With the High Luminosity LHC coming online in the near future, event generators will need to provide very large event samples to match the experimental precision. Currently, the estimated cost to generate these events exceeds the computing budget of the LHC experiments. To address these issues, the computing efficiency of event generators need to be improved. Many different approaches are being taken to achieve this goal. I will cover the ongoing work on implementing event generators on the GPUs, machine learning the matrix element, machine learning the phase space, and minimizing the number of negative weight events.
@article{arxiv.2202.05991,
title = {Generators and the (Accelerated) Future},
author = {Joshua Isaacson},
journal= {arXiv preprint arXiv:2202.05991},
year = {2023}
}
Comments
11 pages, 8 figures, 5 tables, plenary proceedings for the 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research