Papers › Unbiased Elimination of Negative Weights in Monte Carlo Samples
Unbiased Elimination of Negative Weights in Monte Carlo Samples
Jeppe R. Andersen, Andreas Maier
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We propose a novel method for the elimination of negative Monte Carlo event weights. The method is process-agnostic, independent of any analysis, and preserves all physical observables. We demonstrate the overall performance and systematic improvement with increasing event sample size, based on predictions for the production of a W boson with two jets calculated at next-to-leading order perturbation theory.
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