Astrophysics Webinar

Strong gravitational lensing provides a unique, independent probe of cosmology through time-delay cosmography, offering crucial insights into dark energy and, most importantly, the Hubble constant, thereby directly addressing the ongoing Hubble tension. The upcoming Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) presents a rare opportunity to discover short-lived lensed transients at an unprecedented scale, primarily supernovae (SNe), along with tidal disruption events (TDEs) and kilonovae (KNe). Their rarity and rapid evolution make timely detection both challenging and essential. 

For the direct-search approach in LSST, we are developing novel algorithms, often using state-of-the-art deep learning, to identify lensed transients directly from multi-epoch imaging. As the coordinator of this team, I will discuss these methods and their collaborative application for the efficient detection of rare lensed transients amid ~10 million nightly alerts, a needle-in-a-haystack challenge where machine learning is indispensable.  I will also discuss the scientific impact of these discoveries, from precision cosmology to studies of the initial mass function (IMF), galaxy evolution, and other astrophysical phenomena aligned with my research interests.