Identifying Engine-Driven Supernovae: an Optimized Radio Follow-up Strategy
How exactly massive stars die is still an open question as the zoo of supernovae (SNe) explosions is very wide and variegate. The most extreme and rare type of supernova explosion is an engine-driven supernova associated with relativistic ejecta (gamma-ray burst; GRB), and bright radio emission. In the near future, several synoptic optical surveys (e.g., ZTF and LSST) will offer the unprecedented opportunity of discovering larger samples of the rarest forms of core collapses. Therefore, we need to have an efficient radio follow-up plan to detect and correctly identify engine-driven SNe, as well as promptly distinguish them from other types of radio bright (but non-relativistic) explosions such as e.g. CSM-interacting SNe. The next generation Very Large Array (ngVLA) will significantly contribute to the discovery of new engine-driven supernovae, extending the distance to which we can expect to detect them, increasing the number of detections, and allowing us to infer physical parameters of these sources. In this talk, I will present two new statistical methods that allow us to quantify the efficacy of radio follow-up strategies in detecting and classifying radio bright SNe, as well as potential off-axis GRBs. These methods allow us to optimize the follow-up so as to maximize either the detection probability in general, or the accuracy in identifying relativistic events in particular. I will conclude by providing an example follow-up strategy that correctly identifies most of the relativistic SNe, about half the CSMinteracting SNe, and about a third of the off-axis GRBs.