Rivet analyses
Inclusive b-jet production in pp collisions at 7 TeV
Experiment: CMS (LHC)
Inspire ID: 1089835
Status: VALIDATED
Authors: - cms-pag-conveners-bph@cern.ch - Paolo Gunnellini
References: - Expt page: CMS-BPH-11-022 - JHEP 1204 (2012) 084 - DOI:10.1007/JHEP04(2012)084 - arXiv: 1202.4617
Beams: p+ p+
Beam energies: (3500.0, 3500.0)GeV
Run details: - QCD events with transverse momentum greater than 10 GeV
The inclusive b-jet production cross section in pp collisions at a center-of-mass energy of 7 TeV is measured using data collected by the CMS experiment at the LHC. The cross section is presented as a function of the jet transverse momentum in the range 18 < pT < 200 GeV for several rapidity intervals. The results are also given as the ratio of the b-jet production cross section to the inclusive jet production cross section. The measurement is performed with two different analyses, which differ in their trigger selection and b-jet identification: a jet analysis that selects events with a b jet using a sample corresponding to an integrated luminosity of 34 inverse picobarns, and a muon analysis requiring a b jet with a muon based on an integrated luminosity of 3 inverse picobarns. In both approaches the b jets are identified by requiring a secondary vertex. The results from the two methods are in agreement with each other and with next-to-leading order calculations, as well as with predictions based on the PYTHIA event generator.
Source
code:CMS_2012_I1089835.cc
// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Tools/Logging.hh"
#include "Rivet/Projections/FinalState.hh"
#include "Rivet/Projections/FastJets.hh"
namespace Rivet {
/// @brief Inclusive b-jet production in pp collisions at 7 TeV
class CMS_2012_I1089835 : public Analysis {
public:
/// Constructor
RIVET_DEFAULT_ANALYSIS_CTOR(CMS_2012_I1089835);
/// @name Analysis methods
/// @{
/// Book histograms and initialise projections before the run
void init() {
const FinalState cnfs;
declare(cnfs, "FS");
declare(FastJets(cnfs, JetAlg::ANTIKT, 0.5), "Jets");
book(_h_dsigdpty05, 4, 1, 1);
book(_h_dsigdpty10, 5, 1, 1);
book(_h_dsigdpty15, 6, 1, 1);
book(_h_dsigdpty20, 7, 1, 1);
book(_h_dsigdpty22, 8, 1, 1);
}
/// Perform the per-event analysis
void analyze(const Event& event) {
const FastJets& fastjets = apply<FastJets>(event, "Jets");
const Jets jets = fastjets.jetsByPt(Cuts::pT > 10*GeV);
for (const Jet& j : jets) {
const double ptB= j.pT();
const double yB= j.rapidity();
if (j.bTagged()) {
if( fabs(yB) < 0.5) { _h_dsigdpty05->fill( ptB, 1.0 );}
else if( fabs(yB) >= 0.5 && fabs(yB) < 1.0) { _h_dsigdpty10->fill( ptB, 1.0 );}
else if( fabs(yB) >= 1.0 && fabs(yB) < 1.5) { _h_dsigdpty15->fill( ptB, 1.0 );}
else if( fabs(yB) >= 1.5 && fabs(yB) < 2.0) { _h_dsigdpty20->fill( ptB, 1.0 );}
else if( fabs(yB) >= 2.0 && fabs(yB) < 2.2) { _h_dsigdpty22->fill( ptB, 1.0 );}
}
}
}
/// Normalise histograms etc., after the run
void finalize() {
double invlumi = crossSection()/picobarn/sumOfWeights();
scale(_h_dsigdpty05, invlumi);
scale(_h_dsigdpty10, invlumi);
scale(_h_dsigdpty15, invlumi);
scale(_h_dsigdpty20, invlumi);
scale(_h_dsigdpty22, invlumi/0.4);
}
/// @}
private:
/// @name Histograms
/// @{
Histo1DPtr _h_dsigdpty05;
Histo1DPtr _h_dsigdpty10;
Histo1DPtr _h_dsigdpty15;
Histo1DPtr _h_dsigdpty20;
Histo1DPtr _h_dsigdpty22;
/// @}
};
RIVET_DECLARE_PLUGIN(CMS_2012_I1089835);
}