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Unsupervised clustering for collider physics

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arxiv 2010.07106 v3 pith:K4NYU6H6 submitted 2020-09-28 physics.data-an hep-ex

Vinicius Mikuni , Florencia Canelli This is my paper · ORCID
classification physics.data-anhep-ex
keywords physicsunsupervisedclusteringmethodusedanomalyappliedcategorise
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We propose a new method for Unsupervised clustering in particle physics named UCluster, where information in the embedding space created by a neural network is used to categorise collision events into different clusters that share similar properties. We show how this method can be applied to an unsupervised multiclass classification as well as for anomaly detection, which can be used for new physics searches.

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    Autoencoders with latent spaces shaped like S^2, S^2×S^2, or RP^2, matched to the phase-space topology of the background, reduce spurious reconstruction errors and give a small but consistent anomaly-detection gain ov...

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