English

Bayesian Optimization of Pythia8 Tunes

High Energy Physics - Phenomenology 2025-05-20 v1 High Energy Physics - Experiment Applications

Abstract

A new tune (set of model parameters) is found for the six most important parameters of the Pythia8 final state parton shower and hadronization model using Bayesian optimization. The tune fits the LEPI data from ALEPH better than the default tune in Pythia8. To the best of our knowledge, we present the most comprehensive application of Bayesian optimization to the tuning of a parton shower and hadronization model using the LEPI data.

Cite

@article{arxiv.2505.11675,
  title  = {Bayesian Optimization of Pythia8 Tunes},
  author = {Ali Al Kadhim and Harrison B Prosper and Stephen Mrenna},
  journal= {arXiv preprint arXiv:2505.11675},
  year   = {2025}
}
R2 v1 2026-06-28T23:36:49.202Z