Monte Carlo tuning in the presence of Matching

TL;DR

This paper investigates the effects of varying matching scales and parameters in MLM-matched simulations of collider events, proposing improved consistency methods and demonstrating their effectiveness through comparisons with collider data.

Contribution

It introduces a specific prescription to enhance the consistency of MLM matching and addresses how to perform reliable tune variations around a central scale choice.

Findings

Improved matching consistency reduces counter-intuitive results.

Explicit examples show better agreement with collider data.

Method enhances the reliability of simulation tune variations.

Abstract

We consider the impact of varying alpha_s choices (and scales) on each side of the so-called "matching scale" in MLM-matched matrix-element + parton-shower predictions of collider observables. We explain how inconsistent prescriptions can lead to counter-intuitive results and present a few explicit examples, focusing mostly on W/Z + jets processes. We give a specific prescription for how to improve the consistency of the matching and also address how to perform consistent tune variations (e.g., of the renormalization scale) around a central choice. Comparisons to several collider processes are included to illustrate the properties of the resulting improved matching, relying on Alpgen+Pythia6, with the latter using the so-called Perugia 2011 tunes, developed as part of this effort.