.25}$, and the maximum mass is greater than $\text{M}_\textrm{max} > 59$ $\text{M}_\odot$ with a 68% confidence. While these results are consistent with previous inferences, they also provide tighter constraints. The progenitor distribution is somewhat steeper than a Salpeter initial mass function ($\alpha$ = -2.35). This suggests that either SNR catalogs are biased against the youngest SF regions, or the most massive stars do not explode as easily as lower mass stars. If SNR catalogs are biased, it will most likely affect the slope but not the minimum mass. The uncertainties are dominated by three primary sources of uncertainty, the SFH resolution, the number of SF bursts, and the uncertainty on SF rate in each age bin. We address the first two of these uncertainties, with an emphasis on multiple bursts. The third will be addressed in future work.