CMS logoCMS event Hgg
Compact Muon Solenoid
LHC, CERN

CMS-TOP-21-014 ; CERN-EP-2022-155
Measurement of the $\mathrm{t\bar{t}}$ charge asymmetry in events with highly Lorentz-boosted top quarks in pp collisions at $\sqrt{s} = $ 13 TeV
Phys. Lett. B 846 (2023) 137703
Abstract: The measurement of the charge asymmetry in top quark pair events with highly Lorentz-boosted top quarks decaying to a single lepton and jets is presented. The analysis is performed using proton-proton collisions at $ \sqrt{s}= $ 13 TeV with the CMS detector at the LHC and corresponding to an integrated luminosity of 138 fb$ ^{-1} $. The selection is optimized for top quarks produced with large Lorentz boosts, resulting in nonisolated leptons and overlapping jets. The top quark charge asymmetry is measured for events with a $\mathrm{t\bar{t}}$ invariant mass larger than 750 GeV and corrected for detector and acceptance effects using a binned maximum likelihood fit. The measured top quark charge asymmetry of (0.42$_{- 0.69}^{+ 0.64}$)% is in good agreement with the standard model prediction at next-to-next-to-leading order in quantum chromodynamic perturbation theory with next-to-leading-order electroweak corrections. The result is also presented for two invariant mass ranges, 750-900 and $ {>} $900 GeV.
Figures & Tables Summary References CMS Publications
Figures

png pdf
Figure 1:
Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample (described in Section 6): $\Delta |y|$ (upper left), reconstructed $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} $ (upper right), distance between the lepton and the closest AK4 jet $ {\Delta R_{\text {min}}(\ell, j)} $ (lower left), and the number of AK4 jets (lower right). The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions (described in Section 5). The lower panels give the ratio of the data to the sum of the MC predictions.

png pdf
Figure 1-a:
Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample (described in Section 6): $\Delta |y|$ (upper left), reconstructed $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} $ (upper right), distance between the lepton and the closest AK4 jet $ {\Delta R_{\text {min}}(\ell, j)} $ (lower left), and the number of AK4 jets (lower right). The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions (described in Section 5). The lower panels give the ratio of the data to the sum of the MC predictions.

png pdf
Figure 1-b:
Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample (described in Section 6): $\Delta |y|$ (upper left), reconstructed $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} $ (upper right), distance between the lepton and the closest AK4 jet $ {\Delta R_{\text {min}}(\ell, j)} $ (lower left), and the number of AK4 jets (lower right). The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions (described in Section 5). The lower panels give the ratio of the data to the sum of the MC predictions.

png pdf
Figure 1-c:
Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample (described in Section 6): $\Delta |y|$ (upper left), reconstructed $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} $ (upper right), distance between the lepton and the closest AK4 jet $ {\Delta R_{\text {min}}(\ell, j)} $ (lower left), and the number of AK4 jets (lower right). The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions (described in Section 5). The lower panels give the ratio of the data to the sum of the MC predictions.

png pdf
Figure 1-d:
Comparison between data and MC simulation for kinematic distributions based on events in the signal candidate sample (described in Section 6): $\Delta |y|$ (upper left), reconstructed $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} $ (upper right), distance between the lepton and the closest AK4 jet $ {\Delta R_{\text {min}}(\ell, j)} $ (lower left), and the number of AK4 jets (lower right). The vertical bars on the points show the statistical uncertainty in the data. The shaded bands represent the total uncertainty in the MC predictions (described in Section 5). The lower panels give the ratio of the data to the sum of the MC predictions.

png pdf
Figure 2:
Comparison between data and MC simulation for $ {\Delta |y|} $ for each of the 12 analysis channels, both before (left) and after (right) the likelihood normalization. The plots in the upper row correspond to 750 $ < {M_{{\mathrm{t} \mathrm{\bar{t}}}}} < $ 900 GeV, and the plots in the lower row to $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 900 GeV. The vertical bars on the points represent the statistical uncertainties in the data and the shaded bands give the combined MC statistical and systematic uncertainties. The lower panels display the ratio of the data yields to the sum of the MC predictions.

png pdf
Figure 2-a:
Comparison between data and MC simulation for $ {\Delta |y|} $ for each of the 12 analysis channels, both before (left) and after (right) the likelihood normalization. The plots in the upper row correspond to 750 $ < {M_{{\mathrm{t} \mathrm{\bar{t}}}}} < $ 900 GeV, and the plots in the lower row to $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 900 GeV. The vertical bars on the points represent the statistical uncertainties in the data and the shaded bands give the combined MC statistical and systematic uncertainties. The lower panels display the ratio of the data yields to the sum of the MC predictions.

png pdf
Figure 2-b:
Comparison between data and MC simulation for $ {\Delta |y|} $ for each of the 12 analysis channels, both before (left) and after (right) the likelihood normalization. The plots in the upper row correspond to 750 $ < {M_{{\mathrm{t} \mathrm{\bar{t}}}}} < $ 900 GeV, and the plots in the lower row to $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 900 GeV. The vertical bars on the points represent the statistical uncertainties in the data and the shaded bands give the combined MC statistical and systematic uncertainties. The lower panels display the ratio of the data yields to the sum of the MC predictions.

png pdf
Figure 2-c:
Comparison between data and MC simulation for $ {\Delta |y|} $ for each of the 12 analysis channels, both before (left) and after (right) the likelihood normalization. The plots in the upper row correspond to 750 $ < {M_{{\mathrm{t} \mathrm{\bar{t}}}}} < $ 900 GeV, and the plots in the lower row to $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 900 GeV. The vertical bars on the points represent the statistical uncertainties in the data and the shaded bands give the combined MC statistical and systematic uncertainties. The lower panels display the ratio of the data yields to the sum of the MC predictions.

png pdf
Figure 2-d:
Comparison between data and MC simulation for $ {\Delta |y|} $ for each of the 12 analysis channels, both before (left) and after (right) the likelihood normalization. The plots in the upper row correspond to 750 $ < {M_{{\mathrm{t} \mathrm{\bar{t}}}}} < $ 900 GeV, and the plots in the lower row to $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 900 GeV. The vertical bars on the points represent the statistical uncertainties in the data and the shaded bands give the combined MC statistical and systematic uncertainties. The lower panels display the ratio of the data yields to the sum of the MC predictions.

png pdf
Figure 3:
Measured ${{A_{\text {C}}} ^{\text {fid}}}$ (left) and measured ${A_{\text {C}}}$ in the full phase space (right) presented in different mass regions after combining the $ \mu $+jets and e+jets channels. The vertical bars represent the total uncertainties, with the inner tick mark indicating the statistical uncertainty in the observed data. The measured values are compared to the theoretical prediction, including NNLO QCD and NLO EW corrections from Ref. [4]. The theoretical prediction in the fiducial region is obtained by fitting Asimov data that passed the signal candidate selection described in Sections 3 and 4.

png pdf
Figure 3-a:
Measured ${{A_{\text {C}}} ^{\text {fid}}}$ (left) and measured ${A_{\text {C}}}$ in the full phase space (right) presented in different mass regions after combining the $ \mu $+jets and e+jets channels. The vertical bars represent the total uncertainties, with the inner tick mark indicating the statistical uncertainty in the observed data. The measured values are compared to the theoretical prediction, including NNLO QCD and NLO EW corrections from Ref. [4]. The theoretical prediction in the fiducial region is obtained by fitting Asimov data that passed the signal candidate selection described in Sections 3 and 4.

png pdf
Figure 3-b:
Measured ${{A_{\text {C}}} ^{\text {fid}}}$ (left) and measured ${A_{\text {C}}}$ in the full phase space (right) presented in different mass regions after combining the $ \mu $+jets and e+jets channels. The vertical bars represent the total uncertainties, with the inner tick mark indicating the statistical uncertainty in the observed data. The measured values are compared to the theoretical prediction, including NNLO QCD and NLO EW corrections from Ref. [4]. The theoretical prediction in the fiducial region is obtained by fitting Asimov data that passed the signal candidate selection described in Sections 3 and 4.

png pdf
Figure 4:
The $ \pm 1 $ standard deviation ($\sigma $) impacts of the nuisance parameters corresponding to the systematic uncertainties in the full phase space $ {A_{\text {C}}} $ measurement for $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 750 GeV. The red and blue bars show the effect on the unfolded $ {A_{\text {C}}} $ values for up and down variations of the systematic uncertainty. The MC statistical uncertainties are omitted here.
Tables

png pdf
Table 1:
The signal event yields in data and MC simulations after the likelihood fit for each of the 12 channels ($ \mu $+jets, e+jets, 3 years; and two mass regions). The uncertainties in the MC predictions include both statistical and systematic components.

png pdf
Table 2:
Measured unfolded charge asymmetry in the fiducial phase space (upper rows) and the full phase space (lower rows) shown for individual channels compared with the theoretical prediction from MC. Results are shown for events with $ {M_{{\mathrm{t} \mathrm{\bar{t}}}}} > $ 750 GeV and for two invariant mass ranges, 750-900 and ${>}$900 GeV. The statistical (stat) and systematic (syst) uncertainties in the data, the MC statistical uncertainty (MC stat), and the total uncertainty in the measured values (Total) are also shown. All values are in percent.
Summary
A measurement of the charge asymmetry in $\mathrm{t\bar{t}}$ events with highly boosted top quarks produced in proton-proton collisions at $ \sqrt{s}= $ 13 TeV is presented based on 138 fb$ ^{-1} $ of data collected by the CMS experiment at the LHC. The selection is optimized for top quarks produced with high Lorentz boosts that yield collimated decay products that are partially or fully merged and can result in nonisolated leptons and overlapping jets. The measured top quark charge asymmetry ($ A_{\text{C}} $) is corrected for detector and acceptance effects using a binned maximum likelihood fit. This is the first CMS measurement to use 13 TeV data and a binned maximum likelihood unfolding technique to measure $ A_{\text{C}} $ directly at parton level in the full phase space. In addition, it is the first result that focuses exclusively on the highly Lorentz-boosted regime, using dedicated reconstruction techniques for the hadronically and leptonically decaying top quarks at both the trigger and offline stages. Since the relative contribution of valence quarks increases at high momentum transfer, $ A_{\text{C}} $ is especially sensitive to beyond the standard model processes in this highly boosted phase space. The resulting unfolded charge asymmetry for $\mathrm{t\bar{t}}$ events with invariant masses satisfying $ M_{\mathrm{t\bar{t}}} > $ 750 GeV is (0.42$_{- 0.69}^{+ 0.64}$)%, where the uncertainty includes both statistical and systematic components. The corresponding theoretical prediction at next-to-next-to-leading order in QCD perturbation theory with next-to-leading-order electroweak corrections from Ref. [5] is (0.94 $ ^{+ 0.05}_{-0.07} $)%. Good agreement between the measurement and the most precise standard model prediction is thus observed. The result demonstrates that top quark properties can be precisely measured in the highly boosted topology.
References
1 M. Czakon, P. Fiedler, and A. Mitov Total top-quark pair-production cross section at hadron colliders through $ \mathcal{O}(\alpha^4_s) $ PRL 110 (2013) 252004 1303.6254
2 S. Catani et al. Top-quark pair production at the LHC: Fully differential QCD predictions at NNLO JHEP 07 (2019) 100 1906.06535
3 CDF and D0 Collaborations Combined forward-backward asymmetry measurements in top-antitop quark production at the Tevatron PRL 120 (2018) 042001 1709.04894
4 M. Czakon, P. Fiedler, and A. Mitov Resolving the Tevatron top quark forward-backward asymmetry puzzle: Fully differential next-to-next-to-leading-order calculation PRL 115 (2015) 052001 1411.3007
5 M. Czakon et al. Top-quark charge asymmetry at the LHC and Tevatron through NNLO QCD and NLO EW PRD 98 (2018) 014003 1711.03945
6 M. Czakon, D. Heymes, and A. Mitov High-precision differential predictions for top-quark pairs at the LHC PRL 116 (2016) 082003 1511.00549
7 J. Rojo et al. The PDF4LHC report on PDFs and LHC data: results from Run I and preparation for Run II JPG 42 (2015) 103103 1507.00556
8 J. A. Aguilar-Saavedra, A. Juste, and F. Rubbo Boosting the $ \mathrm{t\bar{t}} $ charge asymmetry PLB 707 (2012) 92 1109.3710
9 O. Antunano, J. H. Kuhn, and G. Rodrigo Top quarks, axigluons and charge asymmetries at hadron colliders PRD 77 (2008) 014003 0709.1652
10 P. H. Frampton, J. Shu, and K. Wang Axigluon as possible explanation for pp $\rightarrow\mathrm{t\bar{t}} $ forward-backward asymmetry PLB 683 (2010) 294 0911.2955
11 J. L. Rosner Prominent decay modes of a leptophobic Z' PLB 387 (1996) 113 hep-ph/9607207
12 P. Ferrario and G. Rodrigo Massive color-octet bosons and the charge asymmetries of top quarks at hadron colliders PRD 78 (2008) 094018 0809.3354
13 P. Ferrario and G. Rodrigo Constraining heavy colored resonances from top-antitop quark events PRD 80 (2009) 051701 0906.5541
14 J. A. Aguilar-Saavedra and M. Perez-Victoria Asymmetries in $ \mathrm{t\bar{t}} $ production: LHC versus Tevatron PRD 84 (2011) 115013 1105.4606
15 J. A. Aguilar-Saavedra and M. Perez-Victoria Simple models for the top asymmetry: Constraints and predictions JHEP 09 (2011) 097 1107.0841
16 R. Benbrik, C.-H. Chen, and M. El Kacimi Colored bosons on top FBA and angular cross section for $ \mathrm{t\bar{t}} $ production PLB 725 (2013) 372 1304.2273
17 D.-W. Jung, P. Ko, J. S. Lee, and S.-h. Nam Model independent analysis of the forward-backward asymmetry of top quark production at the Tevatron PLB 691 (2010) 238 0912.1105
18 ATLAS and CMS Collaborations Combination of inclusive and differential $ \mathrm{t} \overline{\mathrm{t}} $ charge asymmetry measurements using ATLAS and CMS data at $ \sqrt{s}= $ 7 and 8 TeV JHEP 04 (2018) 033 1709.05327
19 C. Zhang and S. Willenbrock Effective-field-theory approach to top-quark production and decay PRD 83 (2011) 034006 1008.3869
20 J. Ellis et al. Top, Higgs, diboson and electroweak fit to the Standard Model effective field theory JHEP 04 (2021) 279 2012.02779
21 ATLAS Collaboration Differential $ t\bar{t} $ cross-section measurements using boosted top quarks in the all-hadronic final state with 139 fb$ ^{-1} $ of ATLAS data 5, 2022 2205.02817
22 CMS Collaboration Search for resonant $ \mathrm{t}\overline{\mathrm{t}} $ production in proton-proton collisions at $ \sqrt{s}= $ 13 TeV JHEP 04 (2019) 031 CMS-B2G-17-017
1810.05905
23 CMS Collaboration HEPData record for this analysis link
24 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
25 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
26 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004 CMS-00-001
27 CMS Collaboration Particle-flow reconstruction and global event description with the CMS detector JINST 12 (2017) P10003 CMS-PRF-14-001
1706.04965
28 CMS Collaboration Description and performance of track and primary-vertex reconstruction with the CMS tracker JINST 9 (2014) P10009 CMS-TRK-11-001
1405.6569
29 CMS Collaboration Technical proposal for the Phase-II upgrade of the Compact Muon Solenoid CMS-PAS-TDR-15-002 CMS-PAS-TDR-15-002
30 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ {k_{\mathrm{T}}} $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
31 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1896 1111.6097
32 D. Bertolini, P. Harris, M. Low, and N. Tran Pileup per particle identification JHEP 10 (2014) 059 1407.6013
33 CMS Collaboration Pileup mitigation at CMS in 13 TeV data JINST 15 (2020) P09018 CMS-JME-18-001
2003.00503
34 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
35 CMS Collaboration Determination of jet energy calibration and transverse momentum resolution in CMS JINST 6 (2011) P11002 CMS-JME-10-011
1107.4277
36 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
37 CMS Collaboration Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques JINST 15 (2020) P06005 CMS-JME-18-002
2004.08262
38 A. J. Larkoski, S. Marzani, G. Soyez, and J. Thaler Soft drop JHEP 05 (2014) 146 1402.2657
39 J. Thaler and K. Van Tilburg Identifying boosted objects with N-subjettiness JHEP 03 (2011) 015 1011.2268
40 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
41 E. Bols et al. Jet flavour classification using DeepJet JINST 15 (2020) P12012 2008.10519
42 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
43 CMS Collaboration CMS luminosity measurement for the 2017 data-taking period at $ \sqrt{s} = $ 13 TeV CMS-PAS-LUM-17-004 CMS-PAS-LUM-17-004
44 CMS Collaboration CMS luminosity measurement for the 2018 data-taking period at $ \sqrt{s} = $ 13 TeV CMS-PAS-LUM-18-002 CMS-PAS-LUM-18-002
45 CMS Collaboration Measurement of differential $ \mathrm{t\bar{t}} $ production cross sections in the full kinematic range using lepton+jets events from proton-proton collisions at $ \sqrt {s} = $ 13 TeV PRD 104 (2021) 092013 CMS-TOP-20-001
2108.02803
46 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
47 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
48 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
49 T. Sjostrand et al. An introduction to PYTHIA 8.2 CPC 191 (2015) 159 1410.3012
50 CMS Collaboration Extraction and validation of a new set of CMS PYTHIA 8 tunes from underlying-event measurements EPJC 80 (2020) 4 CMS-GEN-17-001
1903.12179
51 GEANT4 Collaboration GEANT 4 --- a simulation toolkit NIM A 506 (2003) 250
52 NNPDF Collaboration Parton distributions for the LHC Run II JHEP 04 (2015) 040 1410.8849
53 CMS Collaboration Search for $ \mathrm{t\bar{t}} $ resonances in highly-boosted lepton+jets and fully hadronic final stated in proton-proton collisions at 13 TeV JHEP 07 (2017) 001 CMS-B2G-16-015
1704.03366
54 CMS Collaboration Measurement of the top quark polarization and spin correlations using dilepton final states in proton-proton collisions at 13 TeV PRD 100 (2019) 072002 CMS-TOP-18-006
1907.03729
55 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
56 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
57 CMS Collaboration Performance of the DeepJet b tagging algorithm using 41.9 fb$^{-1}$ of data from proton-proton collisions at 13 TeV with the Phase 1 CMS detector CDS
58 NNPDF Collaboration Parton distributions from high-precision collider data EPJC 77 (2017) 663 1706.00428
59 ATLAS, CMS, and the LHC Higgs Combination Group Procedure for the LHC Higgs boson search combination in Summer 2011 CMS-NOTE-2011-005, ATL-PHYS-PUB-2011-11, 2011
link
60 R. J. Barlow and C. Beeston Fitting using finite Monte Carlo samples CPC 77 (1993) 219
61 CMS Collaboration Combine: Software tools used for statistical analysis link
Compact Muon Solenoid
LHC, CERN