Combined measurements of the production and decay rates of the Higgs boson, as well as its couplings to vector bosons and fermions, are presented. The analysis uses the LHC proton–proton collision data set recorded with the CMS detector in 2016 at s = 13 Te , corresponding to an integrated luminosity of 35.9 fb - 1 . The combination is based on analyses targeting the five main Higgs boson production mechanisms (gluon fusion, vector boson fusion, and associated production with a W or Z boson, or a top quark-antiquark pair) and the following decay modes: H → γ γ Z Z W W τ τ b b , and μ μ . Searches for invisible Higgs boson decays are also considered. The best-fit ratio of the signal yield to the standard model expectation is measured to be μ = 1.17 ± 0.10 , assuming a Higgs boson mass of 125.09 Ge . Additional results are given for various assumptions on the scaling behavior of the production and decay modes, including generic parametrizations based on ratios of cross sections and branching fractions or couplings. The results are compatible with the standard model predictions in all parametrizations considered. In addition, constraints are placed on various two Higgs doublet models.
G. Vesztergombi, G. Bolla: Deceased.
Understanding the mechanism behind electroweak symmetry breaking (EWSB) remains one of the main objectives of the physics program at the CERN LHC. In the standard model (SM) of particle physics [[
This paper describes combined measurements of the Higgs boson production rates, decay rates, and couplings using analyses of
Graph: Fig. 1Examples of leading-order Feynman diagrams for Higgs boson decays in the H→bbH→ττ , and H→μμ (upper left); H→ZZ and H→WW (upper right); and H→γγ (lower) channels
The analyses included in this combination target production via gluon fusion (
Graph: Fig. 2Examples of leading-order Feynman diagrams for the ggH (upper left), VBF (upper right), VH (lower left), and ttH (lower right) production modes
Graph: Fig. 3Examples of leading-order Feynman diagrams for the gg→ZH production mode
Graph: Fig. 4Examples of leading-order Feynman diagrams for tH production via the tHW (upper left and right) and tHq (lower) modes
For certain measurements in this paper, such as
The ATLAS and CMS Collaborations have published combined measurements of Higgs boson production rates, decay rates, and couplings with the
This paper is organized as follows: A brief description of the CMS detector is given in Sects. 2, 3 provides a summary of the various analyses included in the combination, and Sect. 4 describes the modifications made to these analyses to ensure a common signal and uncertainty model. Section 5 outlines the statistical procedure used to derive the results, and Sect. 6 outlines the treatment of the systematic uncertainties. Section 7 reports the results of the signal parametrizations in terms of signal strength modifiers and fiducial cross sections, while Sect. 8 describes the results obtained from an alternative set of signal parametrizations in terms of Higgs boson couplings. Section 9 details interpretations in terms of various two Higgs doublet models. The paper is summarized in Sect. 10.
The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity coverage provided by the barrel and endcap detectors. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outside the solenoid. A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [[
In this section, the individual analyses included in the combination are briefly described. More detailed information on each analysis can be found in the corresponding references. Many of the analyses split their primary data sample in multiple event categories with specific signatures that enhance the discrimination power between different Higgs boson production processes. This is achieved through selections that require the presence of additional leptons or jets, as expected in the decay of a
Summary of the event categories in the analyses included in this combination. The first column indicates the decay channel and the second column indicates the production mechanism targeted by an analysis. The third column provides the total number of categories per production tag, excluding control regions. Notes on the expected fractions of different Higgs signal production and decay modes with respect to the total signal yield in the given category are given in the fourth column. Where the numbers do not sum to 100%, the remaining contributions are from other signal production and decay processes. Finally, where relevant, the fifth column specifies the approximate expected relative mass resolution for the SM Higgs boson
Decay tags Production tags Number of categories Expected signal fractions Mass resolution Untagged 4 74–91% 3 51–80% 1 25% 2 64–83% 1 98% 1 59% 2 80–89% Untagged 3 6 3 3 3 3 17 2 6 1 22% 2 2 85–90% 0-jet 4 4 Boosted 4 1 2 Low- 2 High- 2 Boosted 6 10 4 1 1 96% 2 1 6 18 3 Search for S/B bins 15 56–96% Search for invisible 1 52% 1 80% 1 54% 1
The
Exclusive event categories are defined using dedicated selections based on additional reconstructed objects to separate the different Higgs boson production mechanisms. The presence of additional leptons,
In each event class, the background in the signal region (SR) is estimated from a fit to the observed
Despite the
To separate the different Higgs boson production mechanisms, the following categories are defined on the basis of the presence of jets,
In the
The
The analysis also includes categories that are sensitive to the associated production of the Higgs boson with a vector boson that decays leptonically. Two
When measuring the rate of Higgs boson production in the
The
The VBF category requires the presence of two additional jets with large
The
The
The main backgrounds come from
The
The main background component, QCD multijet production, is estimated from a signal-depleted Control Region (CR). The selected events are divided according to the jet
The dominant experimental uncertainties in this analysis are the uncertainties related to the extrapolation of the QCD multijet and top quark pair backgrounds from the CRs.
Measurements of the rate of the
The analysis of
- 2
- 3
- 4
The
- 1
- 2
- 3
In the
There are two analyses that target the associated production of the Higgs boson with a pair of top quarks in the
In the leptonic analysis, events are sorted into the
The all-hadronic final-state analysis selects events that contain at least seven jets, at least three of which are tagged as
The dominant experimental uncertainties in the measurement of the rate of
The
In each event category, the background is estimated from a fit to the observed
The direct search for the Higgs boson decaying into particles that cannot be detected provides a constraint on the invisible Higgs boson branching fraction (
Events selected in the
The
The observed upper limit on the branching fraction of
This section describes the changes in each analysis, as implemented for this combination, compared to their respective publications.
In order to consistently combine the various analyses, it is necessary to use the same theoretical predictions for the signal. The most significant difference between the input analyses is the modeling of the dominant
The
In the combination, many of the nuisance parameters originate from the use of a limited number of Monte Carlo events to determine SM signal and background expectations. Some of the input analyses have been modified to use the "Barlow-Beeston lite" approach, which assigns a single nuisance parameter per bin that scales the total bin yield [[
The overall statistical methodology used in this combination is the same as the one developed by the ATLAS and CMS Collaborations, and described in Ref. [[
The parameters of interest (POI)
Graph
The likelihood functions in the numerator and denominator of Eq. (
For each model considered, the maximum likelihood estimates
The likelihood functions are constructed with respect to either the observed data or an Asimov data set [[
Finally, the SM predictions for the production and decay rates of the Higgs boson depend on the mass of the Higgs boson,
For many of the POIs, the systematic uncertainties in their determination are expected to be as large as, or larger than, the statistical uncertainties. The theoretical uncertainties affecting the signal are among the most important contributions to the systematic uncertainties. The uncertainties in the total cross section prediction for the signal processes arising from the parton distribution functions, the renormalization and factorization scales used in the calculations and the branching fraction predictions are correlated between all input analyses. Instead, theoretical uncertainties that affect kinematic distributions and cause migrations between event categories are largely uncorrelated between the input analyses. An exception is the set of theoretical uncertainties for the
The majority of the systematic uncertainties arising from experimental sources are uncorrelated between the input analyses, with a few exceptions. The uncertainties in the integrated luminosity measurement [[
The free parameters describing the shapes and normalizations of the background models, and parameters that allow for the choice of the background parametrization in each of the
The signal strength modifier
2
Graph
respectively. Here
3
Graph
This parametrization makes use of the narrow width approximation, and the reliability of this approximation was studied in Ref. [[
In this section, results are presented for several signal strength parametrizations starting with a single global signal strength
The combined measurement of the common signal strength modifier at
4
Graph
where the total uncertainty has been decomposed into statistical, signal theoretical systematic, and other systematic components. The largest single source of uncertainty apart from the signal theoretical systematic uncertainties is the integrated luminosity (
Relaxing the assumption of a common production mode scaling, but still assuming the relative SM branching fractions, leads to a parametrization with five production signal strength modifiers:
Graph: Fig. 5Summary plot of the fit to the per-production mode (left) and per-decay mode (right) signal strength modifiers. The thick and thin horizontal bars indicate the ±1σ and ±2σ uncertainties, respectively. Also shown are the ±1σ systematic components of the uncertainties. The last point in the per-production mode summary plot is taken from a separate fit and indicates the result of the combined overall signal strength μ
Best fit values and ±1σ uncertainties for the parametrizations with per-production mode and per-decay mode signal strength modifiers. The expected uncertainties are given in brackets
Production process Best fit value Uncertainty stat. syst. 1.22 0.73 2.18 0.87 1.18
Best fit values and ±1σ uncertainties for the parametrizations with per-production mode and per-decay mode signal strength modifiers. The expected uncertainties are given in brackets
Decay mode Best fit value Uncertainty stat. syst. 1.12 1.02 1.28 1.06 1.20 0.68
The improvement in the precision of the measurement of the
The most generic signal strength parametrization has one signal strength parameter for each production and decay mode combination,
Graph: Fig. 6Summary plot of the fit to the production–decay signal strength products μif=μiμf. The points indicate the best fit values while the horizontal bars indicate the 1σCL intervals. The hatched areas indicate signal strengths that are restricted to nonnegative values as described in the text
Best fit values and ±1σ uncertainties for the parameters of the model with one signal strength parameter for each production and decay mode combination. The entries in the table represent the parameter μif=μiμf, where i is indicated by the column and f by the row. The expected uncertainties are given in brackets. Some of the signal strengths are restricted to nonnegative values, as described in the text
Decay mode Production process Best fit Uncertainty Best fit Uncertainty Best fit Uncertainty Best fit Uncertainty Best fit Uncertainty value stat syst value stat syst value stat syst value stat syst value stat syst 2.51 1.73 0.99 0.91 1.05 1.12 0.23 1.35 0.28 3.91 0.96 1.60 1.22 0.00 0.00 0.00 1.16 0.67 3.76 0.00 2.18 0.31 2.72
Results are presented for a model based on the ratios of cross sections and branching fractions. These are given relative to a well-measured reference process, chosen to be
Graph: Fig. 7Summary of the cross section and branching fraction ratio model. The thick and thin horizontal bars indicate the ±1σ and ±2σ uncertainties, respectively. Also shown are the ±1σ systematic components of the uncertainties
Best fit values and ±1σ uncertainties for the parameters of the cross section and branching fraction ratio model. The expected uncertainties are given in brackets
Parameter Best fit Uncertainty Parameter Best fit Uncertainty stat syst stat syst 1.07 0.84 0.60 1.07 2.19 1.23 0.88 1.14 1.06 0.63
Measurements of production cross sections, which are complementary to the signal strength parametrization, are made for seven processes defined according to the simplified template cross sections proposed in Ref. [[
-
53 ]] proposes separate bins for these modes, they are merged here because of the current lack of sensitivity to the associated production with -
-
-
53 ]] proposes separate bins for the quark- and gluon-initiated modes, they are merged here because they cannot easily be distinguished experimentally, and therefore, their measurements would be highly anticorrelated. -
-
53 ]] proposes separate bins for these modes, they are merged here because of the lack of a dedicated analysis targeting
In addition to the cross sections, the Higgs boson branching fractions are also included as POIs via ratios with respect to
Graph: Fig. 8Summary of the stage 0 model, ratios of cross sections and branching fractions. The points indicate the best fit values, while the error bars show the ±1σ and ±2σ uncertainties. The ±1σ uncertainties on the measurements considering only the contributions from the systematic uncertainties are also shown. The uncertainties in the SM predictions are indicated
Best fit values and ±1σ uncertainties for the parameters of the stage 0 simplified template cross section model. The values are all normalized to the SM predictions. The expected uncertainties are given in brackets
Parameter Best fit Uncertainty Parameter Best fit Uncertainty stat syst stat syst 1.00 0.96 0.66 0.98 3.93 1.30 1.95 1.14 0.84 0.67 1.08
In the
5
Graph
where
6
Graph
In the SM, all
The normalization scaling effects of each of the
Normalization scaling factors for all relevant production cross sections and decay partial widths. For the κ parameters representing loop processes, the resolved scaling in terms of the fundamental SM couplings is also given
Effective Loops Interference scaling factor Resolved scaling factor Production Partial decay width Total width for
Under the assumption that there are no BSM particles contributing to the
Graph: Fig. 9Summary of the κ -framework model assuming resolved loops and BBSM=0. The points indicate the best fit values while the thick and thin horizontal bars show the 1σ and 2σCL intervals, respectively. In this model, the ggH and H→γγ loops are resolved in terms of the remaining coupling modifiers. For this model, both positive and negative values of κWκZ , and κb are considered. Negative values of κW in this model are disfavored by more than 2σ
The rate of the
An additional fit is performed using a phenomenological parametrization relating the masses of the fermions and vector bosons to the corresponding
The lepton and vector boson mass values are taken from Ref. [[
The
Graph: Fig. 10Likelihood scan in the M - ϵ plane (left). The best fit point and the 1σ and 2σCL regions are shown, along with the SM prediction. Result of the phenomenological (M,ϵ) fit overlayed with the resolved κ -framework model (right)
Best fit values and ±1σ uncertainties for the parameters of the κ model in which the loop processes are resolved. The expected uncertainties are given in brackets
Parameter Best fit value Uncertainty stat. syst. 1.10 0.99 1.11 1.01 0.79
The results of the fits to the generic
7
Graph
where
Graph: Fig. 11Summary plots for the κ -framework model in which the ggH and H→γγ loops are scaled with effective couplings. The points indicate the best fit values while the thick and thin horizontal bars show the 1σ and 2σCL intervals, respectively. In the left figure the constraint BBSM=0 is imposed, and both positive and negative values of κW and κZ are considered. In the right figure a constraint |κW|,|κZ|≤1 is imposed (same sign of κW and κZ), while Binv>0 and Bundet>0 are free parameters
Best fit values and ±1σ uncertainties for the parameters of the κ-framework model with effective loops. The expected uncertainties are given in brackets
Parameter Best fit Uncertainty Parameter Best fit Uncertainty stat syst stat syst 1.00 0.98 1.02 1.02 0.93 1.17 0.91 1.18 1.16 1.07 0.96 0.80 0.72 0.07 0.00
Two different model assumptions are made concerning the BSM branching fraction. In the first parametrization, it is assumed that
Graph: Fig. 12Results within the generic κ -framework model with effective loops and with the constraint |κW|,|κZ|≤1 (same sign of κW and κZ), and with Binv>0 and Bundet>0 as free parameters. Scan of the test statistic q as a function of Binv (left), and 68 and 95% CL regions for Binv vs. Bundet (right). The scan of the test statistic q as a function of Binv expected assuming the SM is also shown in the left figure
In both of the generic
Graph: Fig. 13Scan of the test statistic q as a function of κW in the generic κ model assuming BBSM=0 (left) and allowing Binv and Bundet to float (right). The different colored lines indicate the value of q for different combinations of signs for κW and κZ. The solid black line shows the minimum value of q(κW) in each case and is used to determine the best fit point and the 1σ and 2σCL regions. The scan in the right figure is truncated because of the constraints of |κW|≤1 and |κZ|≤1 , which are imposed in this model
The preferred negative value of
Using Eq. (
An additional fit is performed assuming that the only BSM contributions to the Higgs couplings appear in the loop-induced
Graph: Fig. 14The scan of the test statistic q as a function of ΓH/ΓHSM obtained by reinterpreting the model allowing for BSM decays of the Higgs boson. The expected scan of q as a function of ΓH/ΓHSM assuming the SM is also shown
Graph: Fig. 15The 1σ and 2σCL regions in the κg vs. κγ parameter space for the model assuming the only BSM contributions to the Higgs boson couplings appear in the loop-induced processes or in BSM Higgs decays
An analogous parametrization to the ratios of cross sections and branching fractions described in the previous section can be derived in terms of ratios of the coupling modifiers (
Graph: Fig. 16Summary of the model with coupling ratios and effective couplings for the ggH and H→γγ loops. The points indicate the best fit values while the thick and thin horizontal bars show the 1σ and 2σCL intervals, respectively. For this model, both positive and negative values of λWZ and λtg are considered
Best fit values and ±1σ uncertainties for the parameters of the coupling modifier ratio model. The expected uncertainties are given in brackets
Parameter Best fit Uncertainty Parameter Best fit Uncertainty stat syst stat syst 1.03 1.07 1.17 0.83 1.02 0.85 0.81
A more constrained version of the loop-resolved
Graph: Fig. 17The 1σ and 2σCL regions in the κF vs. κV parameter space for the model assuming a common scaling of all the vector boson and fermion couplings
Best fit values and ±1σ uncertainties for the parameters of the κV,κF model. The expected uncertainties are given in brackets
Parameter Best fit Uncertainty Parameter Best fit Uncertainty stat syst stat syst 1.10 1.49 0.96 1.15 1.01 1.10 0.98 1.10 1.14
Several BSM models predict the existence of an extended Higgs sector. In such scenarios, the couplings to up-and down-type fermions, or to leptons and quarks, can be separately modified. In order to probe such models, parametrizations are introduced in which the couplings of the Higgs boson to fermions are scaled either by separate common modifiers for up-type (
Figure 18 shows the results of the fits where the ratio of the couplings to up- and down-type fermions
Graph: Fig. 18Summary plots of the 3-parameter models comparing up- and down-type fermions, and floating the ratio of the vector coupling to the up-type coupling (left) and comparing lepton and quark couplings (right). The points indicate the best fit values while the thick and thin horizontal bars show the 1σ and 2σCL intervals, respectively. Both positive and negative values of λduλVuλlq , and λVq are considered
Best fit values and ±1σ uncertainties for the parameters of the two benchmark models with resolved loops to test the symmetry of fermion couplings. The expected uncertainties are given in brackets
Best fit Uncertainty Best fit Uncertainty Best fit Uncertainty value stat syst value stat syst value stat syst 0.97 0.92 1.14
Best fit values and ±1σ uncertainties for the parameters of the two benchmark models with resolved loops to test the symmetry of fermion couplings. The expected uncertainties are given in brackets
Best fit Uncertainty Best fit Uncertainty Best fit Uncertainty value stat syst value stat syst value stat syst 0.99 0.92 1.10
Table 12 shows a summary of the compatibility of the different models considered, as described in Sects. 7 and 8, with the SM predictions. For each model, the value of q at the values of the POIs for the SM expectation (
Compatibility of the fit results with the SM prediction under various signal parametrizations. The value of q at the values of the POIs for which the SM expectation is obtained (qSM) is shown along with the corresponding p-value, with respect to the SM, assuming q is distributed according to a χ2 function with the specified number of degrees of freedom (DOF)
Parameterization DOF Parameters of interest Global signal strength 6.28% (3.46) 1 Production processes 9.87% (9.27) 5 Decay modes 53.8% (5.05) 6 61.2% (21.5) 24 Ratios of 32.3% (11.5) 10 Simplified template cross sections with branching fractions relative to 21.2% (14.4) 11 Couplings, SM loops 45.6% (5.71) 6 Couplings vs. mass 16.8% (3.57) 2 Couplings, BSM loops 18.5% (11.3) 8 Couplings, BSM loops and decays including 32.4% (11.5) 10 Ratios of coupling modifiers 18.1% (11.4) 8 Fermion and vector couplings 16.9% (3.55) 2 Fermion and vector couplings, per decay mode 76.7% (8.2) 12 Up vs. down-type couplings 25.5% (4.06) 3 Lepton vs. quark couplings 27.2% (3.91) 3
The generic models described in Sect. 8.5 can also be interpreted in the context of explicit benchmark BSM models that contain a second Higgs doublet (2HDM) [[
The minimal supersymmetric standard model (MSSM) [[
Modifications to the couplings of the Higgs bosons to up-type (κu) and down-type (κd) fermions, and vector bosons (κV), with respect to the SM expectation, in 2HDM and for the hMSSM. The coupling modifications for the hMSSM are completed by the expressions for su and sd, as given by Eqs. (
Type I Type II Type III Type IV
8
Graph
9
Graph
To set constraints on the 2HDM model parameters, 3-dimensional likelihood scans of the parametrizations described in Sect. 8.5 (with necessary modifications to the lepton coupling modifiers to describe the Type IV 2HDM) are performed. A test-statistic is then defined, for example in the Types I, II and hMSSM scenarios,
10
Graph
where
A second quantity
11
Graph
where
Figure 19 shows the results of the fits for the different 2HDM benchmark scenarios. The lobe features that can be seen in the Types II, III, and IV constraints for
The results for the hMSSM scenario are also shown in Fig. 19. The constraints observed are more stringent than those expected under the SM. This is due to the best fit value of
Graph: Fig. 19Constraints in the cos(β-α) vs. tanβ plane for the Types I, II, III, and IV 2HDM, and constraints in the mA vs. tanβ plane for the hMSSM. The white regions, bounded by the solid black lines, in each plane represent the regions of the parameter space that are allowed at the 95% CL , given the data observed. The dashed lines indicate the boundaries of the allowed regions expected for the SM Higgs boson
The constraints in the 2HDM and hMSSM scenarios are complementary to those obtained from direct searches for additional Higgs bosons [[
A set of combined measurements of Higgs boson production and decay rates has been presented, along with the consequential constraints placed on its couplings to standard model (SM) particles, and on the parameter spaces of several beyond the standard model (BSM) scenarios. The combination is based on analyses targeting the gluon fusion and vector boson fusion production modes, and associated production with a vector boson or a pair of top quarks. The analyses included in the combination target Higgs boson production in the
Measurements of the Higgs boson production cross section times branching fractions are presented, along with a generic parametrization in terms of ratios of production cross sections and branching fractions, which makes no assumptions about the Higgs boson total width. The combined signal yield relative to the SM prediction has been measured as
We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: the Austrian Federal Ministry of Science, Research and Economy and the Austrian Science Fund; the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research Promotion Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Ministry of Education and Research, Estonian Research Council via IUT23-4 and IUT23-6 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucléaire et de Physique des Particules / CNRS, and Commissariat à l'Énergie Atomique et aux Énergies Alternatives / CEA, France; the Bundesministerium für Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; the National Research, Development and Innovation Fund, Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Lithuanian Academy of Sciences; the Ministry of Education, and University of Malaya (Malaysia); the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI); the Ministry of Business, Innovation and Employment, New Zealand; the Pakistan Atomic Energy Commission; the Ministry of Science and Higher Education and the National Science Centre, Poland; the Fundação para a Ciência e a Tecnologia, Portugal; JINR, Dubna; the Ministry of Education and Science of the Russian Federation, the Federal Agency of Atomic Energy of the Russian Federation, Russian Academy of Sciences, the Russian Foundation for Basic Research and the Russian Competitiveness Program of NRNU "MEPhI"; the Ministry of Education, Science and Technological Development of Serbia; the Secretaría de Estado de Investigación, Desarrollo e Innovación, Programa Consolider-Ingenio 2010, Plan Estatal de Investigación Científica y Técnica y de Innovación 2013–2016, Plan de Ciencia, Tecnología e Innovación 2013–2017 del Principado de Asturias and Fondo Europeo de Desarrollo Regional, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the Ministry of Science and Technology, Taipei; the Thailand Center of Excellence in Physics, the Institute for the Promotion of Teaching Science and Technology of Thailand, Special Task Force for Activating Research and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the National Academy of Sciences of Ukraine, and State Fund for Fundamental Researches, Ukraine; the Science and Technology Facilities Council, UK; the US Department of Energy, and the US National Science Foundation. Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, Contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - EOS" - be.h project n. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület ("Momentum") Programme and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA Research Grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the Council of Scientific and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa de Excelencia María de Maeztu and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its second Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).
This manuscript has no associated data or the data will not be deposited. [Authors' comment: Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS policy as written in its document "CMS data preservation, re-use and open access policy" (https://cmsdocdb.cern.ch/cgi-bin/PublicDocDB/RetrieveFile?docid=6032&filename=CMSDataPolicyV1.2.pdf&version=2).]
By A. M. Sirunyan; A. Tumasyan; W. Adam; F. Ambrogi; E. Asilar; T. Bergauer; J. Brandstetter; M. Dragicevic; J. Erö; A. Escalante Del Valle; M. Flechl; R. Frühwirth; V. M. Ghete; J. Hrubec; M. Jeitler; N. Krammer; I. Krätschmer; D. Liko; T. Madlener; I. Mikulec; N. Rad; H. Rohringer; J. Schieck; R. Schöfbeck; M. Spanring; D. Spitzbart; A. Taurok; W. Waltenberger; J. Wittmann; C.-E. Wulz; M. Zarucki; V. Chekhovsky; V. Mossolov; J. Suarez Gonzalez; E. A. De Wolf; D. Di Croce; X. Janssen; J. Lauwers; M. Pieters; H. Van Haevermaet; P. Van Mechelen; N. Van Remortel; S. Abu Zeid; F. Blekman; J. D'Hondt; I. De Bruyn; J. De Clercq; K. Deroover; G. Flouris; D. Lontkovskyi; S. Lowette; I. Marchesini; S. Moortgat; L. Moreels; Q. Python; K. Skovpen; S. Tavernier; W. Van Doninck; P. Van Mulders; I. Van Parijs; D. Beghin; B. Bilin; H. Brun; B. Clerbaux; G. De Lentdecker; H. Delannoy; B. Dorney; G. Fasanella; L. Favart; R. Goldouzian; A. Grebenyuk; A. K. Kalsi; T. Lenzi; J. Luetic; N. Postiau; E. Starling; L. Thomas; C. Vander Velde; P. Vanlaer; D. Vannerom; Q. Wang; T. Cornelis; D. Dobur; A. Fagot; M. Gul; I. Khvastunov; D. Poyraz; C. Roskas; D. Trocino; M. Tytgat; W. Verbeke; B. Vermassen; M. Vit; N. Zaganidis; H. Bakhshiansohi; O. Bondu; S. Brochet; G. Bruno; C. Caputo; P. David; C. Delaere; M. Delcourt; B. Francois; A. Giammanco; G. Krintiras; V. Lemaitre; A. Magitteri; A. Mertens; M. Musich; K. Piotrzkowski; A. Saggio; M. Vidal Marono; S. Wertz; J. Zobec; F. L. Alves; G. A. Alves; M. Correa Martins Junior; G. Correia Silva; C. Hensel; A. Moraes; M. E. Pol; P. Rebello Teles; E. Belchior Batista Das Chagas; W. Carvalho; J. Chinellato; E. Coelho; E. M. Da Costa; G. G. Da Silveira; D. De Jesus Damiao; C. De Oliveira Martins; S. Fonseca De Souza; H. Malbouisson; D. Matos Figueiredo; M. Melo De Almeida; C. Mora Herrera; L. Mundim; H. Nogima; W. L. Prado Da Silva; L. J. Sanchez Rosas; A. Santoro; A. Sznajder; M. Thiel; E. J. Tonelli Manganote; F. Torres Da Silva De Araujo; A. Vilela Pereira; S. Ahuja; C. A. Bernardes; L. Calligaris; T. R. Fernandez Perez Tomei; E. M. Gregores; P. G. Mercadante; S. F. Novaes; SandraS. Padula; A. Aleksandrov; R. Hadjiiska; P. Iaydjiev; A. Marinov; M. Misheva; M. Rodozov; M. Shopova; G. Sultanov; A. Dimitrov; L. Litov; B. Pavlov; P. Petkov; W. Fang; X. Gao; L. Yuan; M. Ahmad; J. G. Bian; G. M. Chen; H. S. Chen; M. Chen; Y. Chen; C. H. Jiang; D. Leggat; H. Liao; Z. Liu; F. Romeo; S. M. Shaheen; A. Spiezia; J. Tao; C. Wang; Z. Wang; E. Yazgan; H. Zhang; S. Zhang; J. Zhao; Y. Ban; G. Chen; A. Levin; J. Li; L. Li; Q. Li; Y. Mao; S. J. Qian; D. Wang; Z. Xu; Y. Wang; C. Avila; A. Cabrera; C. A. Carrillo Montoya; L. F. Chaparro Sierra; C. Florez; C. F. González Hernández; M. A. Segura Delgado; B. Courbon; N. Godinovic; D. Lelas; I. Puljak; T. Sculac; Z. Antunovic; M. Kovac; V. Brigljevic; D. Ferencek; K. Kadija; B. Mesic; A. Starodumov; T. Susa; M. W. Ather; A. Attikis; M. Kolosova; G. Mavromanolakis; J. Mousa; C. Nicolaou; F. Ptochos; P. A. Razis; H. Rykaczewski; M. Finger; M. Finger; E. Ayala; E. Carrera Jarrin; H. Abdalla; A. A. Abdelalim; E. Salama; S. Bhowmik; A. Carvalho Antunes De Oliveira; R. K. Dewanjee; K. Ehataht; M. Kadastik; M. Raidal; C. Veelken; P. Eerola; H. Kirschenmann; J. Pekkanen; M. Voutilainen; J. Havukainen; J. K. Heikkilä; T. Järvinen; V. Karimäki; R. Kinnunen; T. Lampén; K. Lassila-Perini; S. Laurila; S. Lehti; T. Lindén; P. Luukka; T. Mäenpää; H. Siikonen; E. Tuominen; J. Tuominiemi; T. Tuuva; M. Besancon; F. Couderc; M. Dejardin; D. Denegri; J. L. Faure; F. Ferri; S. Ganjour; A. Givernaud; P. Gras; G. Hamel de Monchenault; P. Jarry; C. Leloup; E. Locci; J. Malcles; G. Negro; J. Rander; A. Rosowsky; M. Ö. Sahin; M. Titov; A. Abdulsalam; C. Amendola; I. Antropov; F. Beaudette; P. Busson; C. Charlot; R. Granier de Cassagnac; I. Kucher; A. Lobanov; J. Martin Blanco; M. Nguyen; C. Ochando; G. Ortona; P. Paganini; P. Pigard; R. Salerno; J. B. Sauvan; Y. Sirois; A. G. Stahl Leiton; A. Zabi; A. Zghiche; J.-L. Agram; J. Andrea; D. Bloch; J.-M. Brom; E. C. Chabert; V. Cherepanov; C. Collard; E. Conte; J.-C. Fontaine; D. Gelé; U. Goerlach; M. Jansová; A.-C. Le Bihan; N. Tonon; P. Van Hove; S. Gadrat; S. Beauceron; C. Bernet; G. Boudoul; N. Chanon; R. Chierici; D. Contardo; P. Depasse; H. El Mamouni; J. Fay; L. Finco; S. Gascon; M. Gouzevitch; G. Grenier; B. Ille; F. Lagarde; I. B. Laktineh; H. Lattaud; M. Lethuillier; L. Mirabito; A. L. Pequegnot; S. Perries; A. Popov; V. Sordini; G. Touquet; M. Vander Donckt; S. Viret; A. Khvedelidze; Z. Tsamalaidze; C. Autermann; L. Feld; M. K. Kiesel; K. Klein; M. Lipinski; M. Preuten; M. P. Rauch; C. Schomakers; J. Schulz; M. Teroerde; B. Wittmer; V. Zhukov; A. Albert; D. Duchardt; M. Endres; M. Erdmann; S. Ghosh; A. Güth; T. Hebbeker; C. Heidemann; K. Hoepfner; H. Keller; L. Mastrolorenzo; M. Merschmeyer; A. Meyer; P. Millet; S. Mukherjee; T. Pook; M. Radziej; H. Reithler; M. Rieger; A. Schmidt; D. Teyssier; G. Flügge; O. 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Walsh; Y. Wen; K. Wichmann; C. Wissing; O. Zenaiev; R. Aggleton; S. Bein; L. Benato; A. Benecke; V. Blobel; M. Centis Vignali; T. Dreyer; E. Garutti; D. Gonzalez; J. Haller; A. Hinzmann; A. Karavdina; G. Kasieczka; R. Klanner; R. Kogler; N. Kovalchuk; S. Kurz; V. Kutzner; J. Lange; D. Marconi; J. Multhaup; M. Niedziela; D. Nowatschin; A. Perieanu; A. Reimers; O. Rieger; C. Scharf; P. Schleper; S. Schumann; J. Schwandt; J. Sonneveld; H. Stadie; G. Steinbrück; F. M. Stober; M. Stöver; A. Vanhoefer; B. Vormwald; I. Zoi; M. Akbiyik; C. Barth; M. Baselga; S. Baur; E. Butz; R. Caspart; T. Chwalek; F. Colombo; W. De Boer; A. Dierlamm; K. El Morabit; N. Faltermann; B. Freund; M. Giffels; M. A. Harrendorf; F. Hartmann; S. M. Heindl; U. Husemann; F. Kassel; I. Katkov; S. Kudella; H. Mildner; S. Mitra; M. U. Mozer; Th. Müller; M. Plagge; G. Quast; K. Rabbertz; M. Schröder; I. Shvetsov; G. Sieber; H. J. Simonis; R. Ulrich; S. Wayand; M. Weber; T. Weiler; S. Williamson; C. Wöhrmann; R. Wolf; G. 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Felcini; M. Grunewald; M. Abbrescia; C. Calabria; A. Colaleo; D. Creanza; L. Cristella; N. De Filippis; M. De Palma; A. Di Florio; F. Errico; L. Fiore; A. Gelmi; G. Iaselli; M. Ince; S. Lezki; G. Maggi; M. Maggi; G. Miniello; S. My; S. Nuzzo; A. Pompili; G. Pugliese; R. Radogna; A. Ranieri; G. Selvaggi; A. Sharma; L. Silvestris; R. Venditti; P. Verwilligen; G. Zito; G. Abbiendi; C. Battilana; D. Bonacorsi; L. Borgonovi; S. Braibant-Giacomelli; R. Campanini; P. Capiluppi; A. Castro; F. R. Cavallo; S. S. Chhibra; C. Ciocca; G. Codispoti; M. Cuffiani; G. M. Dallavalle; F. Fabbri; A. Fanfani; P. Giacomelli; C. Grandi; L. Guiducci; F. Iemmi; S. Marcellini; G. Masetti; A. Montanari; F. L. Navarria; A. Perrotta; F. Primavera; A. M. Rossi; T. Rovelli; G. P. Siroli; N. Tosi; S. Albergo; A. Di Mattia; R. Potenza; A. Tricomi; C. Tuve; G. Barbagli; K. Chatterjee; V. Ciulli; C. Civinini; R. D'Alessandro; E. Focardi; G. Latino; P. Lenzi; M. Meschini; S. Paoletti; L. Russo; G. Sguazzoni; D. 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Vitulo; M. Biasini; G. M. Bilei; C. Cecchi; D. Ciangottini; L. Fanò; P. Lariccia; R. Leonardi; E. Manoni; G. Mantovani; V. Mariani; M. Menichelli; A. Rossi; A. Santocchia; D. Spiga; K. Androsov; P. Azzurri; G. Bagliesi; L. Bianchini; T. Boccali; L. Borrello; R. Castaldi; M. A. Ciocci; R. Dell'Orso; G. Fedi; F. Fiori; L. Giannini; A. Giassi; M. T. Grippo; F. Ligabue; E. Manca; G. Mandorli; A. Messineo; F. Palla; A. Rizzi; P. Spagnolo; R. Tenchini; G. Tonelli; A. Venturi; P. G. Verdini; L. Barone; F. Cavallari; M. Cipriani; D. Del Re; E. Di Marco; M. Diemoz; S. Gelli; E. Longo; B. Marzocchi; P. Meridiani; G. Organtini; F. Pandolfi; R. Paramatti; F. Preiato; S. Rahatlou; C. Rovelli; F. Santanastasio; N. Amapane; R. Arcidiacono; S. Argiro; M. Arneodo; N. Bartosik; R. Bellan; C. Biino; N. Cartiglia; F. Cenna; S. Cometti; M. Costa; R. Covarelli; N. Demaria; B. Kiani; C. Mariotti; S. Maselli; E. Migliore; V. Monaco; E. Monteil; M. Monteno; M. M. Obertino; L. Pacher; N. Pastrone; M. Pelliccioni; G. L. Pinna Angioni; A. Romero; M. Ruspa; R. Sacchi; K. Shchelina; V. Sola; A. Solano; D. Soldi; A. Staiano; S. Belforte; V. Candelise; M. Casarsa; F. Cossutti; A. Da Rold; G. Della Ricca; F. Vazzoler; A. Zanetti; D. H. Kim; G. N. Kim; M. S. Kim; J. Lee; S. Lee; S. W. Lee; C. S. Moon; Y. D. Oh; S. Sekmen; D. C. Son; Y. C. Yang; H. Kim; D. H. Moon; G. Oh; J. Goh; T. J. Kim; S. Cho; S. Choi; Y. Go; D. Gyun; S. Ha; B. Hong; Y. Jo; K. Lee; K. S. Lee; J. Lim; S. K. Park; Y. Roh; H. S. Kim; J. Almond; J. Kim; J. S. Kim; H. Lee; K. Nam; S. B. Oh; B. C. Radburn-Smith; S. h. Seo; U. K. Yang; H. D. Yoo; G. B. Yu; D. Jeon; J. H. Kim and J. S. H. Lee
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