SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics

Understand

Deep learning methods have gained popularity in high energy physics for fast modeling of particle showers in detectors.

• Detailed simulation frameworks such as the gold standard Geant4 are computationally intensive, and current deep generative architectures work on discretized, lower resolution versions of the detailed simulation.
• The development of models that work at higher spatial resolutions is currently hindered by the complexity of the full simulation data, and by the lack of simpler, more interpretable benchmarks.
• Our contribution is SUPA, the SUrrogate PArticle propagation simulator, an algorithm and software package for generating data by simulating simplified particle propagation, scattering and shower development in matter.