CMS logoCMS event Hgg
Compact Muon Solenoid
LHC, CERN

CMS-B2G-22-005 ; CERN-EP-2024-266
Search for pair production of heavy particles decaying to a top quark and a gluon in the lepton+jets final state in proton-proton collisions at $ \sqrt{s}= $ 13 TeV
Accepted for publication in Eur. Phys. J. C
Abstract: A search is presented for the pair production of new heavy resonances, each decaying into a top quark (t) or antiquark and a gluon ($ \mathrm{g} $). The analysis uses data recorded with the CMS detector from proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. Events with one muon or electron, multiple jets, and missing transverse momentum are selected. After using a deep neural network to enrich the data sample with signal-like events, distributions in the scalar sum of the transverse momenta of all reconstructed objects are analyzed in the search for a signal. No significant deviations from the standard model prediction are found. Upper limits at 95% confidence level are set on the product of cross section and branching fraction squared for the pair production of excited top quarks in the $ \mathrm{t}^{*} \to \mathrm{t}\mathrm{g} $ decay channel. The upper limits range from 0.12 pb to 0.8 fb for a $\mathrm{t}^{*}$ with spin-1/2 and from 0.015 pb to 1.0 fb for a $\mathrm{t}^{*}$ with spin-3/2. These correspond to mass exclusion limits up to 1050 and 1700 GeV for spin-1/2 and spin-3/2 $\mathrm{t}^{*}$ particles, respectively. These are the most stringent limits to date on the existence of $ \mathrm{t}^{*} \to \mathrm{t}\mathrm{g} $ resonances.
Figures Summary References CMS Publications
Figures

png pdf
Figure 1:
Representative Feynman diagram of the signal process at leading order.

png pdf
Figure 2:
Distributions in $ S_{\text{T}} $ for $ \mathrm{t}^{*} \overline{\mathrm{t}}{}^{*} $ signal samples with different simulated values of $ m_{\mathrm{t}^{*} } $, for spin-1/2 (solid lines) and spin-3/2 (dashed lines) resonances. The distributions were normalized to the same area for each signal.

png pdf
Figure 3:
Two-dimensional distribution in 1 $ - s_{\text{DNN}} $ versus $ S_{\text{T}} $ for simulated $ \mathrm{t} \overline{\mathrm{t}} $ events. The function $ f(S_{\text{T}}, 30%) $ (red line) is determined by specifying a 30% selection efficiency for $ \mathrm{t} \overline{\mathrm{t}} $ events, i.e.,, 30% of the $ \mathrm{t} \overline{\mathrm{t}} $ events are below this function in each bin of $ S_{\text{T}} $.

png pdf
Figure 4:
The simulation-based ratios between the $ S_{\text{T}} $ distributions in the SRs and CRs for the muon (left) and electron (right) channels. Two functions are fit to each ratio, and the final transfer function used for the non-t background estimation is taken to be their average. The statistical uncertainties in the transfer functions are shown as grey bands. In the lower panels, the simulation-based ratios, fit functions, and statistical uncertainties are shown relative to the final transfer function.

png pdf
Figure 4-a:
The simulation-based ratios between the $ S_{\text{T}} $ distributions in the SRs and CRs for the muon (left) and electron (right) channels. Two functions are fit to each ratio, and the final transfer function used for the non-t background estimation is taken to be their average. The statistical uncertainties in the transfer functions are shown as grey bands. In the lower panels, the simulation-based ratios, fit functions, and statistical uncertainties are shown relative to the final transfer function.

png pdf
Figure 4-b:
The simulation-based ratios between the $ S_{\text{T}} $ distributions in the SRs and CRs for the muon (left) and electron (right) channels. Two functions are fit to each ratio, and the final transfer function used for the non-t background estimation is taken to be their average. The statistical uncertainties in the transfer functions are shown as grey bands. In the lower panels, the simulation-based ratios, fit functions, and statistical uncertainties are shown relative to the final transfer function.

png pdf
Figure 5:
Distributions of $ S_{\text{T}} $ in the VR for the muon (left) and electron (right) channels. The total uncertainties are shown as hatched bands. The signal distributions are scaled to the cross sections predicted by theory. Ratios of data to the expected backgrounds are shown in the lower panels.

png pdf
Figure 5-a:
Distributions of $ S_{\text{T}} $ in the VR for the muon (left) and electron (right) channels. The total uncertainties are shown as hatched bands. The signal distributions are scaled to the cross sections predicted by theory. Ratios of data to the expected backgrounds are shown in the lower panels.

png pdf
Figure 5-b:
Distributions of $ S_{\text{T}} $ in the VR for the muon (left) and electron (right) channels. The total uncertainties are shown as hatched bands. The signal distributions are scaled to the cross sections predicted by theory. Ratios of data to the expected backgrounds are shown in the lower panels.

png pdf
Figure 6:
Distributions in $ S_{\text{T}} $ in the SR for the muon (left) and electron (right) channels, after a background-only fit to the data. The signal distributions are scaled to the cross section predicted by the theory. The hatched bands show the post-fit uncertainty band, combining all sources of uncertainty. The ratio of data to the background predictions is shown in the panels below the distributions.

png pdf
Figure 6-a:
Distributions in $ S_{\text{T}} $ in the SR for the muon (left) and electron (right) channels, after a background-only fit to the data. The signal distributions are scaled to the cross section predicted by the theory. The hatched bands show the post-fit uncertainty band, combining all sources of uncertainty. The ratio of data to the background predictions is shown in the panels below the distributions.

png pdf
Figure 6-b:
Distributions in $ S_{\text{T}} $ in the SR for the muon (left) and electron (right) channels, after a background-only fit to the data. The signal distributions are scaled to the cross section predicted by the theory. The hatched bands show the post-fit uncertainty band, combining all sources of uncertainty. The ratio of data to the background predictions is shown in the panels below the distributions.

png pdf
Figure 7:
Expected and observed 95% CL upper limits on the product of the $ \mathrm{t}^{*} \overline{\mathrm{t}}{}^{*} $ production cross section and the branching fraction squared $ \mathcal{B}^2(\mathrm{t}^{*} \to \mathrm{t}\mathrm{g}) $ for a spin-1/2 $\mathrm{t}^{*}$ as a function of $ m_{\mathrm{t}^{*} } $. The inner (green) and outer (yellow) bands give the central probability intervals containing 68 and 95% of the expected upper limits under the background-only hypothesis. The cross section predicted by theory, following the EFT approach introduced in Ref. [26], is shown as a dotted line, assuming $ \mathcal{B}(\mathrm{t}^{*} \to \mathrm{t}\mathrm{g})= $ 1.

png pdf
Figure 8:
Expected and observed 95% CL upper limits on the product of the $ \mathrm{t}^{*} \overline{\mathrm{t}}{}^{*} $ production cross section and the branching fraction squared $ \mathcal{B}^2(\mathrm{t}^{*} \to \mathrm{t}\mathrm{g}) $ for a spin-3/2 $\mathrm{t}^{*}$ as a function of $ m_{\mathrm{t}^{*} } $. The inner (green) and outer (yellow) bands give the central probability intervals containing 68 and 95% of the expected upper limits under the background-only hypothesis. The cross section predicted by theory, following the EFT approach introduced in Ref. [26], is shown as a dotted line, assuming $ \mathcal{B}(\mathrm{t}^{*} \to \mathrm{t}\mathrm{g})= $ 1. The results of the previous CMS analysis [30], using data corresponding to an integrated luminosity of 35.9 fb$ ^{-1} $, are shown as well.
Summary
A search for the pair production of heavy top-quark partners $\mathrm{t}^{*}$ has been presented, where the $\mathrm{t}^{*}$ couples predominantly to gluons and decays to a top quark and a gluon, $ \mathrm{t}^{*} \to \mathrm{t}\mathrm{g} $. Both spin-1/2 and spin-3/2 resonances are considered. The analysis uses 13 TeV proton-proton collision data collected by the CMS experiment between 2016 and 2018, corresponding to an integrated luminosity of 138 fb$ ^{-1} $. The final state analyzed consists of a lepton with high transverse momentum, missing transverse momentum and several jets. A deep neural network is used to identify potential signal events. With a two-step decorrelation procedure, independence of the deep neural network output from the main observable $ S_{\text{T}} $ has been achieved, where $ S_{\text{T}} $ is the scalar sum of the transverse momenta of the selected lepton and jets, and the missing transverse momentum. No statistically significant deviation from the background prediction was found. Upper limits at 95% confidence level are derived on the product of the $ \mathrm{t}^{*} \overline{\mathrm{t}}{}^{*} $ production cross section and branching fraction squared for $ \mathrm{t}^{*} \to \mathrm{t}\mathrm{g} $. These are between 0.12 pb and 0.8 fb for a spin-1/2 $\mathrm{t}^{*}$ and between 0.015 pb and 1.0 fb for a spin-3/2 $\mathrm{t}^{*}$, depending on the $\mathrm{t}^{*}$ mass. A comparison of these limits with the theory predictions results in mass limits for the $\mathrm{t}^{*}$ resonances, where the existence of a spin-1/2 $\mathrm{t}^{*}$ is excluded below a mass of 1050 GeV and for a spin-3/2 $\mathrm{t}^{*}$ below a mass of 1700 GeV. These are the most stringent limits to date and the first exclusion limit for a spin-1/2 $\mathrm{t}^{*}$ resonance at 13 TeV. The results also substantially improve the spin-3/2 exclusion limits compared to previous results.
References
1 ATLAS Collaboration Observation of a new particle in the search for the standard model Higgs boson with the ATLAS detector at the LHC PLB 716 (2012) 1 1207.7214
2 CMS Collaboration Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC PLB 716 (2012) 30 CMS-HIG-12-028
1207.7235
3 CMS Collaboration Observation of a new boson with mass near 125 GeV in pp collisions at $ \sqrt{s} = $ 7 and 8 TeV JHEP 06 (2013) 081 CMS-HIG-12-036
1303.4571
4 H. Georgi, L. Kaplan, D. Morin, and A. Schenk Effects of top compositeness PRD 51 (1995) 3888 hep-ph/9410307
5 B. Lillie, J. Shu, and T. M. P. Tait Top compositeness at the Tevatron and LHC JHEP 04 (2008) 087 0712.3057
6 A. Pomarol and J. Serra Top quark compositeness: Feasibility and implications PRD 78 (2008) 074026 0806.3247
7 K. Kumar, T. M. P. Tait, and R. Vega-Morales Manifestations of top compositeness at colliders JHEP 05 (2009) 022 0901.3808
8 T. A. DeGrand et al. Towards partial compositeness on the lattice: Baryons with fermions in multiple representations in Proceedings of 34th annual International Symposium on Lattice Field Theory -- PoS(LATTICE), 2016
link
1610.06465
9 A. Pierce and Y. Zhao Naturalness from a composite top? JHEP 01 (2017) 054 1607.01318
10 D. Buarque Franzosi and A. Tonero Top-quark partial compositeness beyond the effective field theory paradigm JHEP 04 (2020) 040 1908.06996
11 N. Arkani-Hamed, A. G. Cohen, E. Katz, and A. E. Nelson The littlest Higgs JHEP 07 (2002) 034 hep-ph/0206021
12 N. Arkani-Hamed, A. G. Cohen, and H. Georgi Electroweak symmetry breaking from dimensional deconstruction PLB 513 (2001) 232 hep-ph/0105239
13 M. Perelstein Little Higgs models and their phenomenology Prog. Part. Nucl. Phys. 58 (2007) 247 hep-ph/0512128
14 A. Ahmed, M. Lindner, and P. Saake Conformal little Higgs models PRD 109 (2024) 075041 2309.07845
15 L. Randall and R. Sundrum A large mass hierarchy from a small extra dimension PRL 83 (1999) 3370 hep-ph/9905221
16 T. Gherghetta and A. Pomarol Bulk fields and supersymmetry in a slice of AdS NPB 586 (2000) 141 hep-ph/0003129
17 S. B. Giddings, S. Kachru, and J. Polchinski Hierarchies from fluxes in string compactifications PRD 66 (2002) 106006 hep-th/0105097
18 K. Agashe, R. Contino, and A. Pomarol The minimal composite Higgs model NPB 719 (2005) 165 hep-ph/0412089
19 CMS Collaboration Search for pair production of vector-like quarks in the $ \mathrm{b}\mathrm{W}\overline{\mathrm{b}}\mathrm{W} $ channel from proton-proton collisions at $ \sqrt{s}= $ 13 TeV PLB 779 (2018) 82 1710.01539
20 CMS Collaboration Search for electroweak production of a vector-like T quark using fully hadronic final states JHEP 01 (2020) 036 1909.04721
21 CMS Collaboration Search for single production of a vector-like T quark decaying to a top quark and a Z boson in the final state with jets and missing transverse momentum at $ \sqrt{s} = $ 13 TeV JHEP 05 (2022) 093 2201.02227
22 CMS Collaboration Search for pair production of vector-like quarks in leptonic final states in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JHEP 07 (2023) 020 2209.07327
23 ATLAS Collaboration Search for pair-produced vector-like top and bottom partners in events with large missing transverse momentum in pp collisions with the ATLAS detector EPJC 83 (2023) 719 2212.05263
24 ATLAS Collaboration Search for pair-production of vector-like quarks in pp collision events at $ \sqrt{s}= $ 13 TeV with at least one leptonically decaying Z boson and a third-generation quark with the ATLAS detector PLB 843 (2023) 138019 2210.15413
25 ATLAS Collaboration Search for singly produced vector-like top partners in multilepton final states with 139 fb$^{-1} $ of pp collision data at $ \sqrt{s} = $ 13 TeV with the ATLAS detector PRD 109 (2024) 112012 2307.07584
26 H. Alhazmi, J. H. Kim, K. Kong, and I. M. Lewis Shedding light on top partner at the LHC JHEP 01 (2019) 139 1808.03649
27 J. Berger, J. Hubisz, and M. Perelstein A fermionic top partner: Naturalness and the LHC JHEP 07 (2012) 016 1205.0013
28 W. Rarita and J. Schwinger On a theory of particles with half integral spin PR 60 (1941) 61
29 CMS Collaboration Search for pair production of excited top quarks in the lepton+jets final state JHEP 06 (2014) 125 1311.5357
30 CMS Collaboration Search for pair production of excited top quarks in the lepton+jets final state PLB 778 (2018) 349 1711.10949
31 CMS Collaboration HEPData record for this analysis link
32 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004
33 CMS Collaboration Development of the CMS detector for the CERN LHC Run 3 JINST 19 (2024) P05064 CMS-PRF-21-001
2309.05466
34 CMS Collaboration Performance of the CMS level-1 trigger in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 15 (2020) P10017 CMS-TRG-17-001
2006.10165
35 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
36 J. Alwall et al. The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations JHEP 07 (2014) 079 1405.0301
37 D. A. Dicus, D. Karabacak, S. Nandi, and S. K. Rai Search for spin-3/2 quarks at the Large Hadron Collider PRD 87 (2013) 015023 1208.5811
38 P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms JHEP 11 (2004) 040 hep-ph/0409146
39 S. Frixione, P. Nason, and C. Oleari Matching NLO QCD computations with parton shower simulations: The POWHEG method JHEP 11 (2007) 070 0709.2092
40 S. Frixione, P. Nason, and G. Ridolfi A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction JHEP 09 (2007) 126 0707.3088
41 S. Alioli, P. Nason, C. Oleari, and E. Re A general framework for implementing NLO calculations in shower Monte Carlo programs: The POWHEG BOX JHEP 06 (2010) 043 1002.2581
42 E. Re Single-top $ {\mathrm{W}}{\mathrm{t}} $-channel production matched with parton showers using the POWHEG method EPJC 71 (2011) 1547 1009.2450
43 M. Czakon and A. Mitov Top++: A program for the calculation of the top-pair cross-section at hadron colliders Comput. Phys. Commun. 185 (2014) 2930 1112.5675
44 T. Sjöstrand et al. An introduction to PYTHIA 8.2 Comput. Phys. Commun. 191 (2015) 159 1410.3012
45 NNPDF Collaboration Parton distributions from high-precision collider data EPJC 77 (2017) 663 1706.00428
46 CMS Collaboration Event generator tunes obtained from underlying event and multiparton scattering measurements EPJC 76 (2016) 155 CMS-GEN-14-001
1512.00815
47 GEANT4 Collaboration GEANT 4---a simulation toolkit NIM A 506 (2003) 250
48 CMS Collaboration Measurement of the inelastic proton-proton cross section at $ \sqrt{s}= $ 13 TeV JHEP 07 (2018) 161 CMS-FSQ-15-005
1802.02613
49 CMS Collaboration Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 CMS-PRF-14-001
1706.04965
50 CMS Collaboration Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 13 (2018) P06015 CMS-MUO-16-001
1804.04528
51 CMS Collaboration Performance of CMS muon reconstruction in pp collision events at $ \sqrt{s}= $ 7 TeV JINST 7 (2012) P10002 CMS-MUO-10-004
1206.4071
52 CMS Collaboration Performance of the reconstruction and identification of high-momentum muons in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JINST 15 (2020) P02027 CMS-MUO-17-001
1912.03516
53 CMS Collaboration Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC JINST 16 (2021) P05014 CMS-EGM-17-001
2012.06888
54 CMS Collaboration ECAL 2016 refined calibration and Run2 summary plots CMS Detector Performance Summary CMS-DP-2020-021, 2020
CDS
55 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ k_{\mathrm{T}} $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
56 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1896 1111.6097
57 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup per particle identification JHEP 10 (2014) 059 1407.6013
58 CMS Collaboration Pileup mitigation at CMS in 13 TeV data JINST 15 (2020) P09018 CMS-JME-18-001
2003.00503
59 CMS Collaboration Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV JINST 12 (2017) P02014 CMS-JME-13-004
1607.03663
60 T. Lapsien, R. Kogler, and J. Haller A new tagger for hadronically decaying heavy particles at the LHC EPJC 76 (2016) 600 1606.04961
61 M. Cacciari, G. P. Salam, and G. Soyez The catchment area of jets JHEP 04 (2008) 005 0802.1188
62 CMS Collaboration Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques JINST 15 (2020) P06005 CMS-JME-18-002
2004.08262
63 R. Kogler Advances in jet substructure at the LHC: Algorithms, measurements and searches for new physical phenomena Volume 284 of Springer Tracts Mod. Phys. Springer, ISBN~978-3-030-72857-1, 978-3-030-72858-8, 2021
link
64 J. Thaler and K. Van Tilburg Identifying boosted objects with $ N $-subjettiness JHEP 03 (2011) 015 1011.2268
65 J. Thaler and K. Van Tilburg Maximizing boosted top identification by minimizing $ N $-subjettiness JHEP 02 (2012) 093 1108.2701
66 CMS Collaboration Search for a heavy resonance decaying into a top quark and a W boson in the lepton+jets final state at $ \sqrt{s} = $ 13 TeV JHEP 04 (2022) 048 2111.10216
67 CMS Collaboration Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV JINST 13 (2018) P05011 CMS-BTV-16-002
1712.07158
68 E. Bols et al. Jet flavour classification using DeepJet JINST 15 (2020) P12012 2008.10519
69 CMS Collaboration Performance summary of AK4 jet b tagging with data from proton-proton collisions at 13 TeV with the CMS detector Technical Report CMS-DP-2023-005, 2023
CDS
70 CMS Collaboration Performance of missing transverse momentum reconstruction in proton-proton collisions at $ \sqrt{s} = $ 13\,TeV using the CMS detector JINST 14 (2019) P07004 CMS-JME-17-001
1903.06078
71 CMS Collaboration Search for resonant $ \mathrm{t}\overline{\mathrm{t}} $ production in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JHEP 04 (2019) 031 1810.05905
72 J. Dolen et al. Thinking outside the ROCs: Designing decorrelated taggers (DDT) for jet substructure JHEP 05 (2016) 156 1603.00027
73 CMS Collaboration Measurement of the differential cross section for top quark pair production in pp collisions at $ \sqrt{s}= $ 8 TeV EPJC 75 (2015) 542 CMS-TOP-12-028
1505.04480
74 CMS Collaboration Measurement of the $ {\mathrm{t}\overline{\mathrm{t}}} $ production cross section in the all-jets final state in pp collisions at $ \sqrt{s}= $ 8 TeV EPJC 76 (2016) 128 CMS-TOP-14-018
1509.06076
75 CMS Collaboration The CMS statistical analysis and combination tool: COMBINE Accepted by Comput. Softw. Big Sci, 2024 CMS-CAT-23-001
2404.06614
76 CMS Collaboration Precision luminosity measurement in proton-proton collisions at $ \sqrt{s} = $ 13 TeV in 2015 and 2016 at CMS EPJC 81 (2021) 800 CMS-LUM-17-003
2104.01927
77 CMS Collaboration CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s} = $ 13 TeV CMS Physics Analysis Summary, 2018
link
CMS-PAS-LUM-17-004
78 CMS Collaboration CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s} = $ 13 TeV CMS Physics Analysis Summary, 2019
link
CMS-PAS-LUM-18-002
79 J. Butterworth et al. PDF4LHC recommendations for LHC Run II JPG 43 (2016) 023001 1510.03865
80 ATLAS and CMS Collaborations, and LHC Higgs Combination Group Procedure for the LHC Higgs boson search combination in Summer 2011 CMS Note CMS-NOTE-2011-005, ATL-PHYS-PUB-2011-11, 2011
81 A. L. Read Presentation of search results: The CL$ _{\text{s}} $ technique JPG 28 (2002) 2693
82 T. Junk Confidence level computation for combining searches with small statistics NIM A 434 (1999) 435 hep-ex/9902006
83 G. Cowan, K. Cranmer, E. Gross, and O. Vitells Asymptotic formulae for likelihood-based tests of new physics EPJC 71 (2011) 1554 1007.1727
84 W. Verkerke and D. P. Kirkby The RooFit toolkit for data modeling in Proc. Int. Conf on Computing in High Energy and Nuclear Physics (CHEP03), L. Lyons and M. Karagoz, eds., 2003
link
physics/0306116
85 L. Moneta et al. The RooStats project in Proc. 13th Int. Workshop on Advanced Computing and Analysis Techniques in Physics Research, T. Speer et al., eds., 2010
link
1009.1003
Compact Muon Solenoid
LHC, CERN