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.
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.
citing papers explorer
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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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Stay Positive: Neural Refinement of Sample Weights
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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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.