From Tens to Tens of Thousands: Supernovae Science in the Big-Data Era

Gautham Narayan

Lasker Data Science Fellow
Space Telescope Science Institute

Despite observations of thousands of type Ia supernovae (SNe Ia), we still do not have a clear understanding of the progenitor systems of these explosions. Our limited understanding of these events restricts our understanding of the nature of Dark Energy. The most promising path to understanding the progenitor physics is obtaining observations of the SNe Ia within a few days of the explosion.

I will discuss SN2018oh and other spectroscopically confirmed SNe Ia with exceptionally early-time observations, discovered by the Kepler Extragalactic Survey (KEGS), and the implications the exquisite K2 light curves have for different SNe Ia progenitor scenarios. While events with such early observations are exceedingly rare, each provides an invaluable piece of the puzzle. To scale from tens to tens of thousands of objects, we must rapidly follow-up new events from wide-field ground-based surveys. I'll discuss work to use cutting edge data science and deep learning techniques to identify these, and other multi-messenger astrophysical phenomena in real-time within the Zwicky Transient Facility (ZTF). I will highlight how we're preparing for LIGO's O3 campaign, and some of the interesting sources we've already identified within ZTF with the ANTARES system. Finally, I'll outline how we're preparing the community to jump scale from the current generation of surveys such as ZTF to the LSST (Large Synoptic Survey Telescope).