Type: Talk
Session: Transient and Variable Star Science II
Author: Maryam Modjaz

Abstract: Stripped-Envelope Supernovae (SESNe) are a major subtype of core-collapse SNe and important for many areas of astrophysics, since they directly link to extreme phenomena such as Long-duration GRBs and Superluminous SNe. However, almost all current photometric classification algorithms designed for finding explosive transients with the Rubin+LSST are not able to robustly identify SESNe in the upcoming data deluge. In this talk, I will present the multi-thronged approach that my research group has developed for setting the stage for training sets with which the community can train their classification algorithms: 1) Producing optical spectral templates of different types of SESNe which then can be redshifted to different z, thus producing the elusive “k-corrections” – including spectra merely days after explosion 2) Curating rest frame UV data of SESNe that can be redshifted to the optical range of Rubin+LSST for various z 3) Characterizing the double-peaked light curves of SNe IIb (where the first peak encoded the progenitor radius) in order to train algorithms for finding them early in Rubin+LSST data.