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ALICE_2016_I1471838

Enhanced production of multi-strange hadrons in high-multiplicity proton-proton collisions.
Experiment: ALICE (LHC)
Inspire ID: 1471838
Status: UNVALIDATED
Authors:
  • Christian Bierlich
References: Beams: p+ p+
Beam energies: (3500.0, 3500.0) GeV
Run details:
  • Minimum bias pp

Measurements of pT spectra and yields of (multi)strange hadrons, as well as protons and pions (yields only) in forward multiplicity classes at 7 TeV. Ratios of yields to pion yields are constructed. The analysis takes care of particle reconstruction as the experiment does, so no finite lifetime should be imposed on generator level. Experimental results are scaled to inelastic cross section, and generator setup should be adjusted accordingly.

Source code: ALICE_2016_I1471838.cc
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// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/ChargedFinalState.hh"
#include "Rivet/Projections/CentralityProjection.hh"
#include "Rivet/Projections/AliceCommon.hh"
#include "Rivet/Tools/AliceCommon.hh"
namespace Rivet {


  /// @brief Strangeness enhancement in pp 7 TeV by ALICE.
  class ALICE_2016_I1471838 : public Analysis {
  public:

    /// Constructor
    DEFAULT_RIVET_ANALYSIS_CTOR(ALICE_2016_I1471838);

    int profileIndex(vector<double> cBins, double c) {
      int index = 100;
      if (c > 0 && c <= cBins[0]) return cBins.size() - 1;
      for (size_t i = 0; i < cBins.size() - 1; ++i) {
        if (c > cBins[i] && c <= cBins[i + 1]) {
	  index = i;
	  break;
	} 
      }
      return max(0, int(cBins.size() - index - 2));
    }

    /// Book histograms and initialise projections before the run
    void init() {
      // Centrality projection.
      declareCentrality(ALICE::V0MMultiplicity(), 
        "ALICE_2015_PPCentrality","V0M","V0M");
      // Central primary particles
      declare(ChargedFinalState(Cuts::abseta < 1.0),"PP");
      declare(ALICE::PrimaryParticles(Cuts::absrap < 0.5),"PPy");
      centralityBins = {1.,5.,10.,15.,20., 30., 40., 50., 70., 100.};
      centralityBinsOmega = {5.,15.,30.,50.,100.};
      // Book histograms
      for (int i = 0; i < 10; ++i) {
        K0SpT[centralityBins[i]] = bookHisto1D(i+1,1,1);
        LambdapT[centralityBins[i]] = bookHisto1D(i+11,1,1);
        XipT[centralityBins[i]] = bookHisto1D(i+21,1,1);
	sow[centralityBins[i]] = bookCounter("sow_" + toString(i));
      }
      for (int i = 0; i < 5; ++i) {
	OmegapT[centralityBinsOmega[i]] = bookHisto1D(i+31,1,1);
	sowOmega[centralityBinsOmega[i]] = bookCounter("sowO_" + toString(i));
      }
      piYield = bookProfile1D(40,1,1);
      pYield = bookProfile1D(41,1,1);
      kYield = bookProfile1D(42,1,1);
      lambdaYield = bookProfile1D(43,1,1);
      xiYield = bookProfile1D(44,1,1);
      omegaYield = bookProfile1D(45,1,1);
      piRebinned = shared_ptr<YODA::Profile1D>(omegaYield->newclone());
      piRebinned->setTitle("piRebinned");
      piRebinned->setPath("/" + name() + "/piRebinned");
      addAnalysisObject(piRebinned);

    }


    /// Perform the per-event analysis
    void analyze(const Event& event) {
      if (apply<ChargedFinalState>(event,"PP").particles().size() < 1) vetoEvent;
      const ALICE::PrimaryParticles& prim = apply<ALICE::PrimaryParticles>(event,"PPy");
      const double weight = event.weight();
      const CentralityProjection& cent = apply<CentralityProjection>(event,"V0M");
      double c  = cent();
      // Find the correct histograms
      auto kptItr = K0SpT.upper_bound(c);
      if (kptItr == K0SpT.end()) return;
      auto lptItr = LambdapT.upper_bound(c);
      if (lptItr == LambdapT.end()) return;
      auto xptItr = XipT.upper_bound(c);
      if (xptItr == XipT.end()) return;
      auto optItr = OmegapT.upper_bound(c);
      if (optItr == OmegapT.end()) return;
      // Fill the sow.
      auto sowItr = sow.upper_bound(c);
      if (sowItr == sow.end()) return;
      auto sowOmegaItr = sowOmega.upper_bound(c);
      if (sowOmegaItr == sowOmega.end()) return;
      sowItr->second->fill(weight);
      sowOmegaItr->second->fill(weight);
      // Fill the pt histograms and count yields.
      int npi = 0, npr = 0, nk = 0;
      int nla = 0, nxi = 0, nom = 0;
      for (auto p : prim.particles()) {
        const double pT = p.pT();
	const int pid = abs(p.pid());
	if (pid == 211) ++npi;
	else if (pid == 2212) ++npr;
	else if (pid == 310) {
	  kptItr->second->fill(pT, weight);
	  ++nk;
	}
	else if (pid == 3122) {
	  lptItr->second->fill(pT, weight);
	  ++nla;
	}
	else if (pid == 3312) {
	  xptItr->second->fill(pT, weight);
	  ++nxi;
	}
	else if (pid == 3334) {
	  optItr->second->fill(pT, weight);
	  ++nom;
	}
      }
      // Fill the profiles of yields.
      int index = profileIndex(centralityBins,c);
      piYield->fillBin(index, double(npi), weight);
      pYield->fillBin(index, double(npr), weight);
      kYield->fillBin(index, double(nk), weight);
      lambdaYield->fillBin(index, double(nla), weight);
      xiYield->fillBin(index, double(nxi), weight);
      index = profileIndex(centralityBinsOmega, c);
      omegaYield->fillBin(index, double(nom), weight);
      piRebinned->fillBin(index,double(npi),weight);
    }


    /// Normalise histograms etc., after the run
    void finalize() {
      // Normalize the spectra
      for (int i = 0; i < 10; ++i) {
        K0SpT[centralityBins[i]]->scaleW(1./sow[centralityBins[i]]->sumW());
        XipT[centralityBins[i]]->scaleW(1./sow[centralityBins[i]]->sumW());
        LambdapT[centralityBins[i]]->scaleW(1./sow[centralityBins[i]]->sumW());
      }
      for (int i = 0; i < 5; ++i) {
	OmegapT[centralityBinsOmega[i]]->scaleW(1./sowOmega[centralityBinsOmega[i]]->sumW());
      }
      // Make the ratios
      kpi = bookScatter2D(36, 1, 1, true);
      ppi = bookScatter2D(47, 1, 1, true);
      lpi = bookScatter2D(37, 1, 1, true);
      xpi = bookScatter2D(38, 1, 1, true);
      opi = bookScatter2D(39, 1, 1, true);
      lk = bookScatter2D(46, 1, 1, true);

      divide(kYield, piYield, kpi);
      kpi->scaleY(2.);
      divide(pYield, piYield, ppi);
      divide(lambdaYield, piYield, lpi);
      divide(xiYield, piYield, xpi);
      divide(omegaYield, piRebinned, opi);
      divide(lambdaYield, kYield, lk);
      lk->scaleY(0.5);

    }

    //@}


    /// @name Histograms
    //@{
    // Histograms ordered in centrality classes
    vector<double> centralityBins;
    vector<double> centralityBinsOmega;

    // pT spectra
    map<double, Histo1DPtr> K0SpT;
    map<double, Histo1DPtr> LambdapT;
    map<double, Histo1DPtr> XipT;
    map<double, Histo1DPtr> OmegapT;
    map<double, CounterPtr> sow;
    map<double, CounterPtr> sowOmega;

    // Total yields
    Profile1DPtr piYield;
    Profile1DPtr pYield;
    Profile1DPtr kYield;
    Profile1DPtr lambdaYield;
    Profile1DPtr xiYield;
    Profile1DPtr omegaYield;
    Profile1DPtr piRebinned;

    // Ratios
    Scatter2DPtr kpi;
    Scatter2DPtr ppi;
    Scatter2DPtr lpi;
    Scatter2DPtr xpi;
    Scatter2DPtr opi;
    Scatter2DPtr lk;
    //@}
  };


  // The hook for the plugin system
  DECLARE_RIVET_PLUGIN(ALICE_2016_I1471838);


}