LSST TVS SC Subgroup: Tidal Disruption Events
Topic: LSST TDEs
The LSST images will contain thousands of tidal disruption events.
Identifying these valuable transients among a much large population of supernovae and variable AGN is the main challenge that we are preparing for in this subgroup.
Membership
Join the TVS Science Collaboration and this TDE subgroup via the main TVS Webpage. Note that your application should include your science interests and proposed contributions to the current TVS-TDE activities described below. All members are expected to read and abide by the TVS Code of Conduct, the TVS Charter, and the TVS Publication Policy. Those documents describe the priviledges and responsibilities of TVS membership. Members may sign the Code of Conduct and Charter using this web form.
After joining TVS, join the Discovery Alliance Slack workspace and drop a short message in the #tvs-tde channel to indicate your interest in this group. We use the Slack channel for almost all our written communication, including planning and reminders for the bi-weekly telecons. We look forward to having you join us!
Subgroup Contact: Sjoert van Velzen
Active Projects of the TDE Subgroup
- TDE classification Data Challenge: Join our challenge on Kaggle.com (opens October 15 2025; deadline January 31, 2026).
- TDE classifers masterlist:The goal is to bring together results from all photometic classifiers that include TDEs.
- Survey Cadence: Proposing and evaluating strategies for the Rubin survey cadence. We have written metric optimized for photometric discrimination of SNe and TDEs. For this goal, u-band observations are very important.
- AGN classification: Removal of AGN is key for an efficient TDE search. Currently, optical transient surveys (e.g. ASASSN, ZTF) use catalogs of known AGN, which are mainly based on spectroscopic observations or WISE photometric selection. However, at the typical redshift of LSST TDEs, these catalog are not deep enough. We need to understand how well can we classify AGN based on the static LSST photometry from the co-add images.
