Rivet analyses referenceATLAS_2017_I1609448$p_\text{T}^\text{miss}$+jets cross-section ratios at 13 TeVExperiment: ATLAS (LHC) Inspire ID: 1609448 Status: VALIDATED Authors:
Beam energies: (6500.0, 6500.0) GeV Run details:
Observables sensitive to the anomalous production of events containing hadronic jets and missing momentum in the plane transverse to the proton beams at the Large Hadron Collider are presented. The observables are defined as a ratio of cross sections, for events containing jets and large missing transverse momentum to events containing jets and a pair of charged leptons from the decay of a $Z/\gamma^\ast$ boson. This definition minimises experimental and theoretical systematic uncertainties in the measurements. This ratio is measured differentially with respect to a number of kinematic properties of the hadronic system in two phase-space regions; one inclusive single-jet region and one region sensitive to vector-boson-fusion topologies. The data are found to be in agreement with the Standard Model predictions and used to constrain a variety of theoretical models for dark-matter production, including simplified models, effective field theory models, and invisible decays of the Higgs boson. The measurements use 3.2 fb${}^{-1}$ of proton-proton collision data recorded by the ATLAS experiment at a centre-of-mass energy of 13 TeV and are fully corrected for detector effects, meaning that the data can be used to constrain new-physics models beyond those shown in this paper. The reference data file comes with the measured $R^\text{miss}$ (y01), the expected $R^\text{miss}$ in the Standard Model (y02), the expected $R^\text{miss}$ numerator in the Standard Model (y03) as well as the expected $R^\text{miss}$ denominator in the Standard Model (y04). If no mode is specified, will assume routine is being run on BSM model and attempt to combine with SM prediction from ref data file. If NU is specified will assume SM $Z\to\nu\nu$ is being run on. If EL or MU is specified, will assume routine is run on SM $Z\to ee$ or $Z\to\mu\mu$ respectively. Note on reinterpretation: If a BSM signal is due to an excess of Z bosons, it should appear both numerator and denominator and so the ratio should have zero sensitivity. This will be wrongly evaluated if the SM denominator mode is used. Source code: ATLAS_2017_I1609448.cc 1// -*- C++ -*-
2#include "Rivet/Analysis.hh"
3#include "Rivet/Projections/FastJets.hh"
4#include "Rivet/Projections/FinalState.hh"
5#include "Rivet/Projections/LeptonFinder.hh"
6#include "Rivet/Projections/VetoedFinalState.hh"
7#include "Rivet/Projections/PromptFinalState.hh"
8#include "Rivet/Projections/MissingMomentum.hh"
9
10namespace Rivet {
11
12
13 /// ATLAS pTmiss+jets cross-section ratios at 13 TeV
14 class ATLAS_2017_I1609448 : public Analysis {
15 public:
16
17 /// Constructor
18 RIVET_DEFAULT_ANALYSIS_CTOR(ATLAS_2017_I1609448);
19
20
21 struct HistoHandler {
22 Histo1DPtr histo;
23 Estimate1DPtr estimate;
24 unsigned int d, x, y;
25
26 void fill(double value) {
27 histo->fill(value);
28 }
29 };
30
31
32 /// Initialize
33 void init() {
34
35 // Get options from the new option system
36 _mode = 0;
37 if ( getOption("LMODE") == "NU" ) _mode = 0; // using Z -> nunu channel by default
38 if ( getOption("LMODE") == "MU" ) _mode = 1;
39 if ( getOption("LMODE") == "EL" ) _mode = 2;
40
41 // Prompt photons
42 PromptFinalState photon_fs(Cuts::abspid == PID::PHOTON && Cuts::abseta < 4.9);
43 // Prompt electrons
44 PromptFinalState el_fs(Cuts::abseta < 4.9 && Cuts::abspid == PID::ELECTRON);
45 // Prompt muons
46 PromptFinalState mu_fs(Cuts::abseta < 4.9 && Cuts::abspid == PID::MUON);
47
48 // Dressed leptons
49 Cut lep_cuts = Cuts::pT > 7*GeV && Cuts::abseta < 2.5;
50 LeptonFinder dressed_leps((_mode == 2 ? el_fs : mu_fs), photon_fs, 0.1, lep_cuts);
51 declare(dressed_leps, "LeptonFinder");
52
53 // In-acceptance leptons for lepton veto
54 PromptFinalState veto_lep_fs(Cuts::abseta < 4.9 && (Cuts::abspid == PID::ELECTRON || Cuts::abspid == PID::MUON));
55 veto_lep_fs.acceptTauDecays();
56 veto_lep_fs.acceptMuonDecays();
57 LeptonFinder veto_lep(veto_lep_fs, photon_fs, 0.1, lep_cuts);
58 declare(veto_lep, "VetoLeptons");
59
60 // MET
61 VetoedFinalState met_fs(Cuts::abseta > 2.5 && Cuts::abspid == PID::MUON); // veto out-of-acceptance muons
62 if (_mode) met_fs.addVetoOnThisFinalState(dressed_leps);
63 declare(MissingMomentum(met_fs), "MET");
64
65 // Jet collection
66 FastJets jets(FinalState(Cuts::abseta < 4.9), JetAlg::ANTIKT, 0.4, JetMuons::NONE, JetInvisibles::NONE);
67 declare(jets, "Jets");
68
69 _h["met_mono"] = bookHandler(1, 1, 2);
70 _h["met_vbf" ] = bookHandler(2, 1, 2);
71 _h["mjj_vbf" ] = bookHandler(3, 1, 2);
72 _h["dphijj_vbf"] = bookHandler(4, 1, 2);
73 }
74
75
76 HistoHandler bookHandler(unsigned int id_d, unsigned int id_x, unsigned int id_y) {
77 HistoHandler dummy;
78 if (_mode < 2) { // numerator mode
79 const string histName = "_" + mkAxisCode(id_d, id_x, id_y);
80 book(dummy.histo, histName, refData(id_d, id_x, id_y)); // hidden auxiliary output
81 book(dummy.estimate, id_d, id_x, id_y - 1); // ratio
82 dummy.d = id_d;
83 dummy.x = id_x;
84 dummy.y = id_y;
85 } else {
86 book(dummy.histo, id_d, id_x, 4); // denominator mode
87 }
88 return dummy;
89 }
90
91
92 bool isBetweenJets(const Jet& probe, const Jet& boundary1, const Jet& boundary2) {
93 const double y_p = probe.rapidity();
94 const double y_b1 = boundary1.rapidity();
95 const double y_b2 = boundary2.rapidity();
96 const double y_min = std::min(y_b1, y_b2);
97 const double y_max = std::max(y_b1, y_b2);
98 return (y_p > y_min && y_p < y_max);
99 }
100
101
102 int centralJetVeto(Jets& jets) {
103 if (jets.size() < 2) return 0;
104 const Jet bj1 = jets.at(0);
105 const Jet bj2 = jets.at(1);
106
107 // Start loop at the 3rd hardest pT jet
108 int n_between = 0;
109 for (size_t i = 2; i < jets.size(); ++i) {
110 const Jet j = jets.at(i);
111 if (isBetweenJets(j, bj1, bj2) && j.pT() > 25*GeV) ++n_between;
112 }
113 return n_between;
114 }
115
116
117 /// Perform the per-event analysis
118 void analyze(const Event& event) {
119
120 // Require 0 (Znunu) or 2 (Zll) dressed leptons
121 bool isZll = bool(_mode);
122 const DressedLeptons &vetoLeptons = apply<LeptonFinder>(event, "VetoLeptons").dressedLeptons();
123 const DressedLeptons &all_leps = apply<LeptonFinder>(event, "LeptonFinder").dressedLeptons();
124 if (!isZll && vetoLeptons.size()) vetoEvent;
125 if ( isZll && all_leps.size() != 2) vetoEvent;
126
127 DressedLeptons leptons;
128 bool pass_Zll = true;
129 if (isZll) {
130 // Sort dressed leptons by pT
131 if (all_leps[0].pt() > all_leps[1].pt()) {
132 leptons.push_back(all_leps[0]);
133 leptons.push_back(all_leps[1]);
134 } else {
135 leptons.push_back(all_leps[1]);
136 leptons.push_back(all_leps[0]);
137 }
138 // Leading lepton pT cut
139 pass_Zll &= leptons[0].pT() > 80*GeV;
140 // Opposite-charge requirement
141 pass_Zll &= charge3(leptons[0]) + charge3(leptons[1]) == 0;
142 // Z-mass requirement
143 const double Zmass = (leptons[0].mom() + leptons[1].mom()).mass();
144 pass_Zll &= (Zmass >= 66*GeV && Zmass <= 116*GeV);
145 }
146 if (!pass_Zll) vetoEvent;
147
148
149 // Get jets and remove those within dR = 0.5 of a dressed lepton
150 Jets jets = apply<FastJets>(event, "Jets").jetsByPt(Cuts::pT > 25*GeV && Cuts::absrap < 4.4);
151 for (const DressedLepton& lep : leptons)
152 idiscard(jets, deltaRLess(lep, 0.5));
153
154 const size_t njets = jets.size();
155 if (!njets) vetoEvent;
156 const int njets_gap = centralJetVeto(jets);
157
158 double jpt1 = jets[0].pT();
159 double jeta1 = jets[0].eta();
160 double mjj = 0., jpt2 = 0., dphijj = 0.;
161 if (njets >= 2) {
162 mjj = (jets[0].momentum() + jets[1].momentum()).mass();
163 jpt2 = jets[1].pT();
164 dphijj = deltaPhi(jets[0], jets[1]);
165 }
166
167 // MET
168 Vector3 met_vec = apply<MissingMomentum>(event, "MET").vectorMPT();
169 double met = met_vec.mod();
170
171 // Cut on deltaPhi between MET and first 4 jets, but only if jet pT > 30 GeV
172 bool dphi_fail = false;
173 for (size_t i = 0; i < jets.size() && i < 4; ++i) {
174 dphi_fail |= (deltaPhi(jets[i], met_vec) < 0.4 && jets[i].pT() > 30*GeV);
175 }
176
177 const bool pass_met_dphi = met > 200*GeV && !dphi_fail;
178 const bool pass_vbf = pass_met_dphi && mjj > 200*GeV && jpt1 > 80*GeV && jpt2 > 50*GeV && njets >= 2 && !njets_gap;
179 const bool pass_mono = pass_met_dphi && jpt1 > 120*GeV && fabs(jeta1) < 2.4;
180 if (pass_mono) _h["met_mono"].fill(met);
181 if (pass_vbf) {
182 _h["met_vbf"].fill(met/GeV);
183 _h["mjj_vbf"].fill(mjj/GeV);
184 _h["dphijj_vbf"].fill(dphijj);
185 }
186 }
187
188
189 /// Normalise, scale and otherwise manipulate histograms here
190 void finalize() {
191 const double sf(crossSection() / femtobarn / sumOfWeights());
192 for (auto& item : _h) {
193 scale(item.second.histo, sf);
194 if (_mode < 2) constructRmiss(item.second);
195 }
196 }
197
198
199 void constructRmiss(HistoHandler& handler) {
200 // Load transfer function from reference data file
201 const YODA::Estimate1D& rmiss = refData(handler.d, handler.x, handler.y);
202 const YODA::Estimate1D& numer = refData(handler.d, handler.x, handler.y + 1);
203 const YODA::Estimate1D& denom = refData(handler.d, handler.x, handler.y + 2);
204 const YODA::Estimate1D& bsm = handler.histo->mkEstimate();
205 for (size_t i = 1; i < handler.estimate->numBins()+1; ++i) {
206 const auto& r = rmiss.bin(i); // SM Rmiss
207 const auto& n = numer.bin(i); // SM numerator
208 const auto& d = denom.bin(i); // SM denominator
209 const auto& b = bsm.bin(i); // BSM
210 // Rmiss central value
211 const double rmiss_y = safediv(n.val() + b.val(), d.val());
212 // Ratio error (Rmiss = SM_num/SM_denom + BSM/SM_denom ~ Rmiss_SM + BSM/SM_denom
213 const double rmiss_p = sqrt(sqr(r.totalErrPos()) + safediv(sqr(b.val()? b.totalErrPos() : 0.), sqr(d.val())));
214 const double rmiss_m = sqrt(sqr(r.totalErrNeg()) + safediv(sqr(b.val()? b.totalErrNeg() : 0.), sqr(d.val())));
215 // Set new values
216 handler.estimate->bin(i).set(rmiss_y, {-rmiss_m, rmiss_p});
217 }
218 }
219
220
221 protected:
222
223 // Analysis-mode switch
224 size_t _mode;
225
226 /// Histograms
227 map<string, HistoHandler> _h;
228
229 };
230
231
232 RIVET_DECLARE_PLUGIN(ATLAS_2017_I1609448);
233}
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