Speaker
Theo Heimel
(UCLouvain)
Description
MadEvent7 is a new modular phase-space generation library written in C++ and CUDA, running on both GPUs and CPUs. It features a variety of different phase-space mappings, including the classic MadGraph multi-channel phase space and an optimized implementation of normalizing flows for neural importance sampling, as well as their corresponding inverse mappings. The full functionality is available through a Python API and easily interfaces with deep learning libraries like PyTorch. It will be one of the core components of the upcoming MadGraph7 release.
Significance
This presentation covers the release of a new library for phase-space generation, a major step towards fully GPU- and ML-enabled LHC event generation.
Authors
Theo Heimel
(UCLouvain)
Olivier Mattelaer
(UCLouvain)
Ramon Winterhalder
(Università degli Studi di Milano)
