Rivet analyses
ATLAS Inclusive jet and dijet cross section measurement at sqrt(s)=13TeV
Experiment: ATLAS (LHC)
Inspire ID: 1634970
Status: VALIDATED
Authors: - Jonathan Bossio - Zdenek Hubacek
References: - JHEP 1805 (2018) 195 - arXiv: 1711.02692
Beams: p+ p+
Beam energies: (6500.0, 6500.0)GeV
Run details: - LHC 13TeV, ATLAS, QCD jet production, anti-kt R=0.4 jets
Inclusive jet and dijet cross-sections are measured in proton-proton collisions at a centre-of-mass energy of 13 TeV. The measurement uses a dataset with an integrated luminosity of 3.2 fb−1 recorded in 2015 with the ATLAS detector at the Large Hadron Collider. Jets are identified using the anti-kt algorithm with a radius parameter value of R = 0.4. The inclusive jet cross-sections are measured double-differentially as a function of the jet transverse momentum, covering the range from 100 GeV to 3.5 TeV, and the absolute jet rapidity up to |y| = 3. The double-differential dijet production cross-sections are presented as a function of the dijet mass, covering the range from 300 GeV to 9 TeV, and the half absolute rapidity separation between the two leading jets within |y| < 3, y*, up to y* = 3. Next-to-leading-order, and next-to-next-to-leading-order for the inclusive jet measurement, perturbative QCD calculations corrected for non-perturbative and electroweak effects are compared to the measured cross-sections.
Source
code:ATLAS_2018_I1634970.cc
// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/FinalState.hh"
#include "Rivet/Projections/FastJets.hh"
namespace Rivet {
/// @brief inclusive jet and dijet at 13 TeV
class ATLAS_2018_I1634970 : public Analysis {
public:
/// Constructor
RIVET_DEFAULT_ANALYSIS_CTOR(ATLAS_2018_I1634970);
/// Book histograms and initialise projections before the run
void init() {
const FinalState fs;
declare(fs,"FinalState");
FastJets fj04(fs, JetAlg::ANTIKT, 0.4, JetMuons::ALL, JetInvisibles::DECAY);
declare(fj04, "AntiKT04");
// |y| and ystar bins
vector<double> ybins{ 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0};
// Book histograms
book(_pThistograms, ybins);
book(_mjjhistograms, ybins);
for (size_t i=1; i < _pThistograms->numBins()+1; ++i) {
book(_pThistograms->bin(i), i, 1, 1);
book(_mjjhistograms->bin(i), 6+i, 1, 1);
}
}
/// Perform the per-event analysis
void analyze(const Event& event) {
const Jets& kt4Jets = apply<FastJets>(event, "AntiKT04").jetsByPt(Cuts::pT > 75*GeV && Cuts::absrap < 3.0);
int nJets = kt4Jets.size();
// Inclusive jet selection
for(int ijet=0;ijet<nJets;++ijet){ // loop over jets
FourMomentum jet = kt4Jets[ijet].momentum();
// pT selection
if (jet.pt()>100.0*GeV){
// Fill distribution
const double absy = jet.absrap();
_pThistograms->fill(absy,jet.pt()/GeV);
}
}
// Dijet selection
if(nJets > 1){ // skip events with less than 2 jets passing pT>75GeV and |y|<3.0 cuts
FourMomentum jet0 = kt4Jets[0].momentum();
FourMomentum jet1 = kt4Jets[1].momentum();
const double rap0 = jet0.rapidity();
const double rap1 = jet1.rapidity();
const double ystar = fabs(rap0-rap1)/2;
const double mass = (jet0 + jet1).mass();
const double HT2 = jet0.pt()+jet1.pt();
if (HT2>200*GeV && ystar<3.0){
// Fill distribution
_mjjhistograms->fill(ystar, mass/GeV);
}
}
}
/// Normalise histograms etc., after the run
void finalize() {
const double xs_norm_factor = 0.5*crossSection() / picobarn / sumOfWeights();
scale(_pThistograms, xs_norm_factor);
scale(_mjjhistograms, crossSectionPerEvent()/picobarn);
divByGroupWidth({_pThistograms, _mjjhistograms});
}
private:
// The inclusive pT spectrum for akt4 jets
Histo1DGroupPtr _pThistograms;
// The dijet mass spectrum for akt4 jets
Histo1DGroupPtr _mjjhistograms;
};
RIVET_DECLARE_PLUGIN(ATLAS_2018_I1634970);
}