The goal of my thesis is to present an analysis of the ASASSN survey core-collapse supernova (CCSN) environments and occurrence rates, to constrain the progenitor stars related to each CCSN subtype. For the first project, I analyzed a sample of 111 galaxies observed by the All-weather MUse Supernova Integral field Nearby Galaxies survey (AMUSING) that hosted CCSNe detected or discovered by ASAS-SN, between 2014 and 2018. This is the largest analysis to date of CCSN host galaxies observed by the MUSE instrument at the Very Large Telescope (VLT). The use of a homogeneous SN sample from ASAS-SN, an untargeted and spectroscopically complete panoramic survey of transients, allows us to perform a minimally biased statistical analysis of CCSN environments. We used stellar population synthesis and spectral fitting techniques to derive physical parameters of all HII regions detected within each galaxy, such as the star formation rate (SFR), Hα equivalent width (EW), and metallicity. By analyzing the nearest HII region to each SN, we found that stripped-envelope supernovae (SESNe) tend to occur in environments with higher values of SFR, Hα EW, and metallicity than H-rich and interacting SNe, with the latter two populations exploding in similar environments. We also found evidence for a strong metallicity dependence on the occurrence of CCSNe relative to star formation (SF) in their host galaxies. We found that the CCSN environment metallicity distribution is significantly lower than the overall distribution of SF within the host galaxies and that the occurrence of CCSN per unit SF as a function of metallicity decreases as metallicity increases. This might have strong implications for different areas of astrophysics. For my next project, I will estimate the volumetric and relative rates of the different CCSN types from the ASASSN survey. By using these estimates and theoretical rates from stellar population modeling, we can constrain ages and masses of their progenitor stars.
Type of project: PhD thesis
Status: Finished. Graduated 2025
Researchers: Thallis De Lourenco Pessi, JOSE LUIS PRIETO KATUNARIC
Funding source: ESO, Becas ANID