Rivet analyses referenceATLAS_2020_I1790256Lund jet plane with charged particlesExperiment: ATLAS (LHC) Inspire ID: 1790256 Status: VALIDATED Authors:
Beam energies: (6500.0, 6500.0) GeV Run details:
The prevalence of hadronic jets at the LHC requires that a deep understanding of jet formation and structure is achieved in order to reach the highest levels of experimental and theoretical precision. There have been many measurements of jet substructure at the LHC and previous colliders, but the targeted observables mix physical effects from various origins. Based on a recent proposal to factorize physical effects, this Letter presents a double-differential cross-section measurement of the Lund jet plane using 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected with the ATLAS detector using jets with transverse momentum above 675 GeV. The measurement uses charged particles to achieve a fine angular resolution and is corrected for acceptance and detector effects. Several parton shower Monte Carlo models are compared with the data. No single model is found to be in agreement with the measured data across the entire plane. Source code: ATLAS_2020_I1790256.cc 1// -*- C++ -*-
2#include "Rivet/Analysis.hh"
3#include "Rivet/Projections/FastJets.hh"
4#include "Rivet/Projections/VetoedFinalState.hh"
5#include "Rivet/Projections/ChargedFinalState.hh"
6#include "fastjet/contrib/LundGenerator.hh"
7
8namespace Rivet {
9
10
11 /// @brief Lund jet plane with charged particles
12 class ATLAS_2020_I1790256: public Analysis {
13 public:
14
15 RIVET_DEFAULT_ANALYSIS_CTOR(ATLAS_2020_I1790256);
16
17
18 /// @name Analysis methods
19 /// @{
20
21 void init() {
22
23 // Projections
24 FinalState fs(Cuts::abseta < 4.5);
25 FastJets jet4(fs, JetAlg::ANTIKT, 0.4, JetMuons::NONE, JetInvisibles::NONE);
26 declare(jet4, "Jets");
27
28 ChargedFinalState tracks(Cuts::pT > 0.5*GeV && Cuts::abseta < 2.5);
29 declare(tracks, "tracks");
30
31 book(_h_lundplane, 1,1,1);
32
33 _h_vs.resize(13);
34 for (size_t i = 0; i < _h_vs.size(); ++i) {
35 book(_h_vs[i] , i+3 , 1, 1);
36 }
37
38 _h_hs.resize(19);
39 for (size_t i = 0; i < _h_hs.size(); ++i) {
40 book(_h_hs[i], i+16, 1, 1);
41 }
42
43 book(_njets, "_njets");
44 }
45
46
47 void analyze(const Event& event) {
48
49 const Jets jets = apply<JetFinder>(event, "Jets").jetsByPt(Cuts::pT > 300*GeV && Cuts::abseta < 2.1);
50
51 if (jets.size() < 2) vetoEvent;
52 if (jets[0].pT() < 675*GeV) vetoEvent;
53
54 if ( (jets[0].pT()/jets[1].pT()) > 1.5 ) vetoEvent;
55
56 _njets->fill(2);
57
58 const Particles& tracks = apply<ChargedFinalState>(event, "tracks").particlesByPt();
59
60 Particles intracks1;
61 Particles intracks2;
62
63 const Jet& j1 = jets[0];
64 const Jet& j2 = jets[1];
65
66
67 for (const Particle& p : tracks) {
68 const double dr = deltaR(j1, p, PSEUDORAPIDITY);
69 if (dr > 0.4) continue;
70 if (abs(p.pid()) == 13) continue;
71 intracks1.push_back(p);
72 }
73
74 for (const Particle& p : tracks) {
75 const double dr = deltaR(j2, p, PSEUDORAPIDITY);
76 if (dr > 0.4) continue;
77 if (abs(p.pid()) == 13) continue;
78 intracks2.push_back(p);
79 }
80
81 JetDefinition tjet1_def(fastjet::cambridge_algorithm, 10);
82 ClusterSequence tjet1_cs(intracks1, tjet1_def);
83 vector<PseudoJet> tjets1 = fastjet::sorted_by_pt(tjet1_cs.inclusive_jets(0.0));
84
85 JetDefinition tjet2_def(fastjet::cambridge_algorithm, 10);
86 ClusterSequence tjet2_cs(intracks2, tjet2_def);
87 vector<PseudoJet> tjets2 = fastjet::sorted_by_pt(tjet2_cs.inclusive_jets(0.0));
88
89 if (tjets1.size() < 1 || tjets2.size() < 1) vetoEvent;
90
91 fjcontrib::LundGenerator lund;
92 vector<fjcontrib::LundDeclustering> declusts1 = lund(tjets1[0]);
93 for (size_t idecl = 0; idecl < declusts1.size(); ++idecl) {
94 pair<double,double> coords = declusts1[idecl].lund_coordinates();
95 double X = -0.9163 + coords.first;
96 double Y = - log(declusts1[idecl].z());
97
98 if (X > 0 && X < 4.33 && Y > log(1/0.5) && Y < 8.6*log(1/0.5) ){
99
100 _h_lundplane->fill(X, Y);
101
102 double hdiv = (double)4.33/(double)13;
103 size_t i = floor(X/hdiv);
104 _h_vs[i]->fill(Y);
105
106 double vdiv = (8.6*log(1/0.5) - log(1/0.5))/(double)19;
107 size_t j = floor((Y - log(1/0.5))/vdiv);
108 _h_hs[j]->fill(X);
109
110 }
111 }
112
113 vector<fjcontrib::LundDeclustering> declusts2 = lund(tjets2[0]);
114 for (size_t idecl = 0; idecl < declusts2.size(); ++idecl) {
115 pair<double,double> coords = declusts2[idecl].lund_coordinates();
116
117 double X = -0.9163 + coords.first;
118 double Y = - log(declusts2[idecl].z());
119
120 if (X > 0 && X < 4.33 && Y > log(1/0.5) && Y < 8.6*log(1/0.5) ) {
121
122 _h_lundplane->fill(X, Y);
123
124 double hdiv = (double)4.33/(double)13;
125 size_t i = floor(X/hdiv);
126 _h_vs[i]->fill(Y);
127
128 double vdiv = (8.6*log(1/0.5) - log(1/0.5))/(double)19;
129 size_t j = floor((Y - log(1/0.5))/vdiv);
130 _h_hs[j]->fill(X);
131 }
132 }
133 }
134
135
136 void finalize() {
137
138 double area = _njets->sumW();
139 if (area > 0) {
140 scale(_h_lundplane, 1/area);
141 scale(_h_vs, 1/(area*0.333));
142 scale(_h_hs, 1/(area*0.277));
143 }
144
145 }
146
147
148 private:
149
150 Histo2DPtr _h_lundplane;
151 vector<Histo1DPtr> _h_vs, _h_hs;
152 CounterPtr _njets;
153
154 };
155
156
157
158 RIVET_DECLARE_PLUGIN(ATLAS_2020_I1790256);
159
160}
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