Rivet analyses
Multijet transverse energy-energy correlations (TEEC) at 8 TeV
Experiment: ATLAS (LHC)
Inspire ID: 1609253
Status: VALIDATED
Authors: - Javier Llorente Merino - Christian Gutschow
References: - Expt page: ATLAS-STDM-2016-10 - submitted to EPJC - arXiv: 1707.02562
Beams: p+ p+
Beam energies: (4000.0, 4000.0)GeV
Run details: - p p -> j j + X at 8 TeV
Measurements of transverse energy-energy correlations and their associated asymmetries in multi-jet events using the ATLAS detector at the LHC are presented. The data used correspond to $\sqrt{s} = 8$ TeV proton-proton collisions with an integrated luminosity of 20.2 fb−1. The results are presented in bins of the scalar sum of the transverse momenta of the two leading jets, unfolded to the particle level and compared to the predictions from Monte Carlo simulations. A comparison with next-to-leading-order perturbative QCD is also performed, showing excellent agreement within the uncertainties. From this comparison, the value of the strong coupling constant is extracted for different energy regimes, thus testing the running of αs(μ) predicted in QCD up to scales over 1 TeV. A global fit to the transverse energy-energy correlation distributions yields αs(mZ) = 0.1162 ± 0.0011(exp.)−0.0070+0.0084(theo.), while a global fit to the asymmetry distributions yields a value of αs(mZ) = 0.1196 ± 0.0013(exp.)−0.0045+0.0075(theo.).
Source
code:ATLAS_2017_I1609253.cc
// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/FinalState.hh"
#include "Rivet/Projections/FastJets.hh"
namespace Rivet {
/// @brief Multijet transverse energy-energy correlations (TEEC) at 8 TeV
class ATLAS_2017_I1609253 : public Analysis {
public:
/// Constructor
RIVET_DEFAULT_ANALYSIS_CTOR(ATLAS_2017_I1609253);
/// Initialization, called once before running
void init() {
// Projections
const FastJets jets(FinalState(), JetAlg::ANTIKT, 0.4, JetMuons::ALL, JetInvisibles::ALL);
declare(jets, "Jets");
// Book histograms
book(_hist_EEC1 , 1, 1, 1);
book(_hist_AEEC1, 2, 1, 1);
book(_hist_EEC2 , 3, 1, 1);
book(_hist_AEEC2, 4, 1, 1);
book(_hist_EEC3 , 5, 1, 1);
book(_hist_AEEC3, 6, 1, 1);
book(_hist_EEC4 , 7, 1, 1);
book(_hist_AEEC4, 8, 1, 1);
book(_hist_EEC5 , 9, 1, 1);
book(_hist_AEEC5, 10, 1, 1);
book(_hist_EEC6 , 11, 1, 1);
book(_hist_AEEC6, 12, 1, 1);
}
void analyze(const Event& event) {
const Jets& jets = apply<FastJets>(event, "Jets").jetsByPt(Cuts::abseta < 2.5 && Cuts::pT > 100*GeV);
if (jets.size() < 2) vetoEvent;
double sumPt12 = jets[0].pt() + jets[1].pt();
if (sumPt12 < 800*GeV) vetoEvent;
double sumEt = 0.;
for (const Jet& j : jets) sumEt += j.Et();
for (const Jet& j1 : jets) {
double et1 = j1.Et();
for (const Jet& j2 : jets) {
double et2 = j2.Et();
double etWeight = et1*et2/(sumEt*sumEt);
double dPhi = deltaPhi(j1, j2);
double cosPhi = cos(dPhi);
if (cos(dPhi) == 1.0) cosPhi = 0.9999;
if (sumPt12 > 800*GeV && sumPt12 <= 850*GeV) _hist_EEC1->fill(cosPhi, etWeight);
if (sumPt12 > 850*GeV && sumPt12 <= 900*GeV) _hist_EEC2->fill(cosPhi, etWeight);
if (sumPt12 > 900*GeV && sumPt12 <= 1000*GeV) _hist_EEC3->fill(cosPhi, etWeight);
if (sumPt12 > 1000*GeV && sumPt12 <= 1100*GeV) _hist_EEC4->fill(cosPhi, etWeight);
if (sumPt12 > 1100*GeV && sumPt12 <= 1400*GeV) _hist_EEC5->fill(cosPhi, etWeight);
if (sumPt12 > 1400*GeV) _hist_EEC6->fill(cosPhi, etWeight);
}
}
}
void finalize() {
normalize(_hist_EEC1);
normalize(_hist_EEC2);
normalize(_hist_EEC3);
normalize(_hist_EEC4);
normalize(_hist_EEC5);
normalize(_hist_EEC6);
vector<Point2D> points1, points2, points3, points4, points5, points6;
size_t nBins = _hist_EEC1->numBins();
for (size_t k = 0; k < nBins/2; ++k) {
double y1 = _hist_EEC1->bin(k+1).sumW() - _hist_EEC1->bin(nBins-k).sumW();
double ey1 = sqrt( sqr(_hist_EEC1->bin(k+1).errW()) + sqr(_hist_EEC1->bin(nBins-k).errW()) );
_hist_AEEC1->bin(k+1).set(y1/_hist_AEEC1->bin(k+1).xWidth(),ey1/_hist_AEEC1->bin(k+1).xWidth());
double y2 = _hist_EEC2->bin(k+1).sumW() - _hist_EEC2->bin(nBins-k).sumW();
double ey2 = sqrt( sqr(_hist_EEC2->bin(k+1).errW()) + sqr(_hist_EEC2->bin(nBins-k).errW()) );
_hist_AEEC2->bin(k+1).set(y2/_hist_AEEC2->bin(k+1).xWidth(),ey2/_hist_AEEC2->bin(k+1).xWidth());
double y3 = _hist_EEC3->bin(k+1).sumW() - _hist_EEC3->bin(nBins-k).sumW();
double ey3 = sqrt( sqr(_hist_EEC3->bin(k+1).errW()) + sqr(_hist_EEC3->bin(nBins-k).errW()) );
_hist_AEEC3->bin(k+1).set(y3/_hist_AEEC3->bin(k+1).xWidth(),ey3/_hist_AEEC3->bin(k+1).xWidth());
double y4 = _hist_EEC4->bin(k+1).sumW() - _hist_EEC4->bin(nBins-k).sumW();
double ey4 = sqrt( sqr(_hist_EEC4->bin(k+1).errW()) + sqr(_hist_EEC4->bin(nBins-k).errW()) );
_hist_AEEC4->bin(k+1).set(y4/_hist_AEEC4->bin(k+1).xWidth(),ey4/_hist_AEEC4->bin(k+1).xWidth());
double y5 = _hist_EEC5->bin(k+1).sumW() - _hist_EEC5->bin(nBins-k).sumW();
double ey5 = sqrt( sqr(_hist_EEC5->bin(k+1).errW()) + sqr(_hist_EEC5->bin(nBins-k).errW()) );
_hist_AEEC5->bin(k+1).set(y5/_hist_AEEC5->bin(k+1).xWidth(),ey5/_hist_AEEC5->bin(k+1).xWidth());
double y6 = _hist_EEC6->bin(k+1).sumW() - _hist_EEC6->bin(nBins-k).sumW();
double ey6 = sqrt( sqr(_hist_EEC6->bin(k+1).errW()) + sqr(_hist_EEC6->bin(nBins-k).errW()) );
_hist_AEEC6->bin(k+1).set(y6/_hist_AEEC6->bin(k+1).xWidth(),ey6/_hist_AEEC6->bin(k+1).xWidth());
}
}
private:
Histo1DPtr _hist_EEC1, _hist_EEC2, _hist_EEC3, _hist_EEC4, _hist_EEC5, _hist_EEC6;
Estimate1DPtr _hist_AEEC1, _hist_AEEC2, _hist_AEEC3, _hist_AEEC4, _hist_AEEC5, _hist_AEEC6;
};
RIVET_DECLARE_PLUGIN(ATLAS_2017_I1609253);
}