A resonance-sensitive metric using relative transverse momenta allows cell resampling to reduce negative weights in NLO W+2jets samples while preserving resonance predictions with high accuracy.
Reducing negative weights in Monte Carlo event generation with Sherpa
6 Pith papers cite this work. Polarity classification is still indexing.
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abstract
An increase in theoretical precision of Monte Carlo event generators is typically accompanied by an increased need for computational resources. One major obstacle are negative weighted events, which appear in Monte Carlo simulations with higher perturbative accuracy. While they can be handled somewhat easily in fixed-order calculations, they are a major concern for particle level event simulations. In this article, the origin of negative weights in the S-MC@NLO method is reviewed and mechanisms to reduce the negative weight fraction in simulations with the Sherpa event generator are presented, with a focus on V+jets and tt+jets simulations.
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hep-ph 6representative citing papers
Neural refinement of Monte Carlo sample weights via phase-space scaling and a new resampling protocol that maintains averages and uncertainties.
IRC-safe optimal-transport metrics (EMD, sEMD) enable lower-bias cell resampling of negative-weight NLO Monte Carlo events without intermediate jet clustering.
First automated MC@NLO matching of NLO QCD+EW to an interleaved QCD+QED parton shower with resonance-aware dipole subtraction, validated for Drell-Yan lepton-pair production.
Proof-of-concept for NLO matrix element method via POWHEG projections applied to fully leptonic WW production in SMEFT, demonstrating near-optimal classification of BSM versus SM events using lepton correlations.
A primer by six leading developers maps the full Monte Carlo chain (matrix elements, parton showers, hadronisation, detector simulation, tuning, analysis) and the computing and reproducibility issues that come with it.
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Precision Cell Resampling with a Relative and Resonant Aware Metric
A resonance-sensitive metric using relative transverse momenta allows cell resampling to reduce negative weights in NLO W+2jets samples while preserving resonance predictions with high accuracy.
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Neural refinement of Monte Carlo sample weights via phase-space scaling and a new resampling protocol that maintains averages and uncertainties.
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Optimal-Transport-Based Cell Resampling for Negative and Pathological Event Weights
IRC-safe optimal-transport metrics (EMD, sEMD) enable lower-bias cell resampling of negative-weight NLO Monte Carlo events without intermediate jet clustering.
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A resonance-aware MC@NLO QCD+EW-matched calculation of lepton-pair production
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Matrix element method at NLO: A fine proof of concept in POWHEG
Proof-of-concept for NLO matrix element method via POWHEG projections applied to fully leptonic WW production in SMEFT, demonstrating near-optimal classification of BSM versus SM events using lepton correlations.
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The Monte Carlo Ecosystem in High-Energy Physics: A Primer
A primer by six leading developers maps the full Monte Carlo chain (matrix elements, parton showers, hadronisation, detector simulation, tuning, analysis) and the computing and reproducibility issues that come with it.