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Monte Carlo tuning in the presence of Matching

B. Cooper, J. Katzy, M. L. Mangano, A. Messina, L. Mijovic, P. Skands

TL;DR

This work identifies and resolves a key inconsistency in ME-PS matched Monte Carlo predictions: mismatches in $\alpha_S$ and $\Lambda_{\mathrm{QCD}}$ across the matrix-element/shower boundary can produce nontrivial, counter-intuitive effects in high-$p_T$ observables. It proposes a straightforward prescription to enforce $\alpha_S$ consistency between AlpGen (ME) and Pythia 6 (PS), implements a new Perugia 2011 'matched' tune, and demonstrates its improved stability under scale variations. The authors validate the approach through detailed comparisons to vector-boson plus jets data from Tevatron and LHC and by examining jet shapes, showing good overall agreement and practical utility for precise multijet predictions. The work provides a principled framework for consistent ME-PS tuning and paves the way for more reliable future analyses at the LHC and beyond.

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.

Monte Carlo tuning in the presence of Matching

TL;DR

This work identifies and resolves a key inconsistency in ME-PS matched Monte Carlo predictions: mismatches in and across the matrix-element/shower boundary can produce nontrivial, counter-intuitive effects in high- observables. It proposes a straightforward prescription to enforce consistency between AlpGen (ME) and Pythia 6 (PS), implements a new Perugia 2011 'matched' tune, and demonstrates its improved stability under scale variations. The authors validate the approach through detailed comparisons to vector-boson plus jets data from Tevatron and LHC and by examining jet shapes, showing good overall agreement and practical utility for precise multijet predictions. The work provides a principled framework for consistent ME-PS tuning and paves the way for more reliable future analyses at the LHC and beyond.

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.

Paper Structure

This paper contains 19 sections, 7 equations, 10 figures, 3 tables.

Table of Contents

  1. Introduction
  2. The Importance of Consistent $\alpha_S$ Treatment in ME-PS Matched Predictions
  3. Theoretical Background
  4. Examples of the interplay between tunes and matching
  5. Stabilising ME-PS Matched Tunings
  6. A New AlpGen + Pythia 6 $\alpha_S$ Consistent Tune
  7. Tests of the Consistent $\alpha_S$ Approach: Behaviour Under Scale Variations
  8. Comparisons with Data
  9. $Z$/$W$+jets production
  10. Jets shapes
  11. Conclusions
  12. Appendix
  13. An $\alpha_S$ Consistent AlpGen + Pythia 6 Tune
  14. AlpGen Parameters
  15. Pythia Parameters
  16. ...and 4 more sections

Figures (10)

  • Figure 1: Ratio of predictions for the leading-jet $E_T$ spectrum in W+jets final states at the Tevatron, obtained with AlpGen plus various MC codes and tunes. The leading jet observable is defined at the particle-level as in the CDF W+jets analysis Aaltonen:2007ip.
  • Figure 2: Comparison of CDF data Aaltonen:2007ip with the leading-jet $E_T$ spectrum predicted by AlpGen plus various MC codes and tunes.
  • Figure 3: Jet ($p_{\rm T}\xspace>20~\rm{GeV}$ and $|\eta|<2.8$) multiplicity distribution in $W$+jets electron channel events in pp collisions at 7 TeV. Distributions are shown for the samples generated with Pythia 6 standalone (left) and with AlpGen + Pythia 6 (right). For each case the distributions obtained when using Perugia 0 (P0), Perugia Hard (Phard) and Perugia Soft (Psoft) tunes are shown. All distributions are scaled so that the value of the first bin agrees with the ATLAS measurement ATLAS-CONF-2011-060.
  • Figure 4: Distribution of the probabilities for the event acceptance (ISVETO=0) or rejection (ISVETO$\neq$0) during the MLM matching step, as a function of the largest $p_{\rm T}\xspace$ shower emission from the initial state radiation (left) and the largest $p_{\rm T}\xspace$ multiple proton-proton interaction in the event (right). The events were generated using exclusive sub-sample of AlpGen + Pythia 6 Perugia 2010 $W$+jets events with exactly three additional partons from the matrix element in the final state for pp collisions at 7 TeV and AlpGen + Pythia 6 Perugia 2010 tune.
  • Figure 5: Comparison of AlpGen + Pythia 6 ($p_{\rm T}\xspace>$20 GeV) jet multiplicity (left) and leading jet transverse momentum (right) distributions in $W$+jets electron channel events. The samples are generated using different AlpGen + Pythia 6 parameter setups described in the text.
  • ...and 5 more figures