https://doi.org/10.1140/epjc/s10052-020-08500-y
Special Article – Tools for Experiment and Theory
Resampling algorithms for high energy physics simulations
1
Department of Mathematics, KTH Royal Institute of Technology, Lindstedtsvägen 25, 100 44, Stockholm, Sweden
2
Particle Physics, Faculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria
3
Department of Astronomy and Theoretical Physics, Lund University, Sölvegatan 14A, 223 62, Lund, Sweden
Received:
21
December
2019
Accepted:
26
September
2020
Published online:
10
October
2020
We demonstrate that the method of interleaved resampling in the context of parton showers can tremendously improve the statistical convergence of weighted parton shower evolution algorithms. We illustrate this by several examples showing significant statistical improvement.
© The Author(s) 2020
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Funded by SCOAP3
