6–8 Jul 2021
Europe/Zurich timezone

Detecting Anomalous jets with Graph Neural Networks

6 Jul 2021, 15:40
20m
BSM

Speaker

Mr Vishal Singh Ngairangbam (Physical Research Laboratory)

Description

We devise an autoencoder based strategy to facilitate anomaly detection for boosted jets, employ-
ing Graph Neural Networks (GNNs) to do so. To overcome known limitations of GNN autoencoders,
we design a symmetric decoder capable of simultaneously reconstructing edge features and node fea-
tures. Focusing on latent space based discriminators, we find that such setups provide a promising
avenue to isolate new physics and competing SM signatures from sensitivity-limiting QCD jet con-
tributions. We demonstrate the flexibility and broad applicability of this approach using examples
of W bosons, top quarks, and exotic hadronically-decaying exotic scalar boson

Affiliation Physical Research Laboratory, Ahmedabad
Academic Rank PhD student

Primary authors

Akanksha Bhardwaj (University of Glasgow) Christoph Englert (University of Glasgow) Michael Spannowsky (University of Durham (GB)) Oliver Atkinson (University of Glasgow) Mr Vishal Singh Ngairangbam (Physical Research Laboratory)

Presentation materials