MINLO t-channel single-top plus jet

TL;DR

This paper introduces a next-to-leading order simulation for t-channel single-top plus jet production, enhanced with MINLO and neural network tuning, providing accurate predictions across all phase space regions.

Contribution

It develops a process-specific MINLO implementation with neural network tuning to achieve NLO accuracy for single-top observables in all phase space regions.

Findings

Achieves NLO accuracy for single-top and single-top plus jet observables.

Provides a neural network-based tuning method for the MINLO Sudakov form factor.

Enables physical predictions even in unresolved jet regions.

Abstract

We present a next-to-leading order accurate simulation of t-channel single-top plus jet production matched to parton showers via the POWHEG method. The calculation underlying the simulation is enhanced with a process-specific implementation of the multi-scale improved NLO (MINLO) method, such that it gives physical predictions all through phase space, including regions where the jet additional to the t-channel single-top process is unresolved. We further describe a tuning procedure for the MINLO Sudakov form factor, fitting the coefficient of the first subleading term in its exponent using an artificial neural-network. The latter tuning, implemented as a straightforward event-by-event reweighting, renders the MINLO simulation NLO accurate for t-channel single-top observables, in addition to those of the analogous single-top plus jet process.