Rivet analyses
Soft-Drop Jet Mass at 13 TeV
Experiment: ATLAS (LHC)
Inspire ID: 1637587
Status: VALIDATED
Authors: - Ben Nachman - Jennifer Roloff
References: - Expt page: ATLAS-STDM-2017-04 - Phys.Rev.Lett. 121 (2018) no.9, 092001 - DOI: 10.1103/PhysRevLett.121.092001 - arXiv: 1711.08341
Beams: p+ p+
Beam energies: (6500.0, 6500.0)GeV
Run details: - p p -> j j at 13 TeV
Jet substructure observables have significantly extended the search program for physics beyond the standard model at the Large Hadron Collider. The state-of-the-art tools have been motivated by theoretical calculations, but there has never been a direct comparison between data and calculations of jet substructure observables that are accurate beyond leading-logarithm approximation. Such observables are significant not only for probing the collinear regime of QCD that is largely unexplored at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider. This Letter documents a measurement of the first jet substructure quantity at a hadron collider to be calculated at next-to-next-to-leading-logarithm accuracy. The normalized, differential cross section is measured as a function of log10ρ2, where ρ is the ratio of the soft-drop mass to the ungroomed jet transverse momentum. This quantity is measured in dijet events from 32.9fb−1 of $\sqrt{s} = 13$ TeV proton-proton collisions recorded by the ATLAS detector. The data are unfolded to correct for detector effects and compared to precise QCD calculations and leading-logarithm particle-level Monte Carlo simulations.
Source
code:ATLAS_2017_I1637587.cc
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/FinalState.hh"
#include "Rivet/Projections/FastJets.hh"
#include "fastjet/contrib/SoftDrop.hh"
namespace Rivet {
/// @brief Soft drop mass at 13 TeV
class ATLAS_2017_I1637587: public Analysis {
public:
/// Constructor
RIVET_DEFAULT_ANALYSIS_CTOR(ATLAS_2017_I1637587);
/// Book cuts and projections
void init() {
// All final state particles
const FinalState fs(Cuts::abseta < 5.0);
FastJets jets(fs, JetAlg::ANTIKT, 0.8, JetMuons::NONE, JetInvisibles::NONE);
declare(jets, "jets");
book(_h_Table1, 1,1,1);
book(_h_Table2, 2,1,1);
book(_h_Table3, 3,1,1);
book(_h_Table4, 4,1,1);
book(_h_Table5, 5,1,1);
book(_h_Table6, 6,1,1);
betas = { 0., 1., 2. };
ptBins = { 600, 650, 700, 750, 800, 850, 900, 950, 1000, 2000 };
rhoBins = { -4.5, -4.1, -3.7, -3.3, -2.9, -2.5, -2.1, -1.7, -1.3, -0.9, -0.5 };
}
void analyze(const Event& event) {
const Jets& myJets = apply<FastJets>(event, "jets").jetsByPt(Cuts::pT > 400*GeV);
if (myJets.size() < 2) vetoEvent;
if (myJets[0].pT() > 1.5*myJets[1].pT()) vetoEvent;
if (myJets[0].abseta() > 1.5 || myJets[1].abseta() > 1.5) vetoEvent;
for (size_t i = 0; i < 2; ++i) {
if (myJets[i].pT() < 600*GeV) continue;
ClusterSequence cs_ca(myJets[i].constituents(), JetDefinition(fastjet::cambridge_algorithm, 0.8));
PseudoJets myJet_ca = sorted_by_pt(cs_ca.inclusive_jets(400.0));
if(myJet_ca.size()==0) continue;
for (size_t ibeta = 0; ibeta < 3; ++ibeta) {
fastjet::contrib::SoftDrop sd(betas[ibeta], 0.1); //beta, zcut
PseudoJet sdJet = sd(myJet_ca[0]);
double rho2 = pow(sdJet.m()/myJets[i].pT(),2);
double log10rho2 = log(rho2)/log(10.);
if (log10rho2 < -4.5) continue;
if (ibeta==0) _h_Table1->fill(log10rho2);
if (ibeta==1) _h_Table2->fill(log10rho2);
if (ibeta==2) _h_Table3->fill(log10rho2);
if (ibeta==0) _h_Table4->fill(return_bin(rho2, myJets[i].pT()));
if (ibeta==1) _h_Table5->fill(return_bin(rho2, myJets[i].pT()));
if (ibeta==2) _h_Table6->fill(return_bin(rho2, myJets[i].pT()));
}
}
}
void finalize() {
//Normalization comes here.
double norm0 = 0.;
double norm1 = 0.;
double norm2 = 0.;
for (size_t i = 4; i <= 7; ++i) { //only normalize in the resummation region.
norm0 += _h_Table1->bin(i+1).sumW()/_h_Table1->bin(i+1).dVol();
norm1 += _h_Table2->bin(i+1).sumW()/_h_Table2->bin(i+1).dVol();
norm2 += _h_Table3->bin(i+1).sumW()/_h_Table3->bin(i+1).dVol();
}
if (norm0 != 0) {
_h_Table1->scaleW(1.0/norm0);
} else {
MSG_WARNING("Zero entries, cannot normalise Table 1");
}
if (norm1 != 0) {
_h_Table2->scaleW(1.0/norm1);
} else {
MSG_WARNING("Zero entries, cannot normalise Table 2");
}
if (norm2 != 0) {
_h_Table3->scaleW(1.0/norm2);
} else {
MSG_WARNING("Zero entries, cannot normalise Table 3");
}
ptNorm( _h_Table4 );
ptNorm( _h_Table5 );
ptNorm( _h_Table6 );
}
void ptNorm(Histo1DPtr ptBinnedHist) {
for (size_t k = 0; k < 9; ++k){
double normalization = 0;
for (size_t j = 4; j <= 7; ++j) {
double height = ptBinnedHist->bin(k*10 + j+1).sumW();
height /= ptBinnedHist->bin(k*10 + j+1).dVol();
normalization += height;
}
if( normalization == 0 ) continue;
for (size_t j = 0; j < 10; ++j) {
ptBinnedHist->bin(k*10 + j+1).scaleW(1. / normalization);
}
}
return;
}
size_t return_bin(double rho, double pT){
if (pT < 600.) return -1;
if (rho < pow(10,-4.5)) return -1;
size_t pTbin = 1;
if (pT < 600) pTbin = 0; //should not happen
else if (pT < 650) pTbin = 1;
else if (pT < 700) pTbin = 2;
else if (pT < 750) pTbin = 3;
else if (pT < 800) pTbin = 4;
else if (pT < 850) pTbin = 5;
else if (pT < 900) pTbin = 6;
else if (pT < 950) pTbin = 7;
else if (pT < 1000) pTbin = 8;
else pTbin = 9;
size_t rhobin = 1;
if (rho < pow(10,-4.5)) rhobin = 0; //this should not happen.
else if (rho < pow(10,-4.1)) rhobin = 1;
else if (rho < pow(10,-3.7)) rhobin = 2;
else if (rho < pow(10,-3.3)) rhobin = 3;
else if (rho < pow(10,-2.9)) rhobin = 4;
else if (rho < pow(10,-2.5)) rhobin = 5;
else if (rho < pow(10,-2.1)) rhobin = 6;
else if (rho < pow(10,-1.7)) rhobin = 7;
else if (rho < pow(10,-1.3)) rhobin = 8;
else if (rho < pow(10,-0.9)) rhobin = 9;
else if (rho < pow(10,-0.5)) rhobin = 10;
else rhobin = 10;
return (rhobin-1) + (pTbin-1)*10;
}
private:
/// Histograms
Histo1DPtr _h_Table1, _h_Table2, _h_Table3, _h_Table4, _h_Table5, _h_Table6;
vector<double> betas, ptBins, rhoBins;
};
RIVET_DECLARE_PLUGIN(ATLAS_2017_I1637587);
}