Speaker
Michelle Lochner
Description
Since the first direct detection of gravitational waves in
2015, a new window of
discovery in Physics has opened up. However, in order to use
gravitational waves as
probes of cosmology and fundamental Physics, an
electromagnetic counterpart must
be detected. As the sky localisation for a gravitational
wave detection is large,
detected transient sources from follow-up and synoptic
astronomy surveys need to be
rapidly classified to locate potential counterparts in real
time. Machine learning has
emerged as a powerful tool to potentially solve this
problem. In this talk, I will
introduce the concepts of machine learning and use our work
in supernova light curve
classification to illustrate how it can be used for
transient classification for searches of
gravitational wave electromagnetic counterparts.
