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2022

Comparing Point Cloud Strategies for Collider Event Classification

Onyisi, Peter, Shen, Delon, Thaler, Jesse

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In this paper, we compare several event classification architectures defined on the point cloud representation of collider events.

These approaches, which are based on the frameworks of deep sets and edge convolutions, circumvent many of the difficulties associated with traditional feature engineering.
To benchmark our architectures against more traditional event classification strategies, we perform a case study involving Higgs boson decays to tau leptons.
We find a 2.5 times increase in performance compared to a baseline ATLAS analysis with engineered features.

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