Monte Carlo efficiency via negative weight reduction

The generation of large event samples with Monte Carlo Event Generators is expected to be a computational bottleneck for precision phenomenology at the HL-LHC and beyond. This is due in part to the computational cost incurred by negative weights in ‘matched’ calculations combining NLO perturbative QCD with a parton shower: for the same target statistical precision, a larger sample must be generated. We summarise two approaches taken to tackle this problem: the development of the KrkNLO matching method, which uses a redefinition of the PDF factorisation scheme to guarantee positive weights by construction, and the restructuring of the Matchbox module to reduce the fraction of negative weights for Mc@Nlo matching.