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CMS-TOP-16-016 ; CERN-EP-2017-023
Search for standard model production of four top quarks in proton-proton collisions at $ \sqrt{s} = $ 13 TeV
Phys. Lett. B 772 (2017) 336
Abstract: A search for events containing four top quarks (${\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $) is reported from proton-proton collisions recorded by the CMS experiment at $\sqrt{s} = $ 13 TeV and corresponding to an integrated luminosity of 2.6 fb$^{-1}$. The analysis considers the single-lepton (e or $\mu$)+jets and the opposite-sign dilepton ($\mu\mu$, $\mu^{\pm} \mathrm{ e }^{\mp}$, or $\mathrm{ e }^{+}\mathrm{ e }^{-}$)+jets channels. It uses boosted decision trees to combine information on the global event and jet properties to distinguish between ${\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ and $\mathrm{ t \bar{t} }$ production. The number of events observed after all selection requirements is consistent with expectations from background and standard model signal predictions, and an upper limit is set on the cross section for ${\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ production in the standard model of 94 fb at 95% confidence level (10.2 $\times$ the prediction), with an expected limit of 118 fb. This is combined with the results from the published CMS search in the same-sign dilepton channel, resulting in an improved limit of 69 fb at 95% confidence level (7.4 $\times$ the prediction), with an expected limit of 71 fb. These are the strongest constraints on the rate of ${\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ production to date.
Figures & Tables Summary Additional Figures & Tables References CMS Publications
Figures

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Figure 1:
A representative Feynman diagram for ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ production in the SM at lowest order in QCD.

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Figure 2:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}}$ for the $\mu $+jets (left) and e+jets (right) final states from data and the estimated background contributions from simulation, in the $ N_{\mathrm {j}} \geq $ 9 and 3 $ N_{\text {tags}}^{\mathrm {m}} $ (upper panels) and the $ N_{\mathrm {j}} \geq $ 9 and $\geq $ 4 $ N_{\text {tags}}^{\mathrm {m}} $ categories (lower panels). The vertical bars show the statistical uncertainties in the data. The predicted background distributions from simulation are shown by the shaded histograms The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the matrix-element (ME) factorization and renormalization scales used in the simulation. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by open histogram, multiplied by a factor of 20.

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Figure 2-a:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}}$ for the $\mu $+jets final state from data and the estimated background contributions from simulation, in the $ N_{\mathrm {j}} \geq $ 9 and 3 $ N_{\text {tags}}^{\mathrm {m}} $ category. The vertical bars show the statistical uncertainties in the data. The predicted background distributions from simulation are shown by the shaded histograms The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the matrix-element (ME) factorization and renormalization scales used in the simulation. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by open histogram, multiplied by a factor of 20.

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Figure 2-b:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}}$ for the e+jets final state from data and the estimated background contributions from simulation, in the $ N_{\mathrm {j}} \geq $ 9 and 3 $ N_{\text {tags}}^{\mathrm {m}} $ category. The vertical bars show the statistical uncertainties in the data. The predicted background distributions from simulation are shown by the shaded histograms The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the matrix-element (ME) factorization and renormalization scales used in the simulation. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by open histogram, multiplied by a factor of 20.

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Figure 2-c:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}}$ for the $\mu $+jets final state from data and the estimated background contributions from simulation, in the $ N_{\mathrm {j}} \geq $ 9 and $\geq $ 4 $ N_{\text {tags}}^{\mathrm {m}} $ category. The vertical bars show the statistical uncertainties in the data. The predicted background distributions from simulation are shown by the shaded histograms The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the matrix-element (ME) factorization and renormalization scales used in the simulation. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by open histogram, multiplied by a factor of 20.

png pdf
Figure 2-d:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}}$ for the e+jets final state from data and the estimated background contributions from simulation, in the $ N_{\mathrm {j}} \geq $ 9 and $\geq $ 4 $ N_{\text {tags}}^{\mathrm {m}} $ category. The vertical bars show the statistical uncertainties in the data. The predicted background distributions from simulation are shown by the shaded histograms The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the matrix-element (ME) factorization and renormalization scales used in the simulation. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by open histogram, multiplied by a factor of 20.

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Figure 3:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\text {dil}}}$ for the combined dilepton ($\pi \mu $+ $\mu ^{\pm } \mathrm{ e } ^{\mp }$+ $\mathrm{ e }^{+} \mathrm{ e }^{-} $) event sample for 4-5 jets (upper left ), 6-7 jets (upper right ), and $\geq $8 jets (bottom). The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by the open histogram, multiplied by a factor of 20.

png pdf
Figure 3-a:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\text {dil}}}$ for the combined dilepton ($\pi \mu $+ $\mu ^{\pm } \mathrm{ e } ^{\mp }$+ $\mathrm{ e }^{+} \mathrm{ e }^{-} $) event sample for 4-5 jets. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by the open histogram, multiplied by a factor of 20.

png pdf
Figure 3-b:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\text {dil}}}$ for the combined dilepton ($\pi \mu $+ $\mu ^{\pm } \mathrm{ e } ^{\mp }$+ $\mathrm{ e }^{+} \mathrm{ e }^{-} $) event sample for 6-7 jets. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by the open histogram, multiplied by a factor of 20.

png pdf
Figure 3-c:
Distribution of the event-level BDT discriminants ${D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\text {dil}}}$ for the combined dilepton ($\pi \mu $+ $\mu ^{\pm } \mathrm{ e } ^{\mp }$+ $\mathrm{ e }^{+} \mathrm{ e }^{-} $) event sample for $\geq $8 jets. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ signal contribution is shown by the open histogram, multiplied by a factor of 20.
Tables

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Table 1:
Expected and observed 95% CL upper limits on SM ${{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } }$ production as a multiple of ${\sigma _{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {SM}}}$ and in fb. The results for the two analyses from this paper are shown separately and combined. The result from a previous CMS measurement [12] is also given, along with the overall limits when the three measurements are combined. The values quoted for the uncertainties on the expected limits are the one standard deviation values and include all statistical and systematic uncertainties.
Summary
In summary, a search has been performed for events containing four top quarks using data recorded by the CMS experiment in proton-proton collisions at $\sqrt{s} = $ 13 TeV corresponding to an integrated luminosity of 2.6 fb$^{-1}$. The final states considered in the analysis are the single-lepton channel with exactly one electron or muon, and the opposite-sign dilepton channel with exactly two of any combination of electrons or muons. A boosted decision tree is used to discriminate between the ${\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ signal and the $\mathrm{ t \bar{t} }$ background, and no signal is observed. This leads to an upper limit on the SM production cross section for$ {\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ of 94 fb (10.2 ${\sigma_{{\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} }^{\mathrm{SM}}} $), with an expected limit of 118$^{+76}_{-41}$ fb at the 95% confidence level. This result is combined with a previous search [12] with similar sensitivity in the same-sign dilepton channel to obtain an improved limit of 69 fb, with an expected limit of 71$^{+38}_{-24}$ fb. This is the most stringent limit on $ {\mathrm{ t \bar{t} }\mathrm{ t \bar{t} }} $ production at $\sqrt{s } = $ 13 TeV published to date.
Additional Figures

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Additional Figure 1:
Summary of the event-level BDT discriminant ${ {D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}} }$ for the single electron events, showing the jet multiplicities and number of b jets considered in the analysis, before the fit. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM $ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } $ signal contribution is shown by the open histogram, multiplied by a factor of 20.

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Additional Figure 2:
Summary of the event-level BDT discriminant ${ {D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {lj}}} }$ for the single muon events, showing the jet multiplicities and number of b jets considered in the analysis, before the fit. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM $ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } $ signal contribution is shown by the open histogram, multiplied by a factor of 20.

png pdf
Additional Figure 3:
Summary of the event-level BDT discriminant ${ {D_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }^{\mathrm {dil}}} }$ for the dilepton ($\mu ^+\mu ^-$+ $\mu ^{\pm } {\rm e}^{\mp }$+ ${\rm e}^+ {\rm e}^-$) events, showing the jet multiplicities considered in the analysis, before the fit. The vertical bars show the statistical uncertainty in the data. The predicted background distributions from simulation are shown by the shaded histograms. The hatched area shows the size of the dominant systematic uncertainty in the simulation, which comes from the choice of the matrix-element (ME) factorization and renormalization scales used in the simulation. The electroweak (EW) histogram is the sum of the Drell-Yan and W boson+jets backgrounds. The expected SM ${\mathrm{ t } {}\mathrm{ \bar{t} } }$ signal contribution is shown by the open histogram, multiplied by a factor of 20.

png pdf
Additional Figure 4:
Summary of the expected and observed upper limits on $ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } $ production, in multiples of the standard model $ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } $ cross section, $\sigma ^{SM}_{ {{\mathrm{ t } {}\mathrm{ \bar{t} } } {\mathrm{ t } {}\mathrm{ \bar{t} } } } }$, for the SS dilepton, OS dilepton, single lepton, and combined analyses.
Additional Tables

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Additional Table 1:
Number of observed and expected background events after preselection in each search channel.
References
1 M. Toharia and J. D. Wells Gluino decays with heavier scalar superpartners JHEP 02 (2006) 015 hep-ph/0503175
2 K. Kumar, T. M. P. Tait, and R. Vega-Morales Manifestations of top compositeness at colliders JHEP 05 (2009) 022 0901.3808
3 S. Calvet, B. Fuks, P. Gris, and L. Valery Searching for sgluons in multitop events at a center-of-mass energy of 8 TeV JHEP 04 (2013) 043 1212.3360
4 G. Cacciapaglia et al. Composite scalars at the LHC: the Higgs, the Sextet and the Octet JHEP 11 (2015) 201 1507.02283
5 O. Ducu, L. Heurtier, and J. Maurer LHC signatures of a $ \mathrm{Z}' $ mediator between dark matter and the SU(3) sector JHEP 03 (2016) 006 1509.05615
6 C. Arina et al. A comprehensive approach to dark matter studies: exploration of simplified top-philic models JHEP 11 (2016) 111 1605.09242
7 Q.-H. Cao, S.-L. Chen, and Y. Liu Probing Higgs width and top quark Yukawa coupling from $ \textrm{t}\bar{\textrm{t}}\textrm{H} $ and $ \textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}} $ productions Submitted to PRD 1602.01934
8 G. Bevilacqua and M. Worek Constraining BSM physics at the LHC: Four top final states with NLO accuracy in perturbative QCD JHEP 07 (2012) 111 1206.3064
9 CMS Collaboration Search for standard model production of four top quarks in the lepton+jets channel in pp collisions at $ \sqrt{s} = $ 8 TeV JHEP 11 (2014) 154 CMS-TOP-13-012
1409.7339
10 ATLAS Collaboration Search for production of vector-like quark pairs and of four top quarks in the lepton-plus-jets final state in pp collisions at $ \sqrt{s}= $ 8 TeV with the ATLAS detector JHEP 08 (2015) 105 1505.04306
11 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
12 CMS Collaboration Search for new physics in same-sign dilepton events in proton-proton collisions at $ \sqrt{s} = $ 13 TeV EPJC 76 (2016) 439 CMS-SUS-15-008
1605.03171
13 CMS Collaboration The CMS trigger system JINST 12 (2017) P01020 CMS-TRG-12-001
1609.02366
14 CMS Collaboration The CMS experiment at the CERN LHC JINST 3 (2008) S08004 CMS-00-001
15 M. L. Mangano, M. Moretti, F. Piccinini, and M. Treccani Matching matrix elements and shower evolution for top-quark production in hadronic collisions JHEP 01 (2007) 013 hep-ph/0611129
16 P. Nason A new method for combining NLO QCD with shower Monte Carlo algorithms JHEP 11 (2004) 040 hep-ph/0409146
17 S. Frixione, P. Nason, and C. Oleari Matching NLO QCD computations with parton shower simulations: the POWHEG method JHEP 11 (2007) 070 0709.2092
18 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
19 S. Alioli, S.-O. Moch, and P. Uwer Hadronic top-quark pair-production with one jet and parton showering JHEP 01 (2012) 137 1110.5251
20 J. Alwall et al. Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions EPJC 53 (2008) 473 0706.2569
21 T. Sj\"ostrand, S. Mrenna, and P. Skands PYTHIA 6.4 physics and manual JHEP 05 (2006) 026 hep-ph/0603175
22 T. Sj\"ostrand, S. Mrenna, and P. Skands A brief introduction to PYTHIA 8.1 Comp. Phys. Comm. 178 (2008) 852 0710.3820
23 CMS Collaboration Event generator tunes obtained from underlying event and multiparton scattering measurements EPJC 76 (2016) 155 CMS-GEN-14-001
1512.00815
24 CMS Collaboration Measurement of $ \mathrm {t}\overline{\mathrm {t}} $ production with additional jet activity, including $ \mathrm {b} $ quark jets, in the dilepton decay channel using pp collisions at $ \sqrt{s} = $ 8 TeV EPJC 76 (2016) 379 CMS-TOP-12-041
1510.03072
25 NNPDF Collaboration Unbiased global determination of parton distributions and their uncertainties at NNLO and at LO Nucl. Phys. B 855 (2012) 153 1107.2652
26 GEANT4 Collaboration GEANT4---a simulation toolkit NIMA 506 (2003) 250
27 M. Czakon and A. Mitov Top++: A program for the calculation of the top-pair cross-section at hadron colliders CPC 185 (2014) 2930 1112.5675
28 M. Aliev et al. HATHOR: HAdronic Top and Heavy quarks crOss section calculatoR CPC 182 (2011) 1034 1007.1327
29 P. Kant et al. HatHor for single top-quark production: Updated predictions and uncertainty estimates for single top-quark production in hadronic collisions CPC 191 (2015) 74 1406.4403
30 J. M. Campbell, J. W. Huston, and W. J. Stirling Hard interactions of quarks and gluons: A primer for LHC physics Rept. Prog. Phys. 70 (2007) 89 hep-ph/0611148
31 CMS Collaboration Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at $ \sqrt{s} = $ 8 TeV JINST 10 (2015) P06005
32 CMS Collaboration Performance of CMS muon reconstruction in pp collision events at $ \sqrt{s} = $ 7 TeV JINST 7 (2012) P10002
33 M. Cacciari, G. P. Salam, and G. Soyez The anti-$ k_t $ jet clustering algorithm JHEP 04 (2008) 063 0802.1189
34 M. Cacciari, G. P. Salam, and G. Soyez FastJet user manual EPJC 72 (2012) 1896 1111.6097
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 Identification of b quark jets at the CMS Experiment in the LHC Run 2 CMS-PAS-BTV-15-001 CMS-PAS-BTV-15-001
37 CMS Collaboration Measurement of the $ \mathrm{ t \bar{t} }\ $ production cross section in the dilepton channel in pp collisions at $ \sqrt{s} = $ 7 TeV JHEP 11 (2012) 067
38 CMS Collaboration Measurements of inclusive W and Z cross sections in pp collisions at $ \sqrt{s} = $ 7 TeV JHEP 01 (2011) 080
39 CMS Collaboration Identification of b-quark jets with the CMS experiment JINST 8 (2013) P04013
40 CMS Collaboration Search for the associated production of the Higgs boson with a top-quark pair JHEP 09 (2014) 087
41 CMS Collaboration Measurement of the cross section ratio $ \sigma_\mathrm{t \bar{t} b \bar{b}} / \sigma_\mathrm{t \bar{t} jj } $ in pp collisions at $ \sqrt{s} = $ 8 TeV PLB 746 (2015) 132 CMS-TOP-13-010
1411.5621
42 L. Breiman, J. Friedman, R. A. Olshen, and C. J. Stone Chapman and Hall/CRC, 1984ISBN 0412048418, 9780412048418
43 H. J. Friedman Recent advances in predictive (machine) learning J. Classif. 23 (2006) 175
44 H. Voss, A. H\"ocker, J. Stelzer, and F. Tegenfeldt TMVA, the Toolkit for Multivariate Data Analysis with ROOT in XIth International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT), p. 40 2007 physics/0703039
45 J. D. Bjorken and S. J. Brodsky Statistical model for electron-positron annihilation into hadrons PRD 1 (1970) 1416
46 CMS Collaboration CMS luminosity measurement for the 2015 data-taking period CMS-PAS-LUM-15-001 CMS-PAS-LUM-15-001
47 M. Czakon, P. Fiedler, and A. Mitov Total Top-Quark Pair-Production Cross Section at Hadron Colliders through $ O(\alpha^4_S) $ PRL 110 (2013) 252004 1303.6254
48 CMS Collaboration Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV Submitted to JINST CMS-JME-13-004
1607.03663
49 L. Moneta et al. The RooStats Project in 13th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT2010), volume ACAT2010, p. 057 2010 1009.1003
50 A. L. Read Presentation of search results: the $ CL_{s} $ technique JPG 28 (2002) 2693
51 T. Junk Confidence level computation for combining searches with small statistics NIMA 434 (1999) 435 hep-ex/9902006
52 G. Cowan, K. Cranmer, E. Gross, and O. Vitells Asymptotic formulae for likelihood-based tests of new physics EPJC. 71 (2011) 1554 1007.1727
53 The ATLAS and CMS Collaborations and the LHC Higgs Combination Group Procedure for the LHC Higgs boson search combination in Summer 2011
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