Data challenges as a tool for time-domain astronomy

Abstract

Data challenges are emerging as powerful tools with which to answer fundamental astronomical questions. Time-domain astronomy lends itself to data challenges, particularly in the era of classification and anomaly detection. With improved sensitivity of wide-field surveys in optical and radio wavelengths from surveys like the Large Synoptic Survey Telescope (LSST) and the Canadian Hydrogen Intensity Mapping Experiment (CHIME), we are entering the large-volume era of transient astronomy. I highlight some recent time-domain challenges, with particular focus on the Photometric LSST Astronomical Time series Classification Challenge (PLAsTiCC), and describe metrics used to evaluate the performance of those entering data challenges.