MadGraph5_aMC@NLO automates tree-level, NLO, shower-matched, and merged cross-section computations for collider processes in a unified flexible framework.
The Matrix Element Method at Next-to-Leading Order
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
This paper presents an extension of the matrix element method to next-to-leading order in perturbation theory. To accomplish this we have developed a method to calculate next-to-leading order weights on an event-by-event basis. This allows for the definition of next-to-leading order likelihoods in exactly the same fashion as at leading order, thus extending the matrix element method to next-to-leading order. A welcome by-product of the method is the straightforward and efficient generation of unweighted next-to-leading order events. As examples of the application of our next-to-leading order matrix element method we consider the measurement of the mass of the Z boson and also the search for the Higgs boson in the four lepton channel.
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hep-ph 2representative citing papers
First NLO-QCD amplitude-assisted ML regression for longitudinal-boson production rate in di-boson events at the LHC, benchmarked against random forests.
citing papers explorer
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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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Higher-order effects in amplitude-assisted polarisation extraction with machine-learning techniques
First NLO-QCD amplitude-assisted ML regression for longitudinal-boson production rate in di-boson events at the LHC, benchmarked against random forests.