  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.
