A characterization of ASAS-SN core-collapse supernova environments with VLT+MUSE: I. Sample selection, analysis of local environments, and correlations with light curve properties

The analysis of core-collapse supernova (CCSN) environments can provide important information on the life cycle of massive stars and constrain the progenitor properties of these powerful explosions. The MUSE instrument at the VLT enables detailed local environment constraints of the progenitors of large samples of CCSNe. Using a homogeneous SN sample from the ASAS-SN survey has enabled us to perform a minimally biased statistical analysis of CCSN environments. We analyze 111 galaxies observed by MUSE that hosted 112 CCSNe detected or discovered by the ASAS-SN survey between 2014 and 2018. The majority of the galaxies were observed by the the AMUSING survey. Here we analyze the immediate environment around the SN locations and compare the properties between the different CCSN types and their light curves. We used stellar population synthesis and spectral fitting techniques to derive physical parameters for all HII regions detected within each galaxy, including the star formation rate (SFR), H$\alpha$ equivalent width (EW), oxygen abundance, and extinction. We found that stripped-envelope (SE) SNe occur in environments with a higher median SFR, H$\alpha$ EW, and oxygen abundances than SNe II and SNe IIn/Ibn. The distributions of SNe II and IIn are very similar, indicating that these events explode in similar environments. For the SESNe, SNe Ic have higher median SFRs, H$\alpha$ EWs, and oxygen abundances than SNe Ib. SNe IIb have environments with similar SFRs and H$\alpha$ EWs to SNe Ib, and similar oxygen abundances to SNe Ic. We also show that the postmaximum decline rate, $s$, of SNe II correlates with the H$\alpha$ EW, and that the luminosity and the $\Delta m_{15}$ parameter of SESNe correlate with the oxygen abundance, H$\alpha$ EW, and SFR at their environments. This suggests a connection between the explosion mechanisms of these events to their environment properties.