Jun 2 – 5, 2020
Europe/Zurich timezone

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

Jun 5, 2020, 2:50 PM
Talk Friday


Elias Bernreuther (RWTH Aachen University)


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)


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

Presentation materials