The BSM-AI project: SUSY-AI - Generalizing LHC limits on Supersymmetry with Machine Learning

Understand

A key research question at the Large Hadron Collider (LHC) is the test of models of new physics.

• Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: It requires the time consuming generation of scattering events, the simulation of the detector response, the event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiment.
• In the BSM-AI project we attack this challenge with a new approach.
• Machine learning tools are thought to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters.