MC@NLO event generation by reweighting unweighted Born events

TL;DR

This paper introduces a new computational method for NLO+PS event simulation that reweights Born events to match full MC@NLO weights, improving stability and reducing negative weights, validated on LHC processes.

Contribution

It presents a novel reweighting strategy starting from LO events to efficiently generate MC@NLO events with reduced negative weights and improved stability.

Findings

Reweighting from Born events reproduces full MC@NLO results.

Large folding values stabilize the integral and reduce negative weights.

The method has comparable computational times to standard approaches.

Abstract

We propose a computational strategy for NLO+PS simulations in the MC@NLO framework that starts from Born-accurate (LO) events and reweights them to the full MC@NLO S-event weight, while generating H-events separately. We validate the approach on two representative LHC processes and compare to direct NLO event generation for both standard MC@NLO and MC@NLO-Delta matching. Employing large folding values in the radiative variables stabilizes the S-event integral, reduces weight variance, and significantly lowers the fraction of negative weights compared to S-event generation without folding. At fixed precision, this pipeline has comparable wall-clock times relative to standard S-event generation and unweighting, with room for further optimisation.