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ATLAS_2011_S9126244

Measurement of dijet production with a veto on additional central jet activity
Experiment: ATLAS (LHC)
Inspire ID: 917526
Status: VALIDATED
Authors:
  • Graham Jones
References: Beams: p+ p+
Beam energies: (3500.0, 3500.0) GeV
Run details:
  • Require QCD interactions at 7TeV. A substantial number of events are required to populate the large rapidity seperation region.

A measurement of the jet activity in rapidity intervals bounded by a dijet system. The fraction of events passing a veto requirement are shown as a function of both the rapidity interval size and the average transverse momentum of the dijet system. The average number of jets above the veto threshold are also shown as a function of the same variables. There are two possible selection criteria applied to data. Either the two highest transverse momentum jets or the jets most forward and backward in rapidity are taken to define the dijet system, where the veto threhsold is 20\;GeV. Additionally for the latter selection an alternative veto transverse momentum threshold which is equal to the average transverse momentum is applied. Jet selections are based on the anti-$k_t$ algorithm with $R=0.6$, $p_\perp > 20$\;GeV and $|y_\text{jet}| < 4.4$.

Source code: ATLAS_2011_S9126244.cc
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// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/FinalState.hh"
#include "Rivet/Projections/FastJets.hh"

#include "Rivet/Tools/BinnedHistogram.hh"

namespace Rivet {


  struct ATLAS_2011_S9126244_Plots {

    int selectionType; ///< The HepData y-axis code
    string intermediateHistName;

    // Gap fraction vs DeltaY plot setup
    int _gapFractionDeltaYHistIndex;
    vector<double> _gapFractionDeltaYSlices;
    BinnedHistogram<double> _h_gapVsDeltaYVeto;
    BinnedHistogram<double> _h_gapVsDeltaYInc;

    // Gap fraction vs ptBar plot setup
    int _gapFractionPtBarHistIndex;
    vector<double> _gapFractionPtBarSlices;
    BinnedHistogram<double> _h_gapVsPtBarVeto;
    BinnedHistogram<double> _h_gapVsPtBarInc;

    // Gap fraction vs Q0 plot setup
    int _gapFractionQ0HistIndex;
    vector<double> _gapFractionQ0SlicesPtBar;
    vector<double> _gapFractionQ0SlicesDeltaY;
    vector<Histo1DPtr> _h_vetoPt;
    vector<Scatter2DPtr> _d_vetoPtGapFraction;
    vector<double> _vetoPtTotalSum; ///< @todo Can this just be replaced with _h_vetoPt.integral()?

    // Average njet vs DeltaY setup
    int _avgNJetDeltaYHistIndex;
    vector<double> _avgNJetDeltaYSlices;
    vector<Profile1DPtr> _p_avgJetVsDeltaY;

    // Average njet vs PptBar setup
    int _avgNJetPtBarHistIndex;
    vector<double> _avgNJetPtBarSlices;
    vector<Profile1DPtr> _p_avgJetVsPtBar;
  };



  /// ATLAS dijet production with central jet veto
  /// @todo Make sure that temp histos are removed
  class ATLAS_2011_S9126244 : public Analysis {
  public:

    /// Constructor
    ATLAS_2011_S9126244()
      : Analysis("ATLAS_2011_S9126244")
    {    }


  public:

    /// Book histograms and initialise projections before the run
    void init() {

      // Initialize the lone projection required
      declare(FastJets(FinalState(), FastJets::ANTIKT, 0.6), "AntiKtJets06");

      // Initialize plots for each selection type
      _selectionPlots[0].intermediateHistName = "highestPt";
      _selectionPlots[0].selectionType = 1;
      _selectionPlots[0]._gapFractionDeltaYHistIndex = 6;
      _selectionPlots[0]._gapFractionPtBarHistIndex = 1;
      _selectionPlots[0]._gapFractionQ0HistIndex = 13;
      _selectionPlots[0]._avgNJetDeltaYHistIndex = 37;
      _selectionPlots[0]._avgNJetPtBarHistIndex = 26;
      _selectionPlots[0]._gapFractionDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      _selectionPlots[0]._gapFractionPtBarSlices = {{ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }};
      _selectionPlots[0]._gapFractionQ0SlicesPtBar = {{ 70.0, 90.0, 120.0, 150.0, 210.0, 240.0 }};
      _selectionPlots[0]._gapFractionQ0SlicesDeltaY = {{ 2.0, 3.0, 4.0, 5.0 }};
      _selectionPlots[0]._avgNJetPtBarSlices = {{ 1.0, 2.0, 3.0, 4.0, 5.0 }};
      _selectionPlots[0]._avgNJetDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      initializePlots(_selectionPlots[0]);

      _selectionPlots[1].intermediateHistName = "forwardBackward";
      _selectionPlots[1].selectionType = 2;
      _selectionPlots[1]._gapFractionDeltaYHistIndex = 6;
      _selectionPlots[1]._gapFractionPtBarHistIndex = 1;
      _selectionPlots[1]._gapFractionQ0HistIndex = 13;
      _selectionPlots[1]._avgNJetDeltaYHistIndex = 37;
      _selectionPlots[1]._avgNJetPtBarHistIndex = 26;
      _selectionPlots[1]._gapFractionDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      _selectionPlots[1]._gapFractionPtBarSlices = {{ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }};
      _selectionPlots[1]._gapFractionQ0SlicesPtBar = {{ 70.0, 90.0, 120.0, 150.0, 210.0, 240.0 }};
      _selectionPlots[1]._gapFractionQ0SlicesDeltaY = {{ 2.0, 3.0, 4.0, 5.0 }};
      _selectionPlots[1]._avgNJetPtBarSlices = {{ 1.0, 2.0, 3.0, 4.0, 5.0 }};
      _selectionPlots[1]._avgNJetDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      initializePlots(_selectionPlots[1]);

      _selectionPlots[2].intermediateHistName = "forwardBackward_PtBarVeto";
      _selectionPlots[2].selectionType = 1;
      _selectionPlots[2]._gapFractionDeltaYHistIndex = 19;
      _selectionPlots[2]._avgNJetDeltaYHistIndex = 30;
      _selectionPlots[2]._gapFractionDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      _selectionPlots[2]._avgNJetDeltaYSlices = {{ 70.0, 90.0, 120.0, 150.0, 180.0, 210.0, 240.0, 270.0 }};
      initializePlots(_selectionPlots[2]);
    }


    void initializePlots(ATLAS_2011_S9126244_Plots& plots) {

      // Gap fraction vs DeltaY
      if (!plots._gapFractionDeltaYSlices.empty()) {
        for (size_t x = 0; x < plots._gapFractionDeltaYSlices.size()-1; x++) {
          const string vetoHistName = "TMP/gapDeltaYVeto_" + plots.intermediateHistName + "_" + to_str(x);
          const string inclusiveHistName = "TMP/gapDeltaYInclusive_" + plots.intermediateHistName + "_" + to_str(x);
          plots._h_gapVsDeltaYVeto.addHistogram(plots._gapFractionDeltaYSlices[x], plots._gapFractionDeltaYSlices[x+1],
                                                bookHisto1D(vetoHistName,refData(plots._gapFractionDeltaYHistIndex+x, 1,plots.selectionType)));
          plots._h_gapVsDeltaYInc.addHistogram(plots._gapFractionDeltaYSlices[x], plots._gapFractionDeltaYSlices[x+1],
                                               bookHisto1D(inclusiveHistName,refData(plots._gapFractionDeltaYHistIndex+x, 1, plots.selectionType)));
        }
      }

      // Average njet vs DeltaY
      if (!plots._avgNJetDeltaYSlices.empty()) {
        for (size_t x = 0; x < plots._avgNJetDeltaYSlices.size()-1; x++) {
          plots._p_avgJetVsDeltaY += bookProfile1D(plots._avgNJetDeltaYHistIndex+x, 1, plots.selectionType);
        }
      }

      // Gap fraction vs PtBar
      if (!plots._gapFractionPtBarSlices.empty()) {
        for (size_t x = 0; x < plots._gapFractionPtBarSlices.size()-1; x++) {
          const string vetoHistName = "TMP/gapPtBarVeto_" + plots.intermediateHistName + "_" + to_str(x);
          const string inclusiveHistName = "TMP/gapPtBarInclusive_" + plots.intermediateHistName + "_" + to_str(x);
          plots._h_gapVsPtBarVeto.addHistogram(plots._gapFractionPtBarSlices[x], plots._gapFractionPtBarSlices[x+1],
                                               bookHisto1D(vetoHistName,refData(plots._gapFractionPtBarHistIndex+x, 1, plots.selectionType)));
          plots._h_gapVsPtBarInc.addHistogram(plots._gapFractionPtBarSlices[x], plots._gapFractionPtBarSlices[x+1],
                                              bookHisto1D(inclusiveHistName,refData(plots._gapFractionPtBarHistIndex+x, 1, plots.selectionType)));
        }
      }

      // Average njet vs PtBar
      if (!plots._avgNJetPtBarSlices.empty()) {
        for (size_t x=0; x<plots._avgNJetPtBarSlices.size()-1; x++) {
          plots._p_avgJetVsPtBar += bookProfile1D(plots._avgNJetPtBarHistIndex+x, 1, plots.selectionType);
        }
      }

      // Gap fraction vs Q0
      int q0PlotCount = 0;
      for (size_t x = 0; x < plots._gapFractionQ0SlicesPtBar.size()/2; x++) {
        for (size_t y = 0; y < plots._gapFractionQ0SlicesDeltaY.size()/2; y++) {
          const string vetoPtHistName = "TMP/vetoPt_" + plots.intermediateHistName + "_" + to_str(q0PlotCount);
          plots._h_vetoPt += bookHisto1D(vetoPtHistName, refData(plots._gapFractionQ0HistIndex + q0PlotCount, 1, plots.selectionType));
          plots._d_vetoPtGapFraction += bookScatter2D(plots._gapFractionQ0HistIndex + q0PlotCount, 1, plots.selectionType);
          plots._vetoPtTotalSum += 0.0; ///< @todo Can this just be replaced with _h_vetoPt.integral()?
          q0PlotCount += 1;
        }
      }
    }


    /// Perform the per-event analysis
    void analyze(const Event& event) {
      const double weight = event.weight();

      // Get minimal list of jets needed to be considered
      double minimumJetPtBar = 50.0*GeV; // of interval defining jets

      vector<FourMomentum> acceptJets;
      foreach (const Jet& jet, apply<FastJets>(event, "AntiKtJets06").jetsByPt(20.0*GeV)) {
        if (jet.absrap() < 4.4) {
          acceptJets.push_back(jet.momentum());
        }
      }

      // If we can't form an interval, drop out of the analysis early
      if (acceptJets.size() < 2) vetoEvent;

      // Analyze leading jet case
      if (acceptJets[0].pT() + acceptJets[1].pT() > 2*minimumJetPtBar) {
        analyzeJets(acceptJets, _selectionPlots[0], weight, 20.0*GeV);
      }

      // Find the most forward-backward jets
      size_t minRapidityJet = 0, maxRapidityJet = 0;
      for (size_t j = 1; j < acceptJets.size(); j++) {
        if (acceptJets[j].rapidity() > acceptJets[maxRapidityJet].rapidity()) maxRapidityJet = j;
        if (acceptJets[j].rapidity() < acceptJets[minRapidityJet].rapidity()) minRapidityJet = j;
      }

      // Make a container of jet momenta with the extreme f/b jets at the front
      vector<FourMomentum> fwdBkwdJets;
      fwdBkwdJets.push_back(acceptJets[maxRapidityJet]);
      fwdBkwdJets.push_back(acceptJets[minRapidityJet]);
      for (size_t j = 0; j < acceptJets.size(); j++) {
        if (j == minRapidityJet || j == maxRapidityJet) continue;
        fwdBkwdJets.push_back(acceptJets[j]);
      }

      if (fwdBkwdJets[0].pT() + fwdBkwdJets[1].pT() > 2*minimumJetPtBar) {
        // Use most forward/backward jets in rapidity to define the interval
        analyzeJets(fwdBkwdJets, _selectionPlots[1], weight, 20.0*GeV);
        // As before but now using PtBar of interval to define veto threshold
        analyzeJets(fwdBkwdJets, _selectionPlots[2], weight, (fwdBkwdJets[0].pT()+fwdBkwdJets[1].pT())/2.0);
      }
    }


    /// Fill plots!
    void analyzeJets(vector<FourMomentum>& jets, ATLAS_2011_S9126244_Plots& plots,
                     const double weight, double vetoPtThreshold) {

      // Calculate the interval size, ptBar and veto Pt (if any)
      const double intervalSize = fabs(jets[0].rapidity()-jets[1].rapidity());
      const double ptBar = (jets[0].pT()+jets[1].pT())/2.0;

      const double minY = min(jets[0].rapidity(), jets[1].rapidity());
      const double maxY = max(jets[0].rapidity(), jets[1].rapidity());

      double vetoPt = 0.0*GeV;
      for (size_t j = 2; j < jets.size(); j++) {
        if (inRange(jets[j].rapidity(), minY, maxY)) vetoPt = max(jets[j].pT(), vetoPt);
      }

      // Fill the gap fraction vs delta Y histograms
      plots._h_gapVsDeltaYInc.fill(ptBar/GeV, intervalSize, weight);
      if (vetoPt < vetoPtThreshold) {
        plots._h_gapVsDeltaYVeto.fill(ptBar/GeV, intervalSize, weight);
      }

      // Fill the gap fraction vs ptBar histograms
      plots._h_gapVsPtBarInc.fill(intervalSize, ptBar/GeV,  weight);
      if (vetoPt < vetoPtThreshold) {
        plots._h_gapVsPtBarVeto.fill(intervalSize, ptBar/GeV, weight);
      }

      // Count the number of veto jets present
      int vetoJetsCount = 0;
      for (size_t j = 2; j < jets.size(); j++) {
        if (inRange(jets[j].rapidity(), minY, maxY) && jets[j].pT() > vetoPtThreshold) {
          vetoJetsCount += 1;
        }
      }

      // Fill the avg NJet, deltaY slices
      if (!plots._avgNJetPtBarSlices.empty()) {
      for (size_t i = 0; i < plots._avgNJetPtBarSlices.size()-1; i++) {
        if (inRange(intervalSize, plots._avgNJetPtBarSlices[i], plots._avgNJetPtBarSlices[i+1])) {
          plots._p_avgJetVsPtBar[i]->fill(ptBar/GeV, vetoJetsCount, weight);
        }
      }
      }

      // Fill the avg NJet, ptBar slices
      if (!plots._avgNJetDeltaYSlices.empty()) {
      for (size_t i = 0; i < plots._avgNJetDeltaYSlices.size()-1; i++) {
        if (inRange(ptBar/GeV, plots._avgNJetDeltaYSlices[i], plots._avgNJetDeltaYSlices[i+1])) {
          plots._p_avgJetVsDeltaY[i]->fill(intervalSize, vetoJetsCount, weight);
        }
      }
      }

      // Fill the veto pt plots
      int q0PlotCount = 0;
      for (size_t x = 0; x < plots._gapFractionQ0SlicesPtBar.size()/2; x++) {
        for (size_t y = 0; y < plots._gapFractionQ0SlicesDeltaY.size()/2; y++) {
          // Check if it should be filled
          if ( ptBar/GeV < plots._gapFractionQ0SlicesPtBar[x*2] ||
               ptBar/GeV >= plots._gapFractionQ0SlicesPtBar[x*2+1] ) {
            q0PlotCount++;
            continue;
          }

          if ( intervalSize < plots._gapFractionQ0SlicesDeltaY[y*2] ||
               intervalSize >= plots._gapFractionQ0SlicesDeltaY[y*2+1] ) {
            q0PlotCount++;
            continue;
          }

          plots._h_vetoPt[q0PlotCount]->fill(vetoPt, weight);
          plots._vetoPtTotalSum[q0PlotCount] += weight;

          q0PlotCount++;
        }
      }
    }


    /// Derive final distributions for each selection
    void finalize() {
      foreach (const ATLAS_2011_S9126244_Plots& plots, _selectionPlots) {

        /// @todo Clean up temp histos -- requires restructuring the temp histo struct

        for (size_t x = 0; x < plots._h_gapVsDeltaYVeto.getHistograms().size(); x++) {
          divide(plots._h_gapVsDeltaYVeto.getHistograms()[x], plots._h_gapVsDeltaYInc.getHistograms()[x],
                 bookScatter2D(plots._gapFractionDeltaYHistIndex+x, 1, plots.selectionType));
        }
        for (size_t x = 0; x < plots._h_gapVsPtBarVeto.getHistograms().size(); x++) {
          divide(plots._h_gapVsPtBarVeto.getHistograms()[x], plots._h_gapVsPtBarInc.getHistograms()[x],
                 bookScatter2D(plots._gapFractionPtBarHistIndex+x, 1, plots.selectionType));
        }

        for (size_t h = 0; h < plots._d_vetoPtGapFraction.size(); h++) {
          finalizeQ0GapFraction(plots._vetoPtTotalSum[h], plots._d_vetoPtGapFraction[h], plots._h_vetoPt[h]);
        }
      }
    }


    /// Convert the differential histograms to an integral histo and assign binomial errors as a efficiency
    /// @todo Should be convertible to a YODA ~one-liner using toIntegralEfficiencyHisto
    void finalizeQ0GapFraction(double totalWeightSum, Scatter2DPtr gapFractionDP, Histo1DPtr vetoPtHist) {
      for (size_t i = 0; i < vetoPtHist->numBins(); ++i) {
        const double vetoPtWeightSum = vetoPtHist->integral(i); ///< Integral (with underflow) up to but not including bin i
        // Calculate the efficiency & binomial uncertainty
        const double eff = (totalWeightSum != 0) ? vetoPtWeightSum/totalWeightSum : 0;
        const double effErr = (totalWeightSum != 0) ? sqrt( eff*(1.0-eff)/totalWeightSum ) : 0;
	// get the x coord and bin width
	const double x    = vetoPtHist->bin(i).xMid();
	const double xerr = 0.5*vetoPtHist->bin(i).xWidth();
	gapFractionDP->addPoint(x, eff, xerr, effErr);
      }
    }


  private:

    // Struct containing the complete set of plots, times 3 for the different selections
    ATLAS_2011_S9126244_Plots _selectionPlots[3];

  };


  // The hook for the plugin system
  DECLARE_RIVET_PLUGIN(ATLAS_2011_S9126244);

}