ML

Developed an auto-encoder model equivariant to Lorentz transformations of the input. We find it outperforms graph and convolutional neural networks on jet reconstruction and anomaly detection tasks.

A systematic investigation of evaluation metrics for fast simulations, including two new ones we propose, the Fréchet and kernel physics distances, which we find to be the most sensitive. We also introduce the generative adversarial particle transformer (GAPT) model, which is significantly faster than MPGAN.

With the increase in luminosity and detector granularity, simulation will be a significant computational challenge in the HL-LHC. To …

The findable, accessible, interoperable, and reusable (FAIR) data principles have provided a framework for examining, evaluating, and …

At the CERN LHC, the task of jet tagging, whose goal is to infer the origin of a jet given a set of final-state particles, is dominated …