Search for resonant and nonresonant Higgs boson pair production in the \( \mathrm{b}\overline{\mathrm{b}}\mathit{\ell \nu \ell \nu } \) final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Journal of High Energy Physics, Jan 2018

Searches for resonant and nonresonant pair-produced Higgs bosons (HH) decaying respectively into ℓνℓν, through either W or Z bosons, and \( \mathrm{b}\overline{\mathrm{b}} \) are presented. The analyses are based on a sample of proton-proton collisions at \( \sqrt{s}=13 \) TeV, collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb−1. Data and predictions from the standard model are in agreement within uncertainties. For the standard model HH hypothesis, the data exclude at 95% confidence level a product of the production cross section and branching fraction larger than 72 fb, corresponding to 79 times the standard model prediction. Constraints are placed on different scenarios considering anomalous couplings, which could affect the rate and kinematics of HH production. Upper limits at 95% confidence level are set on the production cross section of narrow-width spin-0 and spin-2 particles decaying to Higgs boson pairs, the latter produced with minimal gravity-like coupling.

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Search for resonant and nonresonant Higgs boson pair production in the \( \mathrm{b}\overline{\mathrm{b}}\mathit{\ell \nu \ell \nu } \) final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV

Hlb( 13 TeV Search for resonant and nonresonant Higgs boson pair Searches for resonant and nonresonant pair-produced Higgs bosons (HH) deanalyses are based on a sample of proton-proton collisions at p caying respectively into ` ` , through either W or Z bosons, and bb are presented. The the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb 1. Data and predictions from the standard model are in agreement within uncertainties. For the standard model HH hypothesis, the data exclude at 95% con dence level a product of the production cross section and branching fraction larger than 72 fb, corresponding to 79 times the standard model prediction. Constraints are placed on di erent scenarios considering anomalous couplings, which could a ect the rate and kinematics of HH production. Upper limits at 95% con dence level are set on the production cross section of narrowwidth spin-0 and spin-2 particles decaying to Higgs boson pairs, the latter produced with minimal gravity-like coupling. Hadron-Hadron scattering (experiments); Higgs physics - collisions at nal state in proton-proton The CMS collaboration 1 Introduction 2 The CMS detector 3 Event simulation 6 Systematic uncertainties 7 Results 7.1 7.2 Resonant production Nonresonant production 8 Summary The CMS collaboration 4 Event selection and background predictions 5 Parameterised multivariate discriminators for signal extraction and four-point interactions will provide an indication of the scalar potential structure. Nonresonant Higgs boson pair production (HH) can be used to directly study the Higgs boson self-coupling. At the CERN LHC, Higgs boson pairs are predominantly produced through gluon-gluon fusion via two destructively interfering diagrams, shown in gure 1. In the SM the destructive interference between these two diagrams makes the observation of HH production extremely challenging, even in the most optimistic scenarios of energy and integrated luminosity at the future High Luminosity LHC [10, 11]. The SM cross section for HH production in proton-proton collisions at p s = 13 TeV for a Higgs boson mass of 125 GeV is HH = 33:5 fb at next-to-next-to-leading order (NNLO) in quantum chromodynamics (QCD) for the gluon-gluon fusion process [12{21]. { 1 { Indirect e ects at the electroweak scale arising from beyond the standard model (BSM) phenomena at a higher scale can be parameterised in an e ective eld theory framework [22{24] by introducing coupling modi ers for the SM parameters involved in HH production, namely = = SM for the Higgs boson self-coupling and t = yt=ytSM for the top quark Yukawa coupling yt. Such modi cations of the Higgs boson couplings could enhance Higgs boson pair production to rates observable with the current dataset. The relevant part of the modi ed Lagrangian takes the form: 1 2 LH = m2HH2 SM v H3 v mt (v + t H) (tLtR + h.c.); (1.1) where H is the Higgs boson eld, v is the vacuum expectation value of H, mt is the top quark mass, tL and tR are the left- and right-handed top quark elds, and h.c. is the Hermitian conjugate. The appearance of new contact-like interactions, not considered in this paper, could also result in an enhancement of HH production. Extensions of the scalar sector of the SM postulate the existence of additional Higgs bosons. An explored scenario is the two-Higgs-doublet model (2HDM) [25], where a second doublet of complex scalar elds is added to the SM scalar sector Lagrangian. The generic 2HDM potential has a large number of degrees of freedom, which can be reduced to six under speci c assumptions. In case the new CP-even state is massive enough (mass larger than 2mH) it can decay to a pair of Higgs bosons. Models inspired by warped extra dimensions [26] predict the existence of new heavy particles that can decay to pairs of Higgs bosons. Examples of such particles are the radion (spin 0) [27{30] or the rst Kaluza-Klein (KK) excitation of the graviton (spin 2) [31, 32]. In the following, we will use X to denote a generic state decaying into pairs of Higgs bosons. Searches for Higgs boson pair production have been performed by the ATLAS and in p s = 8 TeV [33{37] and 13 TeV data [38, 39]. CMS experiments using LHC proton-proton collision data. These include searches for BSM production as well as more targeted searches for production with SM-like kinematics This paper reports on a search for Higgs boson pair production, HH, and resonant Higgs boson pair production, X ! HH, where one of the H decays into bb, and the other into Z(``)Z( ) or W(` )W(` ), where ` is either an electron, a muon, or a tau lepton that decays leptonically. The search is based on LHC proton-proton collision data at s = 13 TeV collected by the CMS experiment, corresponding to an integrated luminosity . The analysis focuses on the invariant mass distribution of the b jet pairs, searching for a resonant-like excess compatible with the Higgs boson mass, in combination with an arti cial neural network discriminator based on kinematic information. The dominant background is tt production, with smaller contributions from Drell-Yan (DY) and single top quark production. 2 The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic eld of 3.8 T. Within the solenoid volume are a silicon pixel { 2 { g t, b κt H κ λ t, b coupling modi ers for the Higgs boson self-coupling and the top quark Yukawa coupling are denoted ) and H ! W(` )W(` ) decay chains, leading to a total branching fraction B(HH ! bbVV ! bb` ` ) of 2.7% [12]. The event generators used for both signal and background samples are interfaced with pythia 8.212 [51, 52] for simulation of the par{ 3 { ton showering, hadronisation, and underlying event using the CUETP8M1 tune [53]. The NNPDF 3.0 [54] LO and NLO Parton Distribution Functions (PDF) are used. For all processes, the detector response is simulated using a detailed description of the CMS apparatus, based on the Geant4 package [55]. Additional pp interactions in the same and in the neighbouring bunch crossings (pileup) are generated with pythia and overlapped with the simulated events of interest to reproduce the pileup measured in data. All background processes are normalised to their most accurate theoretical cross sections. The tt, DY, single top quark and W+W samples are normalised to NNLO precision in QCD [56{59], while remaining diboson, triboson and ttV processes are normalised to NLO precision in QCD [46, 60]. The single Higgs boson production cross section is \tag-and-probe" technique [61] as a function of lepton pT and in a data control region consisting of Z ! `` events. Events with two oppositely charged leptons (e+e , + , e ) are selected using asymmetric pT requirements, chosen to be above the corresponding trigger thresholds, for leading and subleading leptons of 25 GeV and 15 GeV for ee and e events, 20 GeV and 10 GeV for events, and 25 GeV and 10 GeV for e events. Electrons in the pseudorapidity range j j < 2:5 and muons in the range j j < 2:4 are considered. Electrons, reconstructed by associating tracks with ECAL clusters, are identi ed by a sequential selection using information on the cluster shape in the ECAL, track quality, and the matching between the track and the ECAL cluster. Additionally, electrons from photon conversions are rejected [62]. Muons are reconstructed from tracks found in the muon system, associated with tracks in the silicon tracking detectors. They are identi ed based on the quality of the track t and the number of associated hits in the di erent tracking detectors [63]. The lepton isolation, de ned as the scalar pT sum of all particle candidates in a cone around the lepton, excluding the lepton itself, divided by the lepton pT, is required to be <0.04 for electrons (with a cone of radius R = p ( )2 + ( )2 = 0:3) and <0.15 for muons (with a cone of radius R = 0:4). Lepton identi cation and isolation e ciencies in the simulation are corrected for residual di erences with respect to data. These corrections are measured in a data sample, enriched in Z ! `` events, using a \tag-and-probe" method and are parameterised as a function of lepton pT and . Jets are reconstructed using a particle ow (PF) technique [64]. PF candidates are clustered to form jets using the anti-kT clustering algorithm [65] with a distance parameter of 0.4, implemented in the FastJet package [66]. Jet energies are corrected for residual nonuniformity and nonlinearity of the detector response [67]. Jets are required to have pT > 20 GeV, j j < 2:4, and be separated from identi ed leptons by a distance of R > 0:3. { 4 { to the jet energies are propagated to p~miss. candidates, is referred to as p~miss [68, 69]. Its magnitude is denoted by pmiss. Corrections The reconstructed vertex with the largest value of summed object p2T is taken to be the primary pp interaction vertex, considering the objects returned by a clustering algorithm applied to all charged tracks associated with the vertex, plus the corresponding associated p~miss. The combined multivariate algorithm [70, 71] is used to identify jets originating from b quarks. Jets are considered as b tagged if they pass the medium working point of HJEP01(28)54 the algorithm, which provides around 70% e ciency with a mistag rate less than 1%. Correction factors are applied in the simulation to the selected jets to account for the di erent response of the combined multivariate algorithm between data and simulation [71]. Among all possible dijet combinations ful lling the previous criteria, we select the two jets with the highest combined multivariate algorithm outputs. After the nal object selection consisting of two opposite sign leptons and two b-tagged jets, a requirement of 12 < m`` < mZ 15 GeV is applied to suppress quarkonia resonances and jets misidenti ed as leptons, and to remove the large background at the Z boson peak as well as the high-m`` tail of the DY and tt processes. This requirement has a negligible impact on signal events where one H decays as H ! W(` )W(` ), and removes only the portion of H ! Z(``)Z( ) decays with on-shell Z(``) legs. Figure 2 shows the dijet pT for data and simulated events after requiring the selection criteria described in this section. All the background processes are estimated from simulation, with the exception of DY production in the e+e and + almost negligible, and is taken from simulation. channels. The DY contribution in the e channels is The contribution of the DY process in the analysis selection is estimated from a data sample enriched in DY plus jets events. The estimate is performed by requiring all the selection criteria described above, except for the b tagging requirements. The resulting dataset is corrected with weights to represent the DY contribution in the full selection. The weights are a function of kinematic variables and are tuned to reproduce the e ect of applying the b tagging requirements on the DY process. They account for the following features: The b tagging e ciencies are not constant and depend on jet kinematics. Moreover, this dependency is di erent for b-, c- or light- avour jets. The relative contributions of DY plus two jets of avours k and l, where k; l = b; c; or light- avour, to the DY plus two jets process are not constant throughout the phase-space. Modelling the e ect of b tagging requires to parameterise the fractions Fkl of jets with avours k and l as a function of event kinematics. We compute the weights as: Wsim = X k;l=b;c;light- avour Fkl(BDT) k(pjT1 ; j1 ) l(pjT2 ; j2 ), (4.1) { 5 { V e9G 2500 e±μ ±channels / s t E tt VV ttV tt VV ttV 5 pb for display purposes. Error bars indicate statistical uncertainties, while shaded bands show post- t systematic uncertainties. where k and l are the b tagging e ciencies for k- and l- avour jets calculated from simulation as a function of pT and of the jets and corrected for di erences between data and simulation, and j1 and j2 denote the two pT-ordered jets selected according to the above requirements. The expected fractions of jets with avours k and l in the dataset are denoted by Fkl and are parameterised as a function of the output value of a Boosted Decision Tree (BDT) [72]. The indices k and l refer to the assumed avour of j1 and j2, respectively. The avour fractions Fkl are estimated from a simulated DY sample. Their dependency on the BDT output value accounts for the di erent kinematical behaviours of heavy- or light- avour associated DY processes, e ectively reducing the dimensionality of the phase-space to a single variable. The BDT is trained to discriminate DY+bb; cc from other DY associated production processes using the following input variables: pj1 , T { 6 { pj2 , j1 , j2 , pjTj , p``, ``, T T (``; p~Tmiss) (de ned as the p~miss), number of jets, and HT de ned as the scalar sum of the transverse momentum of T between the dilepton system and all selected leptons and jets. Beside DY, the data sample without b tagging requirements contains small contributions from other backgrounds such as tt, single top quark and diboson production. Hence, the same reweighting procedure is applied to simulated samples for these processes, and the result is subtracted from the weighted data to de ne the estimate of the DY background in the analysis region. The method is validated both in simulation and in two data control regions requiring either m`` > mZ 15 GeV or jm`` mZj < 15 GeV. The predicted DY distributions are in agreement with data and simulation within the uncertainties of the method, described in improve the signal-to-background separation. As the dominant background process (tt production) is irreducible, the DNNs rely on information related to event kinematics. The variables provided as input to the DNNs exploit the presence in the signal of two Higgs bosons decaying into two b jets on the one hand, and two leptons and two neutrinos on the other hand, which results in di erent kinematics for the dilepton and dijet systems between signal and background processes. The variables used as input are: m``, R``, Rjj , (``; jj) (de ned as the p min( Rj`), and mT = 2p`T`pmiss[1 T cos (``; p~Tmiss)]. between the dijet and the dilepton systems), p`T`, pjTj , The DNNs utilise a parameterised machine learning technique [74] in order to ensure optimal sensitivity on the full range of signal hypotheses considered in these searches. In this approach, one or more physics parameters describing the wider scope of the problem, as for example the mass of the resonance in the resonant search case, are provided as input to the DNNs, in addition to reconstructed quantities. The parameterised network is able to perform as well as individual networks trained on speci c hypotheses (parameter values) while requiring only a single training, and provides a smooth interpolation to cases not seen during the training phase, as shown by gure 3. Two parameterised DNNs are trained: one for the resonant and one for the nonresonant search. In the rst case, the set of parameters are the masses of the resonance, providing 13 values for the network training (mX = 260, 270, 300, 350, 400, 450, 500, 550, 600, 650, 750, 800, 900 GeV), and a discrete variable indicating the dilepton avour channel: same avour (e+e and + ) or di erent avour (e ). In the second case, the parameters are and t, providing 32 combinations of those for the network training ( = 20, -5, 0, 1, 2.4, 3.8, 5, 20 and t = 0:5, 1, 1.75, 2.5), and the dilepton avour channel variable as in the resonant case. The mjj distributions, and resonant and nonresonant DNN discriminators after selection requirements, are shown in gures 4 and 5, respectively. Given their discrimination power between signal and background, both variables are used to enhance the sensitivity of the analysis. We de ne three regions in mjj : two of them enriched in background, { 7 { feicny iSgnal .08 .09 .085 .10 .095 .075 .07 iSmulaton X nisp 0 H Vb lb l rTaing iwth tduleav ta rTaing iwth tduleav ta aBckground feicny la mase, la mase .04 xecpt 650 eGV, m X = 650 eGV m X = 650 eGV .06 .0 .02 .08 .10 e ciency for the mX = 650 GeV signal as a function of the selection e ciency for the background (ROC curve), for the combined e+e , + and e channels. The dashed line corresponds to the DNN used in the analysis, trained on all available signal samples, and evaluated at mX = 650 GeV. The dotted line shows an alternative DNN trained using all signal samples except for mX = 650 GeV, and evaluated at mX = 650 GeV. Both curves overlap, indicating that the parameterised DNN is able to generalise to cases not seen during the training phase by interpolating the signal behaviour from nearby mX points. mjj < 75 GeV and mjj 140 GeV, and the other enriched in signal, mjj 2 [ 75; 140 ) GeV. In each region, we use the DNN output as our nal discriminant, as shown in gure 6, where the three mjj regions are represented in a single distribution. 6 Systematic uncertainties We investigate sources of systematic uncertainties and their impact on the statistical interpretation of the results by considering both uncertainties in the normalisation of the various processes in the analysis, as well as those a ecting the shapes of the distributions. Theoretical uncertainties in the cross sections of backgrounds estimated using simulation are considered as systematic uncertainties in the yield predictions. The uncertainty in the total integrated luminosity is determined to be 2.5% [75]. The following sources of systematic uncertainties that a ect the normalisation and shape of the templates used in the statistical evaluation are considered: Trigger e ciency, lepton identi cation and isolation: uncertainties in the measurement, using a \tag-and-probe" technique, of trigger e ciencies as well as electron and muon isolation and identi cation e ciencies, are considered as sources of systematic uncertainties. These are evaluated as a function of lepton pT and , and { 8 { HJEP01(28)54 V e8G 500 e+e− channel s t tt VV ttV s t tt VV ttV E 1000 800 600 400 200 0 1.2 1 ttV SM Higgs 50 100 150 200 250 300 350 400 mjj (GeV) displayed have been scaled to a cross section of 5 pb for display purposes. Error bars indicate statistical uncertainties, while shaded bands show post- t systematic uncertainties. their e ect on the analysis is estimated by varying the corrections to the e ciencies by 1 standard deviation. Jet energy scale and resolution: uncertainties in the jet energy scale are of the order of a few percent and are computed as a function of jet pT and [67]. A di erence in the jet energy resolution of about 10% between data and simulation is accounted for by worsening the jet energy resolution in simulation by -dependent factors. The uncertainty due to these corrections is estimated by a variation of the factors applied by 1 standard deviation. Variations of jet energies are propagated to p~miss. T b tagging: b tagging e ciency and light- avour mistag rate corrections and associated uncertainties are determined as a function of the jet pT [71]. Their e ect on the analysis is estimated by varying these corrections by 1 standard deviation. { 9 { s t E tt VV ttV Data tt VV ttV e v m i a t D 0.6 s t ne 4500 v E 4000 3500 3000 2500 2000 1500 1000 500 m i a t ttV m i a t s t m i a t D 0.6 1.4 1.2 0.8 1 tsn 4000 e v E 3500 3000 2500 2000 1500 1000 500 m i a t D 0.6 1.4 1.2 0.8 1 CMS ttV ttV 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output (left) is evaluated at mX = 400 GeV and the parameterised nonresonant DNN output (right) is evaluated at = 1, t = 1. The two signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes. Error bars indicate statistical uncertainties, while shaded bands show post- t systematic uncertainties. DNN output at m = 400 GeV, mjj bins X CMS ttV ttV ttV ttV m i a t s t m i a t m i a t D 0.6 1.4 1.2 0.8 1 s t e v E 500 400 300 200 100 1.4 1.2 0.8 1 m i a t D 0.6 s tn 1600 e v E 1400 1200 1000 800 600 400 200 m i a t tt VV ttV s t Data tt VV ttV s / / a a 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1 0.5 1 DNN output at m = 400 GeV, mjj bins X DNN output at κλ = κt = 1 (SM), m bins jj (bottom) channels, in three di erent mjj regions: mjj < 75 GeV, mjj 2 140 GeV. The parameterised resonant DNN output (left) is evaluated at mX = 400 GeV and the parameterised nonresonant DNN output (right) is evaluated at = 1, t = 1. The two signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes. Error bars indicate statistical uncertainties, while shaded bands show post- t systematic uncertainties. Pileup: the measured total inelastic cross section is varied by 5% [76] to produce di erent expected pileup distributions. Renormalisation and factorisation scale uncertainty: this uncertainty is estimated by varying the renormalisation ( R) and the factorisation ( F) scales used during the generation of the simulated samples independently by factors of 0.5, 1, or 2. Unphysical cases, where the two scales are at opposite extremes, are not considered. An envelope is built from the 6 possible combinations by keeping maximum and minimum variations for each bin of the distributions, and is used as an estimate of the scale uncertainties for all the background and signal samples. PDF uncertainty: the magnitudes of the uncertainties related to the PDFs and the variation of the strong coupling constant for each simulated background and signal process are obtained using variations of the NNPDF 3.0 set [54], following the PDF4LHC prescriptions [77, 78]. Simulated sample size: the nite nature of simulated samples is considered as an additional source of systematic uncertainty. For each bin of the distributions, one additional uncertainty is added, where only the considered bin is altered by 1 standard deviation, keeping the others at their nominal value. DY background estimate from data: the systematic uncertainties listed above, which a ect the simulation samples, are propagated to k and Fkl, both computed from simulation. These uncertainties are then propagated to the weights Wsim and to the normalisation and shape of the estimated DY background contribution. The uncertainty due to the nite size of the simulation samples used for the determination of k and Fkl is also taken into account. Since previous measurements [79, 80] have shown that the avour composition of DY events with associated jets in data is compatible with the simulation within scale uncertainties, no extra source of theoretical uncertainty has been considered for Fkl. To account for residual di erences between the e+e and + channels not taken into account by Fkl, due to the di erent requirements on lepton pT, a 5% uncertainty in the normalisation of the DY background estimate is added in both channels. The e ects of these uncertainties on the total yields in the analysis selection are summarised in table 1. Results 7 e A binned maximum likelihood t is performed in order to extract best t signal cross sections. The t is performed using templates built from the DNN output distributions in the three mjj regions, as shown in gure 6, and in the three channels (e+e , + , and ). The likelihood function is the product of the Poisson likelihoods over all bins of Source Electron identi cation and isolation Jet b tagging (heavy- avour jets) Pileup PDFs Integrated luminosity Trigger e ciency Muon identi cation Muon isolation Jet energy scale Jet energy resolution Jet b tagging (light- avour jets) R and F scales tt cross section Simulated sample size R and F scales Simulated sample size DY cross section Simulated sample size Normalisation Single t cross section Simulated sample size R and F scales A ecting only signal R and F scales Simulated sample size and on the SM and mX = 400 GeV signal hypotheses in the signal region. A ecting only tt (85.1{95.7% of the total bkg.) A ecting only DY in e channel (0.9% of the total bkg.) A ecting only DY estimate from data in same- avour events (7.1{10.7% of the total bkg.) A ecting only single top quark (2.5{2.9% of the total bkg.) Background yield variation Signal yield variation 2.0{3.2% 2.5% 2.5% 0.5{1.4% 0.3{1.4% 0.4{0.8% 0.6{0.7% 0.3% 0.2{0.3% <0.1{0.3% 0.1% 1.9{2.9% 2.5{2.7% 2.5% 0.4{1.4% 0.3{1.5% 0.4{0.7% 1.0{1.4% 0.3{0.4% 0.1{0.2% 0.7{1.0% <0.1% HJEP01(28)54 12.8{12.9% 5.2% <0.1% 24.6{24.7% 7.7{11.6% 4.9% 18.8{19.0% 5.0% 7.0% <0.1{1.0% <0.1{0.2% SM signal 24.2% <0.1% the templates and is given by L( signal; kjdata) = Nbins ini e i Y ; ni! i=1 k where ni is the number of observed events in bin i and the Poisson mean for bin i is given by i = signal Si + X k Tk;i; where k denotes all of the considered background processes, Tk;i is the bin content of bin i of the template for process k, and Si is the bin content of bin i of the signal template. The parameter k is the nuisance parameter for the normalisation of the process k, constrained by theoretical uncertainties with a log-normal prior, and signal is the signal strength, unconstrained. For each systematic uncertainty a ecting the shape (normalisation) of the templates, a nuisance parameter is introduced with a Gaussian (log-normal) prior. The best- t values for all the nuisance parameters, as well as the corresponding postt uncertainties, are extracted by performing a binned maximum likelihood t, in the background-only hypothesis, of the mjj vs. DNN output distributions (such as gure 6 left) to the data. Only nuisance parameters a ecting the backgrounds are considered. 7.1 Resonant production The t results in signal cross sections compatible with zero; no signi cant excess above background predictions is observed for X particle mass hypotheses between 260 and 900 GeV. We set upper limits at 95% con dence level (CL) on the product of the production cross section for X and branching fraction for X ! HH ! bbVV ! bb` ` using the asymptotic modi ed frequentist method (asymptotic CLs) [81{83] as a function of the X mass hypothesis. The limits are shown in gure 7. The observed upper limits on the product of the production cross section and branching fraction for a narrow-width spin-0 resonance range from 430 to 17 fb, in agreement with expected upper limits of 340+114000 to 14+64 fb. For narrow-width spin-2 particles produced in gluon fusion with minimal gravity-like coupling, the observed upper limits range from 450 to 14 fb, in agreement with expected upper limits of 360+114000 to 13+64 fb. The left plot of gure 7 shows possible cross sections for the production of a radion, for the parameters R = 1 TeV (mass scale) and kL = 35 (size of the extra dimension). The right plot of gure 7 shows possible cross sections for the production of a Kaluza-Klein graviton, for the parameters k=MPl = 0:1 (curvature) and kL = 35. These cross sections are taken from [49], assuming absence of mixing with the Higgs boson. 7.2 Nonresonant production Likewise for the nonresonant case, the t results in signal cross sections compatible with zero; no signi cant excess above background predictions is seen. We set upper limits at 95% CL on the product of the Higgs boson pair production cross section and branching fraction for HH ! bbVV ! bb` ` using the asymptotic CLs, combining the e+e , + and H)×H( 01 2 86% expctd 59% expctd 86% expctd M lP =1.0 01 1 ×H) X )b( f l p( t9L%i noCm5l p2isn HJEP01(28)54 03 04 05 06 07 08 m ,Xnips 0 09 03 04 05 06 07 08 m ,Xnips 2 of the production cross section for X and branching fraction for X ! HH ! bbVV ! bb` ` , as a function of mX. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the backgroundonly hypothesis. These limits are computed using the asymptotic CLs method, combining the e+e , + and e channels, for spin-0 (left) and spin-2 (right) hypotheses. The solid circles represent fully-simulated mass points. The dashed red lines represent possible cross sections for the production of a radion (left) or a Kaluza-Klein graviton (right), assuming absence of mixing with the Higgs boson [49]. Parameters used to compute these cross sections can be found in the legend. e is found to be 72 fb, in agreement with an expected upper limit of 81+4225 fb. Including channels. The observed upper limit on the SM HH ! bbVV ! bb` ` cross section theoretical uncertainties in the SM signal cross section, this observed upper limit amounts to 79 times the SM prediction, in agreement with an expected upper limit of 89+4278 times the SM prediction. In the BSM hypothesis, upper limits are set as a function of = t, as shown in gure 8 (left panel), since the signal kinematics depend only on this ratio of couplings. Red lines show the theoretical cross sections, along with their uncertainties, for t = 1 (SM) and t = 2. The theoretical signal cross section is minimal for = t = 2:45 [84], corresponding to a maximal interference between the diagrams shown on gure 1. Excluded regions in the t vs. plane are shown in gure 8 (right panel). The signal cross sections and kinematics are invariant under a ( ; t) $ ( ; t) transformation, hence the expected and observed limits on the production cross section, as well as the constraints on the and t parameters respect the same symmetry. The red region in the panel corresponds to parameters excluded at 95% CL with the observed data, whereas the dashed black line and the blue areas correspond to the expected exclusions and the 68 and 95% bands. Isolines of the product of the theoretical cross section and branching fraction for HH ! bbVV ! bb` ` are shown as dashed-dotted lines. 01 4 01 3 01 2 lb H( t =2 t =1 / t 02 t .20 .15 .0 .10 .05 .25 CMS 02 51 530 fb 01 410 fb 01 fb 52 fb 57 fb 86% expctd 59% expctd 5 01 fb 25 fb 01 410 fb 51 MS hTeory 2 02 HJEP01(28)54 02 01 0 01 of the Higgs boson pair production cross section and branching fraction for HH ! bbVV ! bb` ` as a function of = t. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the backgroundonly hypothesis. Red lines show the theoretical cross sections, along with their uncertainties, for t = 1 (SM) and t = 2. Right: exclusions in the ( , t) plane. The red region corresponds to parameters excluded at 95% CL with the observed data, whereas the dashed black line and the blue areas correspond to the expected exclusions and the 68 and 95% bands (light and dark respectively). Isolines of the product of the theoretical cross section and branching fraction for HH ! bbVV ! bb` ` are shown as dashed-dotted lines. The diamond marker indicates the prediction of the SM. All theoretical predictions are extracted from refs. [12{17, 84]. 8 Summary A search for resonant and nonresonant Higgs boson pair production (HH) is presented, either a W or a Z boson. The LHC proton-proton collision data at p where one of the Higgs bosons decays to bb, and the other to VV ! ` ` , where V is s = 13 TeV collected by the CMS experiment corresponding to an integrated luminosity of 35.9 fb 1 are used. Masses are considered in the range between 260 and 900 GeV for the resonant search, while anomalous Higgs boson self-coupling and coupling to the top quark are considered in addition to the standard model case for the nonresonant search. The results obtained are in agreement, within uncertainties, with the predictions of the standard model. For the resonant search, the data exclude a product of the production cross section and branching fraction of narrow-width spin-0 particles from 430 to 17 fb, in agreement with the expectations of 340+114000 to 14+64 fb, and narrow-width spin-2 particles produced with minimal gravity-like coupling from 450 to 14 fb, in agreement with the expectations of 360+114000 to 13+64 fb. For the standard model HH hypothesis, the data exclude a product of the production cross section and branching fraction of 72 fb, corresponding to 79 times the SM cross section. The expected exclusion is 81+4225 fb, corresponding to 89+4278 times the SM cross section. Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative sta s at CERN and at other CMS institutes for their contributions to the success of the CMS e ort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so e ectively 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: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). 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 O ce; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, co nanced 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 Clar n-COFUND del Principado de Asturias; the Thalis and Aristeia programmes co nanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845. 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Hamel de Monchenault, P. Jarry, I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.O . Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Universite Paris-Saclay, Palaiseau, France A. Abdulsalam, I. Antropov, S. Ba oni, F. Beaudette, P. Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A. Zghiche Universite de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France S. Gadrat J.-L. Agram11, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N. Chanon, C. Collard, E. Conte11, X. Coubez, J.-C. Fontaine11, D. Gele, U. Goerlach, M. Jansova, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France Universite de Lyon, Universite Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucleaire de Lyon, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, 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, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, A. Popov12, V. Sordini, M. Vander Donckt, S. Viret T. Toriashvili13 Z. Tsamalaidze7 Georgian Technical University, Tbilisi, Georgia Tbilisi State University, Tbilisi, Georgia RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C. Schomakers, J. Schulz, T. Verlage RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Guth, M. Hamer, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thuer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany G. Flugge, B. Kargoll, T. Kress, A. Kunsken, J. Lingemann, T. Muller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl14 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U. Behrens, A. Bermudez Mart nez, A.A. Bin Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo16, J. Garay Garcia, A. Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Gutho , A. Harb, J. Hauk, M. Hempel17, H. Jung, A. Kalogeropoulos, M. Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krucker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann17, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Ho mann, A. Karavdina, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, F. Pantaleo14, T. Pei er, A. Perieanu, C. Scharf, P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbruck, F.M. Stober, M. Stover, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald Institut fur Experimentelle Kernphysik, Karlsruhe, Germany M. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, B. Freund, R. Friese, M. Gi els, A. Gilbert, D. Haitz, F. Hartmann14, Paraskevi, Greece I. Topsis-Giotis S.M. Heindl, U. Husemann, F. Kassel14, S. Kudella, H. Mildner, M.U. Mozer, Th. Muller, M. Plagge, G. Quast, K. Rabbertz, M. Schroder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wohrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D. Loukas, National and Kapodistrian University of Athens, Athens, Greece G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou University of Ioannina, Ioannina, Greece I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary M. Csanad, N. Filipovic, G. Pasztor, G.I. Veres18 Wigner Research Centre for Physics, Budapest, Hungary G. Bencze, C. Hajdu, D. Horvath19, A. Hunyadi, F. Sikler, V. Veszpremi, G. Vesztergombi18, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary M. Bartok18, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India S. Choudhury, J.R. Komaragiri National Institute of Science Education and Research, Bhubaneswar, India S. Bahinipati21, S. Bhowmik, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, N. Sahoo, S.K. Swain Panjab University, Chandigarh, India S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A. Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University of Delhi, Delhi, India Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma, V. Sharma Saha Institute of Nuclear Physics, HBNI, Kolkata, India R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur HJEP01(28)54 Indian Institute of Technology Madras, Madras, India P.K. Behera Bhabha Atomic Research Centre, Mumbai, India R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty14, P.K. Netrakanti, L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata Institute of Fundamental Research-B, Mumbai, India S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Kumar, M. Maity23, G. Majumder, K. Mazumdar, T. Sarkar23, N. Wickramage24 Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei Hosseinabadi, B. Safarzadeh27, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Bari a, Universita di Bari b, Politecnico di Bari c, Bari, Italy M. Abbresciaa;b, C. Calabriaa;b, C. Caputoa;b, A. Colaleoa, D. Creanzaa;c, L. Cristellaa;b, N. De Filippisa;c, M. De Palmaa;b, F. Erricoa;b, L. Fiorea, G. Iasellia;c, S. Lezkia;b, G. Maggia;c, M. Maggia, G. Minielloa;b, S. Mya;b, S. Nuzzoa;b, A. Pompilia;b, G. Pugliesea;c, R. Radognaa;b, A. Ranieria, G. Selvaggia;b, A. Sharmaa, L. Silvestrisa;14, R. Vendittia, P. Verwilligena INFN Sezione di Bologna a, Universita di Bologna b, Bologna, Italy G. Abbiendia, C. Battilanaa;b, D. Bonacorsia;b, S. Braibant-Giacomellia;b, R. Campaninia;b, P. Capiluppia;b, A. Castroa;b, F.R. Cavalloa, S.S. Chhibraa, G. Codispotia;b, M. Cu ania;b, G.M. Dallavallea, F. Fabbria, A. Fanfania;b, D. Fasanellaa;b, P. Giacomellia, C. Grandia, L. Guiduccia;b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa;b, A. Perrottaa, A.M. Rossia;b, T. Rovellia;b, G.P. Sirolia;b, N. Tosia INFN Sezione di Catania a, Universita di Catania b, Catania, Italy S. Albergoa;b, S. Costaa;b, A. Di Mattiaa, F. Giordanoa;b, R. Potenzaa;b, A. Tricomia;b, C. Tuvea;b L. Viliania;b;14 INFN Sezione di Firenze a, Universita di Firenze b, Firenze, Italy G. Barbaglia, K. Chatterjeea;b, V. Ciullia;b, C. Civininia, R. D'Alessandroa;b, E. Focardia;b, P. Lenzia;b, M. Meschinia, S. Paolettia, L. Russoa;28, G. Sguazzonia, D. Stroma, INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 INFN Sezione di Genova a, Universita di Genova b, Genova, Italy V. Calvellia;b, F. Ferroa, E. Robuttia, S. Tosia;b INFN Sezione di Milano-Bicocca a, Universita di Milano-Bicocca b, Milano, Italy L. Brianzaa;b, F. Brivioa;b, V. Cirioloa;b, M.E. Dinardoa;b, S. Fiorendia;b, S. Gennaia, A. Ghezzia;b, P. Govonia;b, S. Gundacker, M. Malbertia;b, S. Malvezzia, R.A. Manzonia;b, D. Menascea, L. Moronia, M. Paganonia;b, K. Pauwelsa;b, D. Pedrinia, S. Pigazzinia;b;29, S. Ragazzia;b, T. Tabarelli de Fatisa;b INFN Sezione di Napoli a, Universita di Napoli 'Federico II' b, Napoli, Italy, Universita della Basilicata c, Potenza, Italy, Universita G. Marconi d, Roma, Italy F. Thyssena S. Buontempoa, N. Cavalloa;c, S. Di Guidaa;d;14, F. Fabozzia;c, F. Fiengaa;b, A.O.M. Iorioa;b, W.A. Khana, L. Listaa, S. Meolaa;d;14, P. Paoluccia;14, C. Sciaccaa;b, INFN Sezione di Padova a, Universita di Padova b, Padova, Italy, Universita di Trento c, Trento, Italy P. Azzia;14, N. Bacchettaa, L. Benatoa;b, D. Biselloa;b, A. Bolettia;b, R. Carlina;b, A. Carvalho Antunes De Oliveiraa;b, P. Checchiaa, M. Dall'Ossoa;b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia;b, U. Gasparinia;b, A. Gozzelinoa, S. Lacapraraa, P. Lujan, M. Margonia;b, A.T. Meneguzzoa;b, N. Pozzobona;b, P. Ronchesea;b, R. Rossina;b, F. Simonettoa;b, E. Torassaa, P. Zottoa;b, G. Zumerlea;b INFN Sezione di Pavia a, Universita di Pavia b, Pavia, Italy A. Braghieria, A. Magnania;b, P. Montagnaa;b, S.P. Rattia;b, V. Rea, M. Ressegotti, C. Riccardia;b, P. Salvinia, I. Vaia;b, P. Vituloa;b INFN Sezione di Perugia a, Universita di Perugia b, Perugia, Italy L. Alunni Solestizia;b, M. Biasinia;b, G.M. Bileia, C. Cecchia;b, D. Ciangottinia;b, L. Fanoa;b, P. Laricciaa;b, R. Leonardia;b, E. Manonia, G. Mantovania;b, V. Mariania;b, M. Menichellia, A. Rossia;b, A. Santocchiaa;b, D. Spigaa INFN Sezione di Pisa a, Universita di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy K. Androsova, P. Azzurria;14, G. Bagliesia, J. Bernardinia, T. Boccalia, L. Borrello, R. Castaldia, M.A. Cioccia;b, R. Dell'Orsoa, G. Fedia, L. Gianninia;c, A. Giassia, M.T. Grippoa;28, F. Ligabuea;c, T. Lomtadzea, E. Mancaa;c, G. Mandorlia;c, L. Martinia;b, A. Messineoa;b, F. Pallaa, A. Rizzia;b, A. Savoy-Navarroa;30, P. Spagnoloa, R. Tenchinia, G. Tonellia;b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Universita di Roma b, Rome, Italy L. Baronea;b, F. Cavallaria, M. Cipriania;b, D. Del Rea;b;14, E. Di Marcoa;b;31, M. Diemoza, S. Gellia;b, E. Longoa;b, F. Margarolia;b, B. Marzocchia;b, P. Meridiania, G. Organtinia;b, R. Paramattia;b, F. Preiatoa;b, S. Rahatloua;b, C. Rovellia, F. Santanastasioa;b INFN Sezione di Torino a, Universita di Torino b, Torino, Italy, Universita del Piemonte Orientale c, Novara, Italy N. Amapanea;b, R. Arcidiaconoa;c, S. Argiroa;b, M. Arneodoa;c, N. Bartosika, R. Bellana;b, C. Biinoa, N. Cartigliaa, F. Cennaa;b, M. Costaa;b, R. Covarellia;b, A. Deganoa;b, N. Demariaa, B. Kiania;b, C. Mariottia, S. Masellia, E. Migliorea;b, V. Monacoa;b, E. Monteila;b, M. Montenoa, M.M. Obertinoa;b, L. Pachera;b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia;b, F. Raveraa;b, A. Romeroa;b, M. Ruspaa;c, R. Sacchia;b, K. Shchelinaa;b, V. Solaa, A. Solanoa;b, A. Staianoa, P. Traczyka;b INFN Sezione di Trieste a, Universita di Trieste b, Trieste, Italy S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa;b, A. Zanettia Kyungpook National University, Daegu, Korea 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 A. Lee Chonbuk National University, Jeonju, Korea Chonnam National University, Institute for Universe and Elementary Particles, H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul, Korea M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S. Lee, S. Lee, J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, National Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia M.N. Yusli, Z. Zolkapli I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz34, Rabadan-Trejo, R. I., R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autonoma de San Luis Potos , San Luis Potos , Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand HJEP01(28)54 D. Krofcheck P.H. Butler M. Waqas University of Canterbury, Christchurch, New Zealand National Centre for Physics, Quaid-I-Azam University, Islamabad, Pakistan A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M. Shoaib, National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Gorski, M. Kazana, K. Nawrocki, M. Szleper, P. Zalewski Warsaw, Poland Institute of Experimental Physics, Faculty of Physics, University of Warsaw, K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratorio de Instrumentac~ao e F sica Experimental de Part culas, Lisboa, Portugal D. Vadruccio, J. Varela P. Bargassa, C. Beir~ao Da Cruz E Silva, A. Di Francesco, P. Faccioli, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J. Seixas, O. Toldaiev, Joint Institute for Nuclear Research, Dubna, Russia S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev36;37, V. Palichik, V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia Y. Ivanov, V. Kim38, E. Kuznetsova39, P. Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical and Experimental Physics, Moscow, Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin HJEP01(28)54 Moscow Institute of Physics and Technology, Moscow, Russia T. Aushev, A. Bylinkin37 National Research Nuclear University 'Moscow Engineering Physics Institute' (MEPhI), Moscow, Russia R. Chistov40, M. Danilov40, P. Parygin, D. Philippov, S. Polikarpov, E. Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan37, A. Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia A. Snigirev A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S. Petrushanko, V. Savrin, Novosibirsk State University (NSU), Novosibirsk, Russia V. Blinov42, Y.Skovpen42, D. Shtol42 State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernandez Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, A. Perez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Alvarez Fernandez Universidad Autonoma de Madrid, Madrid, Spain J.F. de Troconiz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R. Gonzalez Fernandez, E. Palencia Cortezon, S. Sanchez Cruz, I. Suarez Andres, P. Vischia, J.M. Vizan Garcia Santander, Spain Instituto de F sica de Cantabria (IFCA), CSIC-Universidad de Cantabria, I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Au ray, P. Baillon, A.H. Ball, D. Barney, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, A. De Roeck, M. Dobson, B. Dorney, T. du Pree, M. Dunser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, F. Glege, D. Gulhan, P. Harris, J. Hegeman, V. Innocente, P. Janot, O. Karacheban17, J. Kieseler, H. Kirschenmann, V. Knunz, A. Kornmayer14, M.J. Kortelainen, M. Krammer1, C. Lange, P. Lecoq, C. Lourenco, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic44, F. Moortgat, M. Mulders, H. Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfei er, M. Pierini, A. Racz, T. Reis, G. Rolandi45, M. Rovere, H. Sakulin, C. Schafer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas46, A. Stakia, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns47, M. Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertly, L. Caminada48, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bani, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donega, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandol , J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, M. Schonenberger, L. Shchutska, V.R. Tavolaro, K. Theo latos, M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universitat Zurich, Zurich, Switzerland T.K. Aarrestad, C. Amsler49, M.F. Canelli, A. De Cosa, R. Del Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, C. Seitz, Y. Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok, Thailand Turkey B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Cukurova University, Physics Department, Science and Art Faculty, Adana, A. Adiguzel50, F. Boran, S. Cerci51, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, D. Sunar Cerci51, B. Tali51, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey B. Bilin, G. Karapinar56, K. Ocalan57, M. Yalvac, M. Zeyrek Bogazici University, Istanbul, Turkey E. Gulmez, M. Kaya58, O. Kaya59, S. Tekten, E.A. Yetkin60 Istanbul Technical University, Istanbul, Turkey M.N. Agaras, S. Atay, A. Cakir, K. Cankocak Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, Ukraine B. Grynyov Kharkov, Ukraine L. Levchuk, P. Sorokin National Scienti c Center, Kharkov Institute of Physics and Technology, University of Bristol, Bristol, United Kingdom R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, C. Lucas, D.M. Newbold61, S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton Laboratory, Didcot, United Kingdom K.W. Bell, A. Belyaev62, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A. Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College, London, United Kingdom G. Auzinger, R. Bainbridge, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, R. Di Maria, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko6, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta63, T. Virdee14, N. Wardle, D. Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L. Teodorescu, M. Turner Baylor University, Waco, U.S.A. A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith Catholic University of America, Washington DC, U.S.A. R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, U.S.A. A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University, Boston, U.S.A. D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak, D. Zou D. Yu Brown University, Providence, U.S.A. G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S. Sagir, R. Syarif, University of California, Davis, Davis, U.S.A. R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout, M. Shi, J. Smith, M. Squires, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of California, Los Angeles, U.S.A. M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M. Ignatenko, N. Mccoll, D. Saltzberg, C. Schnaible, V. Valuev University of California, Riverside, Riverside, U.S.A. E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I. Paneva, A. Shrinivas, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates University of California, San Diego, La Jolla, U.S.A. J.G. Branson, S. Cittolin, M. Derdzinski, B. Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M. Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech64, J. Wood, F. Wurthwein, A. Yagil, G. Zevi Della Porta bara, U.S.A. N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, S.D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of Technology, Pasadena, U.S.A. D. Anderson, J. Bendavid, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, U.S.A. M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, U.S.A. J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T. Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, U.S.A. J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. So , S.M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator Laboratory, Batavia, U.S.A. S. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G. Bolla, K. Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grunendahl, O. Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, R. Lopes De Sa, J. Lykken, K. Maeshima, N. Magini, J.M. Marra no, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O'Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida, Gainesville, U.S.A. D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerho , A. Carnes, M. Carver, D. Curry, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University, Miami, U.S.A. Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University, Tallahassee, U.S.A. A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T. Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, R. Yohay Florida Institute of Technology, Melbourne, U.S.A. M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, U.S.A. M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D. Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, U.S.A. B. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya67, A. Mestvirishvili, A. Moeller, J. Nachtman, H. Ogul68, Y. Onel, F. Ozok69, A. Penzo, C. Snyder, E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, U.S.A. B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of Kansas, Lawrence, U.S.A. A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S. Sanders, E. Schmitz, R. Stringer, J.D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, U.S.A. A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, U.S.A. F. Rebassoo, D. Wright University of Maryland, College Park, U.S.A. C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli, N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar Massachusetts Institute of Technology, Cambridge, U.S.A. D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, M. D'Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of Minnesota, Minneapolis, U.S.A. A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz University of Mississippi, Oxford, U.S.A. J.G. Acosta, S. Oliveros E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State University of New York at Bu alo, Bu alo, U.S.A. M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, U.S.A. moto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University, Evanston, U.S.A. G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash, T. OriS. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, B. Pollack, M.H. Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, U.S.A. N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams, K. Lannon, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko36, M. Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A. Woodard The Ohio State University, Columbus, U.S.A. J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin Princeton University, Princeton, U.S.A. A. Benaglia, S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroue, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, U.S.A. S. Malik, S. Norberg Purdue University, West Lafayette, U.S.A. A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones, A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, J.F. Schulte, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, U.S.A. T. Cheng, N. Parashar, J. Stupak Rice University, Houston, U.S.A. A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel University of Rochester, Rochester, U.S.A. A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M. Verzetti The Rockefeller University, New York, U.S.A. R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New Jersey, Piscataway, U.S.A. A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gomez Espinosa, E. Halkiadakis, M. Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. She eld, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, U.S.A. A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M University, College Station, U.S.A. O. Bouhali70, A. Castaneda Hernandez70, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon71, R. Mueller, Y. Pakhotin, R. Patel, A. Perlo , L. Pernie, D. Rathjens, A. Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, U.S.A. N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S. Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville, U.S.A. S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville, U.S.A. M.W. Arenton, P. Barria, B. Cox, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia Wayne State University, Detroit, U.S.A. R. Harr, P.E. Karchin, J. Sturdy, S. Zaleski University of Wisconsin - Madison, Madison, WI, U.S.A. M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Herve, U. Hussain, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor, N. Woods y: Deceased China 1: Also at Vienna University of Technology, Vienna, Austria 2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, 3: Also at Universidade Estadual de Campinas, Campinas, Brazil 4: Also at Universidade Federal de Pelotas, Pelotas, Brazil 5: Also at Universite Libre de Bruxelles, Bruxelles, Belgium 6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 7: Also at Joint Institute for Nuclear Research, Dubna, Russia 8: Also at Suez University, Suez, Egypt Moscow, Russia 10: Now at Helwan University, Cairo, Egypt 11: Also at Universite de Haute Alsace, Mulhouse, France 12: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, 13: Also at Tbilisi State University, Tbilisi, Georgia 14: Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland 15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany 16: Also at University of Hamburg, Hamburg, Germany 17: Also at Brandenburg University of Technology, Cottbus, Germany 18: Also at MTA-ELTE Lendulet CMS Particle and Nuclear Physics Group, Eotvos Lorand University, Budapest, Hungary 19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary 20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary 21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India 22: Also at Institute of Physics, Bhubaneswar, India 23: Also at University of Visva-Bharati, Santiniketan, India 24: Also at University of Ruhuna, Matara, Sri Lanka 25: Also at Isfahan University of Technology, Isfahan, Iran 26: Also at Yazd University, Yazd, Iran 27: Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran 28: Also at Universita degli Studi di Siena, Siena, Italy 29: Also at INFN Sezione di Milano-Bicocca; Universita di Milano-Bicocca, Milano, Italy 30: Also at Purdue University, West Lafayette, U.S.A. 31: Also at INFN Sezione di Roma; Sapienza Universita di Roma, Rome, Italy 32: Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia 33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia 34: Also at Consejo Nacional de Ciencia y Tecnolog a, Mexico city, Mexico 35: Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland 36: Also at Institute for Nuclear Research, Moscow, Russia 37: Now at National Research Nuclear University 'Moscow 38: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 39: Also at University of Florida, Gainesville, U.S.A. 40: Also at P.N. Lebedev Physical Institute, Moscow, Russia 41: Also at California Institute of Technology, Pasadena, U.S.A. 42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia 43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia Belgrade, Serbia 45: Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy 46: Also at National and Kapodistrian University of Athens, Athens, Greece 47: Also at Riga Technical University, Riga, Latvia 48: Also at Universitat Zurich, Zurich, Switzerland 49: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria 50: Also at Istanbul University, Faculty of Science, Istanbul, Turkey 51: Also at Adiyaman University, Adiyaman, Turkey 44: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, 53: Also at Mersin University, Mersin, Turkey 54: Also at Cag University, Mersin, Turkey 55: Also at Piri Reis University, Istanbul, Turkey 56: Also at Izmir Institute of Technology, Izmir, Turkey 57: Also at Necmettin Erbakan University, Konya, Turkey 58: Also at Marmara University, Istanbul, Turkey 59: Also at Kafkas University, Kars, Turkey 60: Also at Istanbul Bilgi University, Istanbul, Turkey 61: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom 62: Also at School of Physics and Astronomy, University of Southampton, Southampton, United 63: Also at Instituto de Astrof sica de Canarias, La Laguna, Spain 64: Also at Utah Valley University, Orem, U.S.A. 65: Also at Beykent University, Istanbul, Turkey 66: Also at Bingol University, Bingol, Turkey 67: Also at Erzincan University, Erzincan, Turkey 68: Also at Sinop University, Sinop, Turkey 69: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 70: Also at Texas A&M University at Qatar, Doha, Qatar 71: Also at Kyungpook National University, Daegu, Korea [1] F. 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Kargoll, T. Kress, A. Künsken, J. Lingemann, T. Müller. Search for resonant and nonresonant Higgs boson pair production in the \( \mathrm{b}\overline{\mathrm{b}}\mathit{\ell \nu \ell \nu } \) final state in proton-proton collisions at \( \sqrt{s}=13 \) TeV, Journal of High Energy Physics, 2018, 54, DOI: 10.1007/JHEP01(2018)054