Finding EM counterparts for kilonovae with LSST using machine learning

Ved Shah

The project aims to use multi messenger astrophysics principles to find the EM counterparts for gravitational wave events (specifically Binary Neutron Star & Neutron Star - Black Hole mergers) by training machine learning models on synthetic LSST data so that they can be identified for early follow up when the telescope begins operation. Additionally, work done with EM detection rate estimates using Bulla SED’s, will help us understand how many such events we can expect to observe using LSST


This poster will be displayed on Monday and Tuesday.


Career Stage: 
Undergrad Student