Born spreading with consistent shower starting scales in MC@NLO and FxFx merging

Abstract

Negative weights are a major cost in NLO event generation matched to parton showers at the LHC, as they increase the number of events needed for a given statistical precision. Born spreading reduces the fraction of negative-weight $\mathbb S$ events in MC@NLO by redistributing the Born contribution over the radiation variables. It introduces no bias only if everything that is passed to the parton shower together with $\mathbb S$ events depends on Born-level quantities alone. We show that the same condition is needed for the MC counterterms to reproduce the first shower emission, independently of how the radiation phase space is integrated. In MadGraph5_aMC@NLO, the $\mathbb S$-event starting scales did not fully satisfy this condition, which so far prevented the public release of Born spreading. We present a new and consistent construction of the starting scales for ordinary MC@NLO, FxFx merging and MC@NLO-$Δ$, with which Born spreading is now publicly available, including for merged samples. We also study modified formulations of the MC counterterms, and FxFx-merged $W$+jets production with up to two jets at NLO, for which Born spreading reduces the fraction of negative weights after merging without affecting the predictions, and the event samples are generated six times faster than with the former implementation.