Jun 2 – 5, 2020
Europe/Zurich timezone

Casting a GraphNet to catch dark showers (8'+2')

Jun 5, 2020, 2:50 PM
10m
Talk Friday

Speaker

Elias Bernreuther (RWTH Aachen University)

Description

Strongly interacting dark sectors predict dark showers, which give rise to novel LHC signatures such as semi-visible jets. However, these are difficult to search for with conventional analysis techniques. In my talk I will first consider the sensitivity of existing and prospective LHC searches to semi-visible jets and then discuss how deep learning can help to distinguish dark showers from background. I will compare different network architectures and show that dynamic graph convolutional networks are particularly well suited to this task. I will then demonstrate that a deep-learned dark shower tagger can strongly improve the sensitivity of existing and prospective searches.

Primary author

Elias Bernreuther (RWTH Aachen University)

Co-authors

Mr Thorben Finke (RWTH Aachen University) Felix Kahlhoefer (RWTH Aachen) Michael Kramer (Rheinisch Westfaelische Tech. Hoch. (DE)) Alexander Mueck

Presentation materials