Reweighting Monte Carlo Predictions and Automated Fragmentation Variations in Pythia 8

Fuente: arXiv
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Autores principales: Bierlich, Christan, Ilten, Philip, Menzo, Tony, Mrenna, Stephen, Szewc, Manuel, Wilkinson, Michael K., Youssef, Ahmed, Zupan, Jure
Formato: Preprint
Publicado: 2023
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author Bierlich, Christan
Ilten, Philip
Menzo, Tony
Mrenna, Stephen
Szewc, Manuel
Wilkinson, Michael K.
Youssef, Ahmed
Zupan, Jure
author_facet Bierlich, Christan
Ilten, Philip
Menzo, Tony
Mrenna, Stephen
Szewc, Manuel
Wilkinson, Michael K.
Youssef, Ahmed
Zupan, Jure
contents This work reports on a method for uncertainty estimation in simulated collider-event predictions. The method is based on a Monte Carlo-veto algorithm, and extends previous work on uncertainty estimates in parton showers by including uncertainty estimates for the Lund string-fragmentation model. This method is advantageous from the perspective of simulation costs: a single ensemble of generated events can be reinterpreted as though it was obtained using a different set of input parameters, where each event now is accompanied with a corresponding weight. This allows for a robust exploration of the uncertainties arising from the choice of input model parameters, without the need to rerun full simulation pipelines for each input parameter choice. Such explorations are important when determining the sensitivities of precision physics measurements. Accompanying code is available at https://gitlab.com/uchep/mlhad-weights-validation.
format Preprint
id arxiv_https___arxiv_org_abs_2308_13459
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Reweighting Monte Carlo Predictions and Automated Fragmentation Variations in Pythia 8
Bierlich, Christan
Ilten, Philip
Menzo, Tony
Mrenna, Stephen
Szewc, Manuel
Wilkinson, Michael K.
Youssef, Ahmed
Zupan, Jure
High Energy Physics - Phenomenology
This work reports on a method for uncertainty estimation in simulated collider-event predictions. The method is based on a Monte Carlo-veto algorithm, and extends previous work on uncertainty estimates in parton showers by including uncertainty estimates for the Lund string-fragmentation model. This method is advantageous from the perspective of simulation costs: a single ensemble of generated events can be reinterpreted as though it was obtained using a different set of input parameters, where each event now is accompanied with a corresponding weight. This allows for a robust exploration of the uncertainties arising from the choice of input model parameters, without the need to rerun full simulation pipelines for each input parameter choice. Such explorations are important when determining the sensitivities of precision physics measurements. Accompanying code is available at https://gitlab.com/uchep/mlhad-weights-validation.
title Reweighting Monte Carlo Predictions and Automated Fragmentation Variations in Pythia 8
topic High Energy Physics - Phenomenology
url https://arxiv.org/abs/2308.13459