Presentation #224.08 in the session “The Data Lab Science Platform and Open-Data Ecosystem at NSF's NOIRLab”.
Using Data Lab to Identify Tidal Disruption Events Identifying Tidal Disruption Events (TDEs) with Rubin Observatory will be challenging due to their low rates compared to other transients like supernovae and due to the large variation in the properties of TDEs observed to date. Nonetheless, Rubin Observatory has the capability to dramatically increase the sample of known events from the dozens currently known, discovering about 10 new TDEs every night. One method for identifying TDEs in Rubin Observatory is to use information about the host galaxies to identify likely candidate TDEs for spectroscopic follow-up. TDEs occur at a high rate in post-starburst (or “E+A”) galaxies, at rates of 2×10-4 — 3×10-3 per year per galaxy. I will discuss how a strategy of host galaxy-informed follow-up will enable the discovery of a large number of new TDEs and enable the discovery of a wider variety of TDE behaviors. I will also discuss methods for identifying likely TDE host galaxies in the southern hemisphere for which spectroscopic information will be limited. These programs require large photometric datasets across multiple wavelengths, the ability to cross-match large numbers of sources, and a platform to analyze and classify objects; all of which can be achieved with Data Lab.