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ATLAS_2017_I1509919

Track-based underlying event at 13 TeV in ATLAS
Experiment: ATLAS (LHC)
Inspire ID: 1509919
Status: VALIDATED
Authors:
  • Roman Lysak
References: Beams: p+ p+
Beam energies: (6500.0, 6500.0) GeV
Run details:
  • $pp$ QCD interactions at 13 TeV. Diffractive events should be included.

We present charged-particle distributions sensitive to the underlying event, measured by the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV, in low-luminosity Large Hadron Collider fills corresponding to an integrated luminosity of 1.6 nb${}^{-1}$. The distributions were constructed using charged particles with absolute pseudorapidity less than 2.5 and with transverse momentum greater than 500 MeV, in events with at least one such charged particle with transverse momentum above 1 GeV. These distributions characterise the angular distribution of energy and particle flows with respect to the charged particle with highest transverse momentum, as a function of both that momentum and of charged-particle multiplicity. The results have been corrected for detector effects and are compared to the predictions of various Monte Carlo event generators, experimentally establishing the level of underlying-event activity at LHC Run 2 energies and providing inputs for the development of event generator modelling. The current models in use for UE modelling typically describe this data to 5% accuracy, compared with data uncertainties of less than 1%.

Source code: ATLAS_2017_I1509919.cc
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// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/ChargedFinalState.hh"

namespace Rivet {


  /// Track-based underlying event at 13 TeV in ATLAS
  class ATLAS_2017_I1509919 : public Analysis {
  public:

    // Constructor
    DEFAULT_RIVET_ANALYSIS_CTOR(ATLAS_2017_I1509919);


    // Pre-run histogram and projection booking
    void init() {

      declare(ChargedFinalState(Cuts::abseta < 2.5 && Cuts::pT > 500*MeV), "CFS500");

      for (size_t iR = 0; iR < NREGIONS; ++iR) {
        // Nch profiles vs. pT_lead
        _hist_nch[iR] = bookProfile1D(1, 1 + iR, 1);
        // pTsum profiles vs. pT_lead
        _hist_ptsum[iR] = bookProfile1D(2, 1 + iR, 1);
        // <pT> profiles vs pT_lead (not measured for trans diff)
        if (iR != kTransDiff)  _hist_ptavg[iR] = bookProfile1D(3, 1 + iR, 1);
        // <pT> profiles vs. Nch (not measured for trans diff)
        if (iR != kTransDiff)  _hist_dn_dpt[iR] = bookProfile1D(4, 1 + iR, 1);
        // Only measured for trans max/min
        if ( (iR == kTransMax) || (iR == kTransMin) )  _hist_dn_dpt2[iR] = bookProfile1D(5, 1 + iR, 1);
      }

      for (size_t iC = 0; iC < NCUTS; ++iC) {
        // Nch vs. Delta(phi) profiles
        _hist_N_vs_dPhi[iC] = bookProfile1D(6, 1 + iC, 1);
        // pT vs. Delta(phi) profiles
        _hist_pT_vs_dPhi[iC] = bookProfile1D(7, 1 + iC, 1);
        //ptLead histos only for 1 and 5 GeV cuts
        if ( (iC == 0) || (iC == 1) )  _hist_ptLead[iC] = bookHisto1D(8, 1 + iC, 1);
        // 
        _counters[iC] = bookCounter("Ctr_cut_" + toString(iC));
      }

    }


    void analyze(const Event& event) {

      // Get charged particles (tracks) with pT > 500 MeV
      const ChargedFinalState& charged500 = apply<ChargedFinalState>(event, "CFS500");
      const Particles& particlesAll = charged500.particlesByPt();
      MSG_DEBUG("Num tracks: " << particlesAll.size());

      const Cut& pcut = ( (Cuts::abspid != PID::SIGMAMINUS) && (Cuts::abspid != PID::SIGMAPLUS) &&
                          (Cuts::abspid != PID::XIMINUS)    && (Cuts::abspid != PID::OMEGAMINUS) );
      const Particles& particles = charged500.particlesByPt(pcut);
      MSG_DEBUG("Num tracks without strange baryons: " <<  particles.size());

      // Require at least one track in the event for pTlead histograms
      if (particles.empty()) vetoEvent;
      const double weight = event.weight();
      for (size_t iC = 0; iC < 2; ++iC) {
        if (particles[0].pT() < PTCUTS[iC]*GeV) continue;
        _counters[iC]->fill(weight);
        _hist_ptLead[iC]->fill( particles[0].pT()/GeV, weight);
      }

      // Require at least one track in the event with pT >= 1 GeV for the rest
      if (particles[0].pT() < 1*GeV) vetoEvent;

      // Identify leading track and its phi and pT
      const Particle& p_lead = particles[0];
      const double philead = p_lead.phi();
      const double etalead = p_lead.eta();
      const double pTlead  = p_lead.perp();
      MSG_DEBUG("Leading track: pT = " << pTlead << ", eta = " << etalead << ", phi = " << philead);

      // Iterate over all particles and count particles and scalar pTsum in three basic regions
      vector<double> num(NREGIONS, 0), ptSum(NREGIONS, 0.0), avgpt(NREGIONS, 0.0);

      // Temporary histos that bin Nch and pT in dPhi.
      Histo1D hist_num_dphi(*_hist_N_vs_dPhi[0].get(), "/hist_num_dphi");
      Histo1D hist_pt_dphi(*_hist_pT_vs_dPhi[0].get(), "/hist_pt_dphi");
      hist_num_dphi.reset();
      hist_pt_dphi .reset();

      int    tmpnch[2]   = {0,0};
      double tmpptsum[2] = {0,0};
      for (const Particle& p : particles) {
        const double pT   = p.pT()/GeV;
        const double dPhi = deltaPhi(philead, p.phi()); // in range (0,pi)
        const int    ir   = region_index(dPhi); // gives just toward/away/trans

        // Toward/away/trans region: just count
        num  [ir] += 1;
        ptSum[ir] += pT;

        // Determine which transverse side
        if (ir == kTrans) {
          const size_t iside = (mapAngleMPiToPi(p.phi() - philead) > 0) ? 0 : 1;
          tmpnch  [iside] += 1;
          tmpptsum[iside] += p.pT();
        }

        // Fill temp histos to bin Nch and pT in dPhi
        if (p.genParticle() != p_lead.genParticle()) { // We don't want to fill all those zeros from the leading track...
          hist_num_dphi.fill(dPhi/M_PI*180, 1);
          hist_pt_dphi .fill(dPhi/M_PI*180, pT/GeV);
        }
      }

      // Construct max/min/diff regions
      num[kTransMax ]   = std::max(tmpnch[0], tmpnch[1]);
      num[kTransMin ]   = std::min(tmpnch[0], tmpnch[1]);
      num[kTransDiff]   = num[kTransMax ] - num[kTransMin ];
      ptSum[kTransMax ] = std::max(tmpptsum[0], tmpptsum[1]);
      ptSum[kTransMin ] = std::min(tmpptsum[0], tmpptsum[1]);
      ptSum[kTransDiff] = ptSum[kTransMax ] - ptSum[kTransMin ];
      avgpt[kToward]    = (num[kToward] > 0 ) ? ptSum[kToward] / num[kToward] : 0. ;
      avgpt[kAway]      = (num[kAway  ] > 0 ) ? ptSum[kAway]   / num[kAway]   : 0. ;
      avgpt[kTrans]     = (num[kTrans ] > 0 ) ? ptSum[kTrans]  / num[kTrans]  : 0. ;
      // Avg pt max/min regions determined according sumpt max/min
      int sumptMaxRegID = (tmpptsum[0] >  tmpptsum[1]) ? 0 : 1 ;
      int sumptMinRegID = (sumptMaxRegID == 0) ? 1 : 0;
      avgpt[kTransMax ] = (tmpnch[sumptMaxRegID] > 0) ? tmpptsum[sumptMaxRegID] / tmpnch[sumptMaxRegID] : 0.;
      avgpt[kTransMin ] = (tmpnch[sumptMinRegID] > 0) ? tmpptsum[sumptMinRegID] / tmpnch[sumptMinRegID] : 0.;
      avgpt[kTransDiff] = ((tmpnch[sumptMaxRegID] > 0) && (tmpnch[sumptMinRegID] > 0)) ? avgpt[kTransMax ] - avgpt[kTransMin ] : 0.;


      // Now fill underlying event histograms

      // The densities are calculated by dividing the UE properties by dEta*dPhi
      // -- each basic region has a dPhi of 2*PI/3 and dEta is two times 2.5
      // min/max/diff regions are only half of that
      const double dEtadPhi[NREGIONS] = { 2*2.5 * 2*PI/3.0, 2*2.5 * 2*PI/3.0, 2*2.5 * 2*PI/3.0,
                                          2*2.5 *   PI/3.0, 2*2.5 *   PI/3.0, 2*2.5 *   PI/3.0 };
      for (size_t iR = 0; iR < NREGIONS; ++iR) {

        _hist_nch  [iR]->fill(pTlead/GeV, num[iR]   /dEtadPhi[iR]     , weight);
        _hist_ptsum[iR]->fill(pTlead/GeV, ptSum[iR] /GeV/dEtadPhi[iR] , weight);

        // <pT> profiles vs. pT_lead (first 3 are the same!)
        switch (iR) {
        case kToward    :
        case kAway      :
        case kTrans     :
          if (num[iR] > 0) _hist_ptavg[iR]->fill(pTlead/GeV, avgpt[iR]/GeV, weight);
          break;
        case kTransMax  :
          if (tmpnch[sumptMaxRegID] > 0) _hist_ptavg[iR]->fill(pTlead/GeV, avgpt[iR]/GeV, weight);
          break;
        case kTransMin  :
          if (tmpnch[sumptMinRegID] > 0) _hist_ptavg[iR]->fill(pTlead/GeV, avgpt[iR]/GeV, weight);
          break;
        case kTransDiff :
          break;
        default: //should not get here!!!
          MSG_WARNING("Unknown region in <pT> profiles vs.pt lead switch!!! : " << iR);
        }

        // <pT> profiles vs. Nch (first 3 are the same!)
        switch (iR) {
        case kToward    :
        case kAway      :
        case kTrans     :
          if (num[iR] > 0) _hist_dn_dpt[iR]->fill(num[iR] , avgpt[iR]/GeV, weight);
          break;
        case kTransMax  :
          if (tmpnch[sumptMaxRegID] > 0) {
            _hist_dn_dpt [iR]->fill(num[kTrans]          , avgpt[iR]/GeV, weight);
            _hist_dn_dpt2[iR]->fill(tmpnch[sumptMaxRegID], avgpt[iR]/GeV, weight);
          }
          break;
        case kTransMin  :
          if (tmpnch[sumptMinRegID] > 0) {
            _hist_dn_dpt [iR]->fill(num[kTrans]          , avgpt[iR]/GeV, weight);
            _hist_dn_dpt2[iR]->fill(tmpnch[sumptMinRegID], avgpt[iR]/GeV, weight);
          }
          break;
        case kTransDiff :
          break;
        default : //should not get here!!!
          MSG_INFO("unknown region in <pT> profiles vs. nch switch!!! : " <<  iR);
        }

      }


      // Update the "proper" dphi profile histograms
      // Note that we fill dN/dEtadPhi: dEta = 2*2.5, dPhi = 2*PI/nBins
      const double dEtadPhi2 = (2*2.5 * 2) * M_PI/180.;
      for (size_t i = 0; i < hist_num_dphi.numBins(); ++i) {

        // First Nch
        double mean = hist_num_dphi.bin(i).xMid() ;
        double value = 0.;
        if (hist_num_dphi.bin(i).numEntries() > 0) {
          mean  = hist_num_dphi.bin(i).xMean() ;
          value = hist_num_dphi.bin(i).area()/hist_num_dphi.bin(i).xWidth()/dEtadPhi2;
        }
        for (size_t iC = 0; iC < NCUTS; ++iC) {
          if (pTlead >= PTCUTS[iC]*GeV) _hist_N_vs_dPhi[iC] ->fill(mean, value, weight);
        }

        // Then pT
        mean = hist_pt_dphi.bin(i).xMid();
        value = 0.;
        if (hist_pt_dphi.bin(i).numEntries() > 0) {
          mean  = hist_pt_dphi.bin(i).xMean() ;
          value = hist_pt_dphi.bin(i).area()/hist_pt_dphi.bin(i).xWidth()/dEtadPhi2;
        }
        for (size_t iC = 0; iC < NCUTS; ++iC) {
          if (pTlead >= PTCUTS[iC]*GeV) _hist_pT_vs_dPhi[iC] ->fill(mean, value, weight);
        }
      }

    }


    void finalize() {
      for (size_t iC = 0; iC < NCUTS; ++iC) {
        if (iC == 0 || iC == 1) scale(_hist_ptLead[iC], 1.0/_counters[iC]->sumW());
      }
    }


  private:

    enum regionID {
      kToward = 0,
      kAway,
      kTrans,
      kTransMax,
      kTransMin,
      kTransDiff,
      NREGIONS
    };

    // Little helper function to identify basic Delta(phi) regions: toward/away/trans
    int region_index(double dphi) {
      assert(inRange(dphi, 0.0, PI, CLOSED, CLOSED));
      if (dphi < PI/3.0)    return kToward;
      if (dphi < 2*PI/3.0)  return kTrans;
      return kAway;
    }

    const static size_t NCUTS = 3;
    const vector<double> PTCUTS = { 1., 5., 10. };


    /// @name Histograms
    //@{

    // Nch, sumpT, avgpT profiles vs. pTlead
    Profile1DPtr _hist_nch   [NREGIONS]; //for regions: all 6 regions
    Profile1DPtr _hist_ptsum [NREGIONS]; //for regions: all 6 regions
    Profile1DPtr _hist_ptavg [NREGIONS]; //for regions: trans towards/away/all/min/max
    // Nch, sumpT, avgpT profiles vs. Nch
    Profile1DPtr _hist_dn_dpt [NREGIONS]; //regions: towards/away/ vs nch(region) & trans all/min/max vs nch(trans)
    Profile1DPtr _hist_dn_dpt2[NREGIONS]; //regions: trans min/max vs. nch(region)

    Profile1DPtr _hist_N_vs_dPhi [NCUTS];
    Profile1DPtr _hist_pT_vs_dPhi[NCUTS];
    Histo1DPtr   _hist_ptLead[NCUTS]; //for 1,5 GeV cuts only
    CounterPtr   _counters[NCUTS];

    //@}

  };


  // The hook for the plugin system
  DECLARE_RIVET_PLUGIN(ATLAS_2017_I1509919);

}