A Positive Resampler for Monte Carlo Events with Negative Weights
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 boson in association with multiple jets.
Cite
@article{arxiv.2005.09375,
title = {A Positive Resampler for Monte Carlo Events with Negative Weights},
author = {Jeppe R. Andersen and Christian Gutschow and Andreas Maier and Stefan Prestel},
journal= {arXiv preprint arXiv:2005.09375},
year = {2020}
}