AUTOMATED TRANSIENT IDENTIFICATION IN THE DARK ENERGY SURVEY
AUTOMATED TRANSIENT IDENTIFICATION IN THE DARK ENERGY SURVEY
We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where …