Abstract
We discuss how Deep Learning could be used to help our quest for new physics at the LHC. After introducing the basic ingredients, we review how new search strategies could be designed, exploiting new opportunities offered by Deep Learning. We then discuss how Deep Learning could indirectly serve the search program, freeing online and offline computing resources, speeding up demanding tasks, e.g., event reconstruction and detector simulation. These resources could be used to extend the search program in new directions. As an example, the proposal of an anomalous event dataset will be discussed.
Date
Dec 1, 2021 4:30 PM China Standard Time
Event
Theory Seminar