CIRCLE WITH A DOT

This #CMSPaper investigates different #AI #machinelearning methods that aim to find jets that are inconsistent with the standard model. It shows that a new method called #Wasserstein normalized autoencodes works much better than other neural networks arxiv.org/abs/2510.02168

In quantum physics, the decay width is a fundamental parameter that quantifies a particle's instability. Measuring the decay width is also a way to check if a particle is decaying to undiscovered particles. This #CMSPaper measures the decay width of the Higgs boson in a single signature, which involves a trick comparing Higgs bosons in their on-shell and off-shell production, which means this paper isolates these separately using machine learning https://arxiv.org/abs/2601.05168