Rivet analyses

title: CMS_2014_I1298810

Ratios of jet pT spectra, which relate to the ratios of inclusive, differential jet cross sections

Experiment: CMS (LHC)

Inspire ID: 1298810

Status: VALIDATED

Authors: - Markus Radziej

References: - arXiv: 1406.0324 - Expt page: CMS-SMP-13-002 - CERN-PH-EP-2014-068 - Accepted by Phys. Rev. D

Beams: p+ p+

Beam energies: (3500.0, 3500.0)GeV

Run details: - Hard QCD events with $\hat{p}{\text{T}} > 40\,\text{GeV}$ at $\sqrt{s} = 7\,\text{TeV}$. Either a $\hat{p}{\text{T}}$-binned approach or a 'flat' spectrum is recommended, to generate sufficient events in the high $p_{\text{T}}$ region.

Ratios of jet transverse momentum spectra. The jets objects are defined using the anti-$k_{\text{T}}$ algorithm with radii of R = 0.5 and R = 0.7. The ratios are given for six 0.5 wide rapidity regions ranging from 0.0 to 3.0 and relate the ratio of inclusive, differential jet cross sections.

Source code:CMS_2014_I1298810.cc

```c++ // -- C++ --

include "Rivet/Analysis.hh"

include "Rivet/Projections/FastJets.hh"

include "Rivet/Projections/FinalState.hh"

namespace Rivet {

/// Ratios of jet pT spectra, related to ratios of differential jet cross sections class CMS_2014_I1298810 : public Analysis { public:

/// Constructor
CMS_2014_I1298810()
    : Analysis("CMS_2014_I1298810") { }


/// @name Analysis methods
/// @{

void init() {
  // Projections
  FastJets jetsak5(FinalState(), JetAlg::ANTIKT, 0.5);
  declare(jetsak5, "JetsAK5");
  FastJets jetsak7(FinalState(), JetAlg::ANTIKT, 0.7);
  declare(jetsak7, "JetsAK7");

  // Histograms
  book(_h_pt_05_ak5, 1, 1, 1);
  book(_h_pt_05_10_ak5, 2, 1, 1);
  book(_h_pt_10_15_ak5, 3, 1, 1);
  book(_h_pt_15_20_ak5, 4, 1, 1);
  book(_h_pt_20_25_ak5, 5, 1, 1);
  book(_h_pt_25_30_ak5, 6, 1, 1);

  book(_h_pt_05_ak7, 7, 1, 1);
  book(_h_pt_05_10_ak7, 8, 1, 1);
  book(_h_pt_10_15_ak7, 9, 1, 1);
  book(_h_pt_15_20_ak7, 10, 1, 1);
  book(_h_pt_20_25_ak7, 11, 1, 1);
  book(_h_pt_25_30_ak7, 12, 1, 1);

  book(_h_pt_05_ratio, 13, 1, 1);
  book(_h_pt_05_10_ratio, 14, 1, 1);
  book(_h_pt_10_15_ratio, 15, 1, 1);
  book(_h_pt_15_20_ratio, 16, 1, 1);
  book(_h_pt_20_25_ratio, 17, 1, 1);
  book(_h_pt_25_30_ratio, 18, 1, 1);
}


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

  const Jets& jetsak5 = apply<FastJets>(event, "JetsAK5").jetsByPt(Cuts::pT > 56 * GeV);
  const Jets& jetsak7 = apply<FastJets>(event, "JetsAK7").jetsByPt(Cuts::pT > 56 * GeV);
  if (jetsak5.size() < 1 && jetsak7.size() < 1) vetoEvent;


  // Filling R = 0.5 jets
  for (const Jet& jet : jetsak5) {
    if (jet.absrapidity() < 0.5) {
      _h_pt_05_ak5->fill(jet.pT() / GeV);
    }
    else if (jet.absrapidity() < 1.0) {
      _h_pt_05_10_ak5->fill(jet.pT() / GeV);
    }
    else if (jet.absrapidity() < 1.5) {
      _h_pt_10_15_ak5->fill(jet.pT() / GeV);
    }
    else if (jet.absrapidity() < 2.0) {
      _h_pt_15_20_ak5->fill(jet.pT() / GeV);
    }
    else if (jet.absrapidity() < 2.5) {
      _h_pt_20_25_ak5->fill(jet.pT() / GeV);
    }
    else if (jet.absrapidity() < 3.0) {
      _h_pt_25_30_ak5->fill(jet.pT() / GeV);
    }
  }


  // Filling R = 0.7 jets
  for (const Jet& jet : jetsak7) {
    if (jet.absrapidity() < 0.5) {
      _h_pt_05_ak7->fill(jet.pT() * GeV);
    }
    else if (jet.absrapidity() < 1.0) {
      _h_pt_05_10_ak7->fill(jet.pT() * GeV);
    }
    else if (jet.absrapidity() < 1.5) {
      _h_pt_10_15_ak7->fill(jet.pT() * GeV);
    }
    else if (jet.absrapidity() < 2.0) {
      _h_pt_15_20_ak7->fill(jet.pT() * GeV);
    }
    else if (jet.absrapidity() < 2.5) {
      _h_pt_20_25_ak7->fill(jet.pT() * GeV);
    }
    else if (jet.absrapidity() < 3.0) {
      _h_pt_25_30_ak7->fill(jet.pT() * GeV);
    }
  }
}


/// Normalise histograms etc., after the run
void finalize() {
  scale(_h_pt_05_ak5, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_05_10_ak5, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_10_15_ak5, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_15_20_ak5, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_20_25_ak5, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_25_30_ak5, crossSection() / picobarn / sumOfWeights());

  scale(_h_pt_05_ak7, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_05_10_ak7, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_10_15_ak7, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_15_20_ak7, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_20_25_ak7, crossSection() / picobarn / sumOfWeights());
  scale(_h_pt_25_30_ak7, crossSection() / picobarn / sumOfWeights());

  divide(_h_pt_05_ak5, _h_pt_05_ak7, _h_pt_05_ratio);
  divide(_h_pt_05_10_ak5, _h_pt_05_10_ak7, _h_pt_05_10_ratio);
  divide(_h_pt_10_15_ak5, _h_pt_10_15_ak7, _h_pt_10_15_ratio);
  divide(_h_pt_15_20_ak5, _h_pt_15_20_ak7, _h_pt_15_20_ratio);
  divide(_h_pt_20_25_ak5, _h_pt_20_25_ak7, _h_pt_20_25_ratio);
  divide(_h_pt_25_30_ak5, _h_pt_25_30_ak7, _h_pt_25_30_ratio);
}

/// @}

private:

/// @name Histograms
/// @{
Histo1DPtr _h_pt_05_ak5, _h_pt_05_10_ak5, _h_pt_10_15_ak5, _h_pt_15_20_ak5, _h_pt_20_25_ak5,
    _h_pt_25_30_ak5;
Histo1DPtr _h_pt_05_ak7, _h_pt_05_10_ak7, _h_pt_10_15_ak7, _h_pt_15_20_ak7, _h_pt_20_25_ak7,
    _h_pt_25_30_ak7;
Estimate1DPtr _h_pt_05_ratio, _h_pt_05_10_ratio, _h_pt_10_15_ratio, _h_pt_15_20_ratio, _h_pt_20_25_ratio,
    _h_pt_25_30_ratio;
/// @}

};

RIVET_DECLARE_PLUGIN(CMS_2014_I1298810);

} ```