Rivet analyses
Multiplicity Dependence of Pion, Kaon, Proton and Lambda Production in p–Pb Collisions at 5.02 TeV/nn
Experiment: ALICE (LHC)
Inspire ID: 1244523
Status: UNVALIDATED
Authors: - Johannes Bellm - Christian Bierlich - Cody B Duncan - Patrick Kirchgaesser - Harsh Shah
References: - Phys.Lett. B728 (2014) 25-38 - 10.1016/j.physletb.2013.11.020 - arXiv: 1307.6796
Beams: 1000822080 p+
Beam energies: (328000.0, 4000.0)GeV
Run details: - Hadron multiplicity studies in proton-lead collisions at $\sqrt{s} = 5.02~\TeV$
Identified baryons and mesons plotted in invariant pT spectra as well as average pT and yield ratios. The measurements are done in centrality classes, and one must apply centrality selection by first running the ALICE pB centrality calibration analysis and preloading the produced histograms. No generator level cut on particle life time should be applied.
Source
code:ALICE_2014_I1244523.cc
// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/CentralityProjection.hh"
#include "Rivet/Analyses/AliceCommon.hh"
#include "Rivet/Tools/Cuts.hh"
namespace Rivet {
/// @brief Identified particles in p--Pb @ 5 TeV
class ALICE_2014_I1244523 : public Analysis {
public:
/// Constructor
RIVET_DEFAULT_ANALYSIS_CTOR(ALICE_2014_I1244523);
/// @name Analysis methods
/// @{
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;
}
}
// Catch low fluctuation.
return max(0, int(cBins.size() - index - 2));
}
void scaleHisto(Histo1DPtr h) {
for (auto& b : h->bins()) {
b.scaleW(1./b.xWidth()/b.xMid());
}
}
/// Book histograms and initialise projections before the run
void init() {
// The centrality projection.
declareCentrality(ALICE::V0AMultiplicity(),
"ALICE_2015_CENT_PPB", "V0A", "V0A");
// Define the cuts for the analysis:
// pPb Collision has a centre of mass system shift of +0.465
// They study -0.5 < yCoM < 0.0 -> -0.035 < y < 0.465
const Cut& cut = Cuts::rap < 0.035 && Cuts::rap > -0.465;
//const Cut& cut = Cuts::rap > -0.035 && Cuts::rap < 0.465;
const ALICE::PrimaryParticles fs(cut);
declare(fs,"FS");
// The event trigger.
declare(ALICE::V0AndTrigger(), "V0-AND");
// The centrality bins
centralityBins = {5.,10.,20.,40.,60.,80.,100.};
for (int i = 0; i < 4; ++i) {
// First we book the invariant spectra.
book(_histPipT[centralityBins[i]], 1, 1, 1 + i);
if (i < 3) book(_histPipT[centralityBins[i + 4]], 2, 1, 1 + i);
book(_histKpT[centralityBins[i]], 3, 1, 1 + i);
if (i < 3) book(_histKpT[centralityBins[i + 4]], 4, 1, 1 + i);
book(_histK0SpT[centralityBins[i]], 5, 1, 1 + i);
if (i < 3) book(_histK0SpT[centralityBins[i + 4]], 6, 1, 1 + i);
book(_histProtonpT[centralityBins[i]], 7, 1, 1 + i);
if (i < 3) book(_histProtonpT[centralityBins[i + 4]], 8, 1, 1 + i);
book(_histLambdapT[centralityBins[i]], 9, 1, 1 + i);
if (i < 3) book(_histLambdapT[centralityBins[i + 4]], 10, 1, 1 + i);
// The associated sow counters.
book(_sow[centralityBins[i]], "TMP/sow" + toString(i));
if (i < 3) book(_sow[centralityBins[i + 4]], "TMP/sow" + toString(i + 4));
// Then the pi spectra going into the centrality dependent pT ratios.
book(_tmpPi4KpT[centralityBins[i]], "TMP/NPi4K" + toString(i), refData(11, 1, 1 + i));
if (i < 3) book(_tmpPi4KpT[centralityBins[i + 4]], "TMP/NPi4K" + toString(i + 4), refData(12, 1, 1 + i));
book(_tmpPi4PpT[centralityBins[i]], "TMP/NPi4P" + toString(i), refData(13, 1, 1 + i));
if (i < 3) book(_tmpPi4PpT[centralityBins[i + 4]], "TMP/NPi4P" + toString(i + 4), refData(14, 1, 1 + i));
book(_tmpK4LpT[centralityBins[i]], "TMP/NK4L" + toString(i), refData(15, 1, 1 + i));
if (i < 3) book(_tmpK4LpT[centralityBins[i + 4]], "TMP/NK4L" + toString(i + 4), refData(16, 1, 1 + i));
// Then the rest of the spectra going into the cent. dep't pT ratios.
book(_tmpKpT[centralityBins[i]], "TMP/NK" + toString(i), refData(11, 1, 1 + i));
if (i < 3) book(_tmpKpT[centralityBins[i + 4]], "TMP/NK" + toString(i + 4), refData(12, 1, 1 + i));
book(_tmpProtonpT[centralityBins[i]], "TMP/NP" + toString(i), refData(13, 1, 1 + i));
if (i < 3) book(_tmpProtonpT[centralityBins[i + 4]], "TMP/NP" + toString(i + 4), refData(14, 1, 1 + i));
book(_tmpLambdapT[centralityBins[i]], "TMP/NL" + toString(i), refData(15, 1, 1 + i));
if (i < 3) book(_tmpLambdapT[centralityBins[i + 4]], "TMP/NL" + toString(i + 4), refData(16, 1, 1 + i));
// Then the centrality dependent pT ratios.
book(_ratioKPi[centralityBins[i]], 11, 1, 1 + i);
if (i < 3) book(_ratioKPi[centralityBins[i + 4]], 12, 1, 1 + i);
book(_ratioPPi[centralityBins[i]], 13, 1, 1 + i);
if (i < 3) book(_ratioPPi[centralityBins[i + 4]], 14, 1, 1 + i);
book(_ratioLK[centralityBins[i]], 15, 1, 1 + i);
if (i < 3) book(_ratioLK[centralityBins[i + 4]], 16, 1, 1 + i);
}
// Mean pT vs. multiplicity class.
book(_histLambdaMeanpT, 17, 1, 1);
book(_histProtonMeanpT, 18, 1, 1);
book(_histK0SMeanpT, 19, 1, 1);
book(_histKMeanpT, 20, 1, 1);
book(_histPiMeanpT, 21, 1, 1);
// Yield ratios.
book(_histKtoPiYield, 22, 1, 1);
book(_histProtontoPiYield, 22, 1, 2);
book(_histLambdatoPiYield, 22, 1, 3);
book(_histKYield, "TMP/KY", refData(22,1,1));
book(_histProtonYield, "TMP/PrY", refData(22,1,2));
book(_histLambdaYield, "TMP/LY", refData(22,1,3));
book(_histPiYield, "TMP/PiY", refData(22,1,1));
book(_histPi4LYield, "TMP/PiLY",refData(22,1,3)); // HepData entry is wrong -- look in the paper.
}
/// Perform the per-event analysis
void analyze(const Event& event) {
// Event trigger.
if (!apply<ALICE::V0AndTrigger>(event, "V0-AND")() ) vetoEvent;
// Centrality
const CentralityProjection& cent = apply<CentralityProjection>(event,"V0A");
double c = cent();
// Find the index for the profiles.
int index = profileIndex(centralityBins, c);
// Find the correct histograms
// all the pion histos
auto pi1Itr = _histPipT.upper_bound(c);
// Test the first one.
if (pi1Itr == _histPipT.end()) return;
auto pi2Itr = _tmpPi4KpT.upper_bound(c);
auto pi3Itr = _tmpPi4PpT.upper_bound(c);
// Then the rest
auto kItr = _histKpT.upper_bound(c);
auto k0Itr = _histK0SpT.upper_bound(c);
auto krItr = _tmpKpT.upper_bound(c);
auto klItr = _tmpK4LpT.upper_bound(c);
auto pItr = _histProtonpT.upper_bound(c);
auto prItr = _tmpProtonpT.upper_bound(c);
auto lItr = _histLambdapT.upper_bound(c);
auto lrItr = _tmpLambdapT.upper_bound(c);
// And the sow
auto sowItr = _sow.upper_bound(c);
sowItr->second->fill();
const ALICE::PrimaryParticles& fs = apply<ALICE::PrimaryParticles>(event,"FS");
// Count number of particles for yields.
int npi = 0, nk = 0, np = 0, nlam = 0;
for (const auto& p : fs.particles()) {
const double pT = p.pT();
const int pid = abs(p.pid());
const double nW = 1 / M_PI / pT; // Dividing and multiplying by 2 because dy.
if (pid == 211) { // pi+/-
++npi;
pi1Itr->second->fill(pT, nW);
pi2Itr->second->fill(pT);
pi3Itr->second->fill(pT);
_histPiMeanpT->fill(_histPiMeanpT->bin(index).xMid(), pT);
}
else if (pid == 321) { // K +/-
++nk;
kItr->second->fill(pT, nW);
krItr->second->fill(pT);
_histKMeanpT->fill(_histKMeanpT->bin(index).xMid(), pT);
}
else if (pid == 310) { // K0S
k0Itr->second->fill(pT, nW);
klItr->second->fill(pT);
_histK0SMeanpT->fill(_histK0SMeanpT->bin(index).xMid(), pT);
}
else if (pid == 2212) { // p + pbar
++np;
pItr->second->fill(pT, nW);
prItr->second->fill(pT);
_histProtonMeanpT->fill(_histProtonMeanpT->bin(index).xMid(), pT);
}
else if (pid == 3122) { // Lambda + Lambdabar
++nlam;
lItr->second->fill(pT, nW);
lrItr->second->fill(pT);
_histLambdaMeanpT->fill(_histLambdaMeanpT->bin(index).xMid(), pT);
}
}
// Fill the yield profiles.
_histKYield->fill(_histKYield->bin(index).xMid(), double(nk));
_histPi4LYield->fill(_histPi4LYield->bin(index).xMid(), double(npi));
_histProtonYield->fill(_histProtonYield->bin(index).xMid(), double(np));
_histPiYield->fill(_histPiYield->bin(index).xMid(), double(npi));
_histLambdaYield->fill(_histLambdaYield->bin(index).xMid(), double(nlam));
}
/// Normalise histograms etc., after the run
void finalize() {
// Loop over centrality classes.
for (int i = 0; i < 7; i++){
// Normalize the spectra.
_histPipT[centralityBins[i]]->scaleW(1./_sow[centralityBins[i]]->sumW());
_histKpT[centralityBins[i]]->scaleW(1./_sow[centralityBins[i]]->sumW());
_histK0SpT[centralityBins[i]]->scaleW(1./_sow[centralityBins[i]]->sumW());
_histProtonpT[centralityBins[i]]->scaleW(1./_sow[centralityBins[i]]->sumW());
_histLambdapT[centralityBins[i]]->scaleW(1./_sow[centralityBins[i]]->sumW());
// Make the pT ratios.
divide(_tmpKpT[centralityBins[i]], _tmpPi4KpT[centralityBins[i]], _ratioKPi[centralityBins[i]]);
divide(_tmpProtonpT[centralityBins[i]], _tmpPi4PpT[centralityBins[i]], _ratioPPi[centralityBins[i]]);
divide(_tmpLambdapT[centralityBins[i]], _tmpK4LpT[centralityBins[i]], _ratioLK[centralityBins[i]]);
}
divide(_histKYield, _histPiYield, _histKtoPiYield);
divide(_histProtonYield, _histPiYield, _histProtontoPiYield);
divide(_histLambdaYield, _histPi4LYield, _histLambdatoPiYield);
}
/// @}
private:
vector<double> centralityBins;
// pT spectra (separated by multiplicity classes)
map<double, Histo1DPtr> _histPipT;
map<double, Histo1DPtr> _histKpT;
map<double, Histo1DPtr> _histK0SpT;
map<double, Histo1DPtr> _histProtonpT;
map<double, Histo1DPtr> _histLambdapT;
// Associated sum of weights.
map<double, CounterPtr> _sow;
// pT spectra for ratios.
map<double, Histo1DPtr> _tmpPi4KpT;
map<double, Histo1DPtr> _tmpPi4PpT;
map<double, Histo1DPtr> _tmpK4LpT;
map<double, Histo1DPtr> _tmpKpT;
map<double, Histo1DPtr> _tmpProtonpT;
map<double, Histo1DPtr> _tmpLambdapT;
// The acual ratios.
map<double, Estimate1DPtr> _ratioKPi;
map<double, Estimate1DPtr> _ratioPPi;
map<double, Estimate1DPtr> _ratioLK;
// Mean pT vs. Multiplicity
Profile1DPtr _histKMeanpT;
Profile1DPtr _histK0SMeanpT;
Profile1DPtr _histProtonMeanpT;
Profile1DPtr _histLambdaMeanpT;
Profile1DPtr _histPiMeanpT;
// Total yields
Profile1DPtr _histKYield;
Profile1DPtr _histProtonYield;
Profile1DPtr _histLambdaYield;
Profile1DPtr _histPiYield;
Profile1DPtr _histPi4LYield;
// Yield ratios.
Estimate1DPtr _histKtoPiYield;
Estimate1DPtr _histProtontoPiYield;
Estimate1DPtr _histLambdatoPiYield;
};
RIVET_DECLARE_PLUGIN(ALICE_2014_I1244523);
}