Unsupervised clustering for collider physics

Understand

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.