Separating wheat from chaff: photometric classification in the age of LSST

The Large Synoptic Survey Telescope will generate a data deluge: millions of transients and variable sources will need to be classified from their light curves. Photometric classification has long been a problem of interest in the astronomical community, but the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) brings a wide range of models together, simulated under LSST-like conditions for the first time. PLAsTiCC was delivered to the community through a Kaggle challenge, designed to stimulate interest in time-series photometric classification and deliver methodologies that will advance the LSST science case. I will give an overview of the road to PLAsTiCC, the models and the validation of the data, discuss some of the results from PLAsTiCC, and discuss the science impact of classification on photometric cosmology with Type Ia supernovae.

Speaker: Renee Hlozek, University of Toronto