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Measurement of four-jet production in proton-proton collisions at sqrt(s) = 7 TeV

CMS Collaboration

TL;DR

This CMS study measures differential cross sections for pp → 4 jets at √s = 7 TeV using 36 pb^-1 of data, reconstructing jets with the anti-$k_{\mathrm{T}}$ algorithm and unfolding to stable-particle level. It compares to a broad set of MC predictions including SPS, MPI, and DPS components, finding that fixed-order matrix elements enhanced with parton showers describe only parts of the phase space and that including double parton scattering improves agreement. The work highlights the importance of MPI/DPS modelling for multijet final states and provides data-driven constraints on generator tunes. The results demonstrate that DPS can leave observable imprints in four-jet topologies and guide future high-pt four-jet studies.

Abstract

Measurements of the differential cross sections for the production of exactly four jets in proton-proton collisions are presented as a function of the transverse momentum pt and pseudorapidity eta, together with the correlations in azimuthal angle and the pt balance among the jets. The data sample was collected in 2010 at a center-of-mass energy of 7 TeV with the CMS detector at the LHC, with an integrated luminosity of 36 inverse picobarns. The cross section for a final state with a pair of hard jets with pt > 50 GeV and another pair with pt > 20 GeV within abs(eta) < 4.7 is measured to be sigma = 330 +- 5 (stat.) +- 45 (syst.) nb. It is found that fixed-order matrix element calculations including parton showers describe the measured differential cross sections in some regions of phase space only, and that adding contributions from double parton scattering brings the Monte Carlo predictions closer to the data.

Measurement of four-jet production in proton-proton collisions at sqrt(s) = 7 TeV

TL;DR

This CMS study measures differential cross sections for pp → 4 jets at √s = 7 TeV using 36 pb^-1 of data, reconstructing jets with the anti- algorithm and unfolding to stable-particle level. It compares to a broad set of MC predictions including SPS, MPI, and DPS components, finding that fixed-order matrix elements enhanced with parton showers describe only parts of the phase space and that including double parton scattering improves agreement. The work highlights the importance of MPI/DPS modelling for multijet final states and provides data-driven constraints on generator tunes. The results demonstrate that DPS can leave observable imprints in four-jet topologies and guide future high-pt four-jet studies.

Abstract

Measurements of the differential cross sections for the production of exactly four jets in proton-proton collisions are presented as a function of the transverse momentum pt and pseudorapidity eta, together with the correlations in azimuthal angle and the pt balance among the jets. The data sample was collected in 2010 at a center-of-mass energy of 7 TeV with the CMS detector at the LHC, with an integrated luminosity of 36 inverse picobarns. The cross section for a final state with a pair of hard jets with pt > 50 GeV and another pair with pt > 20 GeV within abs(eta) < 4.7 is measured to be sigma = 330 +- 5 (stat.) +- 45 (syst.) nb. It is found that fixed-order matrix element calculations including parton showers describe the measured differential cross sections in some regions of phase space only, and that adding contributions from double parton scattering brings the Monte Carlo predictions closer to the data.

Paper Structure

This paper contains 7 sections, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Detector description
  3. Monte Carlo Simulation
  4. Event selection and analysis
  5. Results
  6. Conclusions
  7. The CMS Collaboration

Figures (3)

  • Figure 1: Differential cross sections as a function of the jet transverse momenta $p_{\mathrm{T}}$ (left) and pseudorapidity $\eta$ (right) compared to predictions of powheg, MadGraph, sherpa, and pythia8. Scale factors of $10^6$, $10^4$ and $10^2$ are applied to the measurement of the leading, subleading and third jet, respectively. The yellow band represents the total uncertainty, including the statistical and systematic components added in quadrature.
  • Figure 2: Ratios of predictions of powheg, MadGraph, sherpa, pythia8 and herwig++ to data as a function of the jet transverse momenta $p_{\mathrm{T}}$ (top) and pseudorapidity $\eta$ (bottom) for each specific jet. The yellow band represents the total uncertainty, including the statistical and systematic components added in quadrature.
  • Figure 3: Normalized differential cross sections as a function of the difference in azimuthal angle $\Delta\phi_{\text{soft}}$ (left), $\Delta^{\text{rel}}_{\text{soft}}p_{\mathrm{T}}\xspace$ (middle), and $\Delta\mathrm{S}\xspace$ (right) compared to the predictions of powheg, MadGraph, sherpa, pythia8 and herwig++. A comparison with the powheg predictions interfaced with the parton shower pythia6 tune Z2' without MPI is also shown. The lower panel shows the ratios of the predictions to the data. The yellow band represents the total uncertainty, including the statistical and systematic components added in quadrature. Systematic uncertanties in the normalized cross sections are smaller than the ones in the absolute cross sections, since they are not affected by the migration effects from outside the selected phase space.