A Positive Resampler for Monte Carlo events with negative weights

Andersen, Jeppe R.; Gütschow, Christian; Maier, Andreas; Prestel, Stefan

Abstract

We propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative weight. The proposed method guarantees positive weights for all physical distributions, and a correct description of all observables. A desirable side product of the method is the possibility to reduce the size of event samples produced by General Purpose Event Generators, thus lowering the resource demands for subsequent computing-intensive event processing steps. We demonstrate the viability and efficiency of our approach by considering its application to a next-to-leading order + parton shower merged prediction for the production of a W boson in association with multiple jets.

Citation

Andersen, J. R., Gütschow, C., Maier, A., & Prestel, S. (2020). A Positive Resampler for Monte Carlo events with negative weights. The European Physical Journal C, 80(11), Article 1007. https://doi.org/10.1140/epjc/s10052-020-08548-w

• Journal Article Type: Article
• Online Publication Date: Oct 30, 2020
• Publication Date: 2020-11
• Deposit Date: Nov 17, 2020
• Publicly Available Date: Nov 17, 2020
• Journal: European Physical Journal C: Particles and Fields
• Print ISSN: 1434-6044
• Electronic ISSN: 1434-6052
• Publisher: SpringerOpen
• Peer Reviewed: Peer Reviewed
• Volume: 80
• Issue: 11
• Article Number: 1007
• DOI: https://doi.org/10.1140/epjc/s10052-020-08548-w
• Public URL: https://durham-repository.worktribe.com/output/1250824