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| Preprint | PUBDB-2020-02358 |
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2020
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Please use a persistent id in citations: doi:10.3204/PUBDB-2020-02358
Report No.: DCPT/20/30; DESY-20-090; IPPP/20/15; LU-TP-20-21; MCNET-20-14; SAGEX-20-12; arXiv:2005.09375
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.
Keyword(s): parton: showers ; higher-order: 1 ; Monte Carlo ; efficiency ; hadron: scattering ; W: associated production ; jet: production
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Journal Article
A Positive Resampler for Monte Carlo Events with Negative Weights
The European physical journal / C 80(11), 1007 (2020) [10.1140/epjc/s10052-020-08548-w]
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