Resampling Algorithms for High Energy Physics Simulations
Jimmy Olsson, Simon Pl\"atzer, Malin Sjodahl
TL;DR
This paper introduces an interleaved resampling method for parton showers in high energy physics, significantly enhancing the statistical convergence of weighted simulation algorithms.
Contribution
The paper presents a novel resampling technique that improves statistical efficiency in high energy physics simulations of parton showers.
Findings
Significant statistical improvement demonstrated
Method enhances convergence of weighted algorithms
Applicable to various simulation examples
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.