Rivet analyses

Charged particle distributions in different final states at 13~TeV

Experiment: CMS collaboration (LHC)

Inspire ID: 1680318

Status: VALIDATED

Authors: - cms-pag-conveners-smp@cern.ch - Juan Manuel Grados Luyando - Pieters Maxim

References: - Eur.Phys.J. C78 (2018) no.9, 697 - DOI: 10.1140/epjc/s10052-018-6144-y - arXiv: 1806.11245 - http://cms-results.web.cern.ch/cms-results/public-results/publications/FSQ-16-011/

Beams: p+ p+

Beam energies: (6500.0, 6500.0)GeV

Run details: - Inelastic events at 13~TeV centre of mass energy. Tracks in |η| < 2.4 and with $\pT > 0.5~GeV$

Charged particle distributions in different final states at $\sqrt{s} = 13$~TeV by the CMS experiment. Pseudorapidity, multiplicity and transverse momentum distributions of all charged particles. Also the $\pT$ leading charged particle spectrum and its integration as function of $\pT$. The distributions are presented for inelastic, non-single-diffractive and single-diffractive event selections. Please note, that the MC predictions are not scaled to the datapoints, in contrast to Figure 6 in the publication.

Source code:CMS_2018_I1680318.cc

// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/ChargedFinalState.hh"
#include "Rivet/Projections/FinalState.hh"

namespace Rivet {


  class CMS_2018_I1680318 : public Analysis {
  public:

    /// Constructor
    RIVET_DEFAULT_ANALYSIS_CTOR(CMS_2018_I1680318);


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

      // Cuts
      MinEnergy = 5.0; // Particle's energy cut in the forward region [GeV]
      EtaForwardMin = 3.0;
      EtaForwardMax = 5.0;
      EtaCentralCut = 2.4;
      MinParticlePt = 0.5; // [GeV]


      // Initialise and register projections
      const FinalState fsa(Cuts::abseta < EtaForwardMax);
      declare(fsa, "FSA");

      const ChargedFinalState cfs(Cuts::abseta < EtaCentralCut && Cuts::pT > MinParticlePt * GeV);
      declare(cfs, "CFS");

      // Event counters
      book(_num_evts_noCuts, "num_evts_noCuts");
      book(_num_evts_after_cuts_or, "num_evts_after_cuts_or");
      book(_num_evts_after_cuts_and, "num_evts_after_cuts_and");
      book(_num_evts_after_cuts_xor, "num_evts_after_cuts_xor");
      book(_num_evts_after_cuts_xorm, "num_evts_after_cuts_xorm");
      book(_num_evts_after_cuts_xorp, "num_evts_after_cuts_xorp");

      // Histograms
      book(_hist_dNch_all_dEta_OR, 1, 1, 1);
      book(_hist_dNch_all_dEta_AND, 1, 2, 1);
      book(_hist_dNch_all_dEta_XOR, 1, 3, 1);
      book(_hist_dNch_all_dEta_XORpm, 1, 4, 1);

      book(_hist_dNch_all_dpt_OR, 2, 1, 1);
      book(_hist_dNch_all_dpt_AND, 2, 2, 1);
      book(_hist_dNch_all_dpt_XOR, 2, 3, 1);

      book(_hist_dNch_leading_dpt_OR, 3, 1, 1);
      book(_hist_dNch_leading_dpt_AND, 3, 2, 1);
      book(_hist_dNch_leading_dpt_XOR, 3, 3, 1);

      book(_hist_integrated_leading_pt_OR, 4, 1, 1);
      book(_hist_integrated_leading_pt_AND, 4, 2, 1);
      book(_hist_integrated_leading_pt_XOR, 4, 3, 1);

      book(_hist_dNev_all_dM_OR, 5, 1, 1);
      book(_hist_dNev_all_dM_AND, 5, 2, 1);
    }


    /// Perform the per-event analysis
    void analyze(const Event& event) {

      const ChargedFinalState& charged = apply<ChargedFinalState>(event, "CFS");
      const FinalState& fsa = apply<FinalState>(event, "FSA");

      bool activity_plus_side = false, activity_minus_side = false;

      for (const Particle& p : fsa.particles()) {
        if (p.energy() >= MinEnergy) {
          if (inRange(p.eta(), EtaForwardMin, EtaForwardMax)) activity_plus_side = true;
          if (inRange(p.eta(), -1.0 * EtaForwardMax, -1.0 * EtaForwardMin)) activity_minus_side = true;
        }

        // If activity already found in both sides,
        // then there is no point in keep going the loop
        if (activity_plus_side && activity_minus_side) break;
      }

      // Event selections
      const bool cutsor = (activity_plus_side || activity_minus_side);
      const bool cutsand = (activity_plus_side && activity_minus_side);
      const bool cutsxor = ((activity_plus_side && !activity_minus_side)
                            || (!activity_plus_side && activity_minus_side));
      const bool cutsxorm = (!activity_plus_side && activity_minus_side);
      const bool cutsxorp = (activity_plus_side && !activity_minus_side);

      _num_evts_noCuts->fill();
      if (charged.size() >= 1) {
        if (cutsor) _num_evts_after_cuts_or->fill();
        if (cutsand) _num_evts_after_cuts_and->fill();
        if (cutsxor) _num_evts_after_cuts_xor->fill();
        if (cutsxorm) _num_evts_after_cuts_xorm->fill();
        if (cutsxorp) _num_evts_after_cuts_xorp->fill();
      }

      // Loop over charged particles
      double leading_pt = 0;
      for (const Particle& p : charged.particles()) {
        // Find the leading-pt particle of the event
        if (p.pT() > leading_pt) leading_pt = p.pT();

        // Filling histograms
        if (cutsor) _hist_dNch_all_dEta_OR->fill(p.eta());
        if (cutsand) _hist_dNch_all_dEta_AND->fill(p.eta());
        if (cutsxor) _hist_dNch_all_dEta_XOR->fill(p.eta());

        //Average xorm & xorp
        if (cutsxorm) _hist_dNch_all_dEta_XORpm->fill(p.eta());
        if (cutsxorp) _hist_dNch_all_dEta_XORpm->fill(-1.0 * p.eta());

        if (cutsor) _hist_dNch_all_dpt_OR->fill(p.pT());
        if (cutsand) _hist_dNch_all_dpt_AND->fill(p.pT());
        if (cutsxor) _hist_dNch_all_dpt_XOR->fill(p.pT());
      }

      // Filling multiplicity histograms
      if (charged.size() >= 1) {
        if (cutsor) _hist_dNev_all_dM_OR->fill(charged.size());
        if (cutsand) _hist_dNev_all_dM_AND->fill(charged.size());
      }

      // Filling leading-pt histograms
      if (cutsor) _hist_dNch_leading_dpt_OR->fill(leading_pt);
      if (cutsand) _hist_dNch_leading_dpt_AND->fill(leading_pt);
      if (cutsxor) _hist_dNch_leading_dpt_XOR->fill(leading_pt);

      // Integrating leading-pt histograms
      for (size_t i = 0; i < _hist_integrated_leading_pt_OR->numBins(); ++i) {
        double binlimitlow_t = _hist_integrated_leading_pt_OR->bin(i).xMin();
        double weightbw_t = _hist_integrated_leading_pt_OR->bin(i).xWidth();
        double xbin_t = _hist_integrated_leading_pt_OR->bin(i).xMid();
        if (leading_pt > binlimitlow_t) {
          if (cutsor) _hist_integrated_leading_pt_OR->fill(xbin_t, weightbw_t);
          if (cutsand) _hist_integrated_leading_pt_AND->fill(xbin_t, weightbw_t);
          if (cutsxor) _hist_integrated_leading_pt_XOR->fill(xbin_t, weightbw_t);
        }
      }
    }


    /// Normalise histograms etc., after the run
    void finalize() {
      MSG_INFO("Number of selected events: " << endl
                                             << "\t All       = " << _num_evts_noCuts->val() << endl
                                             << "\t Inelastic = " << _num_evts_after_cuts_or->val() << endl
                                             << "\t NSD       = " << _num_evts_after_cuts_and->val() << endl
                                             << "\t Xor       = " << _num_evts_after_cuts_xor->val() << endl
                                             << "\t Xorm      = " << _num_evts_after_cuts_xorm->val() << endl
                                             << "\t Xorp      = " << _num_evts_after_cuts_xorp->val());

      scale(_hist_dNch_all_dEta_OR, 1. / *_num_evts_after_cuts_or);
      scale(_hist_dNch_all_dEta_AND, 1. / *_num_evts_after_cuts_and);
      scale(_hist_dNch_all_dEta_XOR, 1. / *_num_evts_after_cuts_xor);
      scale(_hist_dNch_all_dEta_XORpm, 1. / (*_num_evts_after_cuts_xorm + *_num_evts_after_cuts_xorp));

      scale(_hist_dNch_all_dpt_OR, 1. / *_num_evts_after_cuts_or);
      scale(_hist_dNch_all_dpt_AND, 1. / *_num_evts_after_cuts_and);
      scale(_hist_dNch_all_dpt_XOR, 1. / *_num_evts_after_cuts_xor);

      scale(_hist_dNch_leading_dpt_OR, 1. / *_num_evts_after_cuts_or);
      scale(_hist_dNch_leading_dpt_AND, 1. / *_num_evts_after_cuts_and);
      scale(_hist_dNch_leading_dpt_XOR, 1. / *_num_evts_after_cuts_xor);

      scale(_hist_integrated_leading_pt_OR, 1. / *_num_evts_after_cuts_or);
      scale(_hist_integrated_leading_pt_AND, 1. / *_num_evts_after_cuts_and);
      scale(_hist_integrated_leading_pt_XOR, 1. / *_num_evts_after_cuts_xor);

      scale(_hist_dNev_all_dM_OR, 1. / *_num_evts_after_cuts_or);
      scale(_hist_dNev_all_dM_AND, 1. / *_num_evts_after_cuts_and);
    }


  private:

    // Cuts
    double MinEnergy, EtaForwardMin, EtaForwardMax, EtaCentralCut, MinParticlePt;

    // Counters
    CounterPtr _num_evts_noCuts, _num_evts_after_cuts_and, _num_evts_after_cuts_or, _num_evts_after_cuts_xor,
        _num_evts_after_cuts_xorp, _num_evts_after_cuts_xorm;

    // Histograms
    Histo1DPtr _hist_dNch_all_dEta_AND, _hist_dNch_all_dEta_OR, _hist_dNch_all_dEta_XOR,
        _hist_dNch_all_dEta_XORpm;
    Histo1DPtr _hist_dNch_all_dpt_AND, _hist_dNch_all_dpt_OR, _hist_dNch_all_dpt_XOR;
    Histo1DPtr _hist_dNch_leading_dpt_AND, _hist_dNch_leading_dpt_OR, _hist_dNch_leading_dpt_XOR;
    Histo1DPtr _hist_integrated_leading_pt_AND, _hist_integrated_leading_pt_OR,
        _hist_integrated_leading_pt_XOR;
    Histo1DPtr _hist_dNev_all_dM_AND, _hist_dNev_all_dM_OR;
  };


  RIVET_DECLARE_PLUGIN(CMS_2018_I1680318);

}