Neural refinement of Monte Carlo sample weights via phase-space scaling and a new resampling protocol that maintains averages and uncertainties.
Automation of one-loop QCD corrections
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present the complete automation of the computation of one-loop QCD corrections, including UV renormalization, to an arbitrary scattering process in the Standard Model. This is achieved by embedding the OPP integrand reduction technique, as implemented in CutTools, into the MadGraph framework. By interfacing the tool so constructed, which we dub MadLoop, with MadFKS, the fully automatic computation of any infrared-safe observable at the next-to-leading order in QCD is attained. We demonstrate the flexibility and the reach of our method by calculating the production rates for a variety of processes at the 7 TeV LHC.
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hep-ph 4representative citing papers
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A color-octet scalar Θ pair-produced via gluons and decaying to quark pairs can account for the CMS excess in equal-mass dijet pairs at 0.95 TeV with a 65 fb cross section for the real case.
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.
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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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The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
MadGraph5_aMC@NLO automates tree-level, NLO, shower-matched, and merged cross-section computations for collider processes in a unified flexible framework.
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Octet scalars shaping LHC distributions in 4-jet final states
A color-octet scalar Θ pair-produced via gluons and decaying to quark pairs can account for the CMS excess in equal-mass dijet pairs at 0.95 TeV with a 65 fb cross section for the real case.
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The Monte Carlo Ecosystem in High-Energy Physics: A Primer
A primer that surveys the architecture, methodologies, computational challenges, and future trajectory of the Monte Carlo event generator ecosystem in collider physics.