Neural refinement of Monte Carlo sample weights via phase-space scaling and a new resampling protocol that maintains averages and uncertainties.
Automated one-loop calculations: a proof of concept
3 Pith papers cite this work. Polarity classification is still indexing.
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abstract
An algorithm, based on the OPP reduction method, to automatically compute any one-loop amplitude, for all momentum, color and helicity configurations of the external particles, is presented. It has been implemented using the tree-order matrix element code HELAC and the OPP reduction code CutTools. As a demonstration of the potential of the current implementation, results for all sub-processes included in the 2007 Les Houches wish list for LHC, are presented.
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Computes the ratio of ttgamma/tt cross sections at LHC Run II with NLO QCD including off-shell effects, quantifying reduced theoretical uncertainties from correlations.
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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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On the ratio of $t\bar{t}\gamma$ and $t\bar{t}$ cross sections at the LHC
Computes the ratio of ttgamma/tt cross sections at LHC Run II with NLO QCD including off-shell effects, quantifying reduced theoretical uncertainties from correlations.
- SMEFT everywhere: a NLO study of $\boldsymbol{pp \to t\bar{t}H}$ with decaying tops