First NLO-QCD amplitude-assisted ML regression for longitudinal-boson production rate in di-boson events at the LHC, benchmarked against random forests.
Finding the Higgs boson in decays to Z gamma using the matrix element method at Next-to-Leading Order
1 Pith paper cite this work. Polarity classification is still indexing.
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abstract
We illustrate how the Matrix Element Method at Next-to-Leading Order (MEM@NLO) can be used to discriminate between events arising from the production of a Higgs boson, which subsequently decays to a final state consisting of ell^+ell^-gamma, and the background production of the same final state. We illustrate how the method could be used in an experimental analysis by devising cuts on the signal (P_S) and background (P_B) weights that are computed event-by-event in this approach. We find that we can increase the S/sqrt(B) ratio by around 50\% compared to an invariant mass fit on its own. Considering only statistical uncertainty, this is equivalent to recording a factor of around two times more integrated luminosity.
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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.