CDS&E: Enabling Population Studies of Supernovae in the Era of Vera Rubin via Simulated-based Inference

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to discover over 10,000 super-luminous supernovae (SLSNe) annually, a significant increase from the around 100 known today. SLSNe are rare, exceptionally bright supernovae, believed to be powered by newly formed, highly magnetized neutron stars called magnetars. This project aims to develop advanced statistical techniques to analyze this unprecedented volume of data, improving our understanding of the progenitor systems and the properties of these magnetars. The methodologies developed can be applied to other SN classes. Additionally, the research team will create an online game that allows users to classify supernovae based on LSST light curves. The game will be featured at the annual Cambridge Science Festival and made available online, engaging and educating a broad audience about these extraordinary cosmic events. A set of LSST SLSNe will be simulated using archival light curves and incorporated into the PLAsTiCC dataset. A custom classifier will be developed to identify SLSNe with high accuracy, and both the datasets and classifier will be made publicly accessible. Second, a new inference pipeline for SLSN light curves will be created, utilizing simulation-based inference (SBI), and its performance will be thoroughly studied under various conditions. A Bayesian hierarchical modeling framework will be implemented to combine individual event data and correct for observational biases. Finally, the first year of LSST data will be analyzed to place the strongest constraints on the underlying SLSN progenitor population. This research award is partially funded by a generous gift from Charles Simonyi to the NSF Astronomy division. The project includes significant contributions to Vera C. Rubin Observatory’s Legacy Survey of Space and Time. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.