Search for New Particles Decaying to a Jet and an Emerging Jet

Search for new particles decaying to a jet and an emerging jet

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Citation CMS Collaboration (Sirunyan, A.M., et al.), "Search for new particles decaying to a jet and an emerging jet." Journal of high energy physics 2019 (Feb. 2019): no. 179 doi 10.1007/JHEP02(2019)179 ©2019 Author(s)

As Published 10.1007/JHEP02(2019)179

Version Final published version

Citable link https://hdl.handle.net/1721.1/124860

Detailed Terms https://creativecommons.org/licenses/by/4.0/ JHEP02(2019)179 Springer October 23, 2018 January 18, 2019 January 29, 2019 February 26, 2019 : : : : from proton-proton 1 − Revised Received Accepted Published Published for SISSA by https://doi.org/10.1007/JHEP02(2019)179 . 3 1810.10069 = 13 TeV collected by the CMS experiment at the LHC in 2016. The s Beyond Standard Model, Hadron-Hadron scattering (experiments) √ A search is performed for events consistent with the pair production of a , Copyright CERN, [email protected] E-mail: Article funded by SCOAP Open Access for the benefit of the CMS Collaboration. Keywords: ArXiv ePrint: between 400 and 1250 GeV. Decayexcluded lengths smaller in than the 5 lower andpion greater part than mass of 225 is mm this are weak masssearch also for for range. masses the between pair The production 1 dependence of and of a 10 the GeV. new limit This particle on that analysis decays the is to dark the a first jet dedicated and an emerging jet. dark quark is chargedan only “emerging under jet” a viato new a displaced quantum-chromodynamics-like parton vertices force, shower, when and containingwith decaying forms long-lived the to expectation dark standard from hadrons standard model modelexcluding that hadrons. processes. dark give pion Limits rise The are decay data set lengths are at between 95% consistent 5 confidence and level 225 mm for dark mediators with masses Abstract: new heavy particle thatand that acts decays as tobased a a on mediator light data between quark corresponding acollisions and to at dark a an integrated new sector luminosity fermion and of called normal 16.1 fb a matter, dark quark. The search is The CMS collaboration Search for new particles decayingemerging to jet a jet and an JHEP02(2019)179 16 ], it 1 ]. 5 ]. Unlike 3 , 2 is the number ], such models 4 DK C N 2 ]. Emerging jets contain electrically 7 ) symmetry, where , 6 DK C N – 1 – , which are not charged under the forces of the standard DK 14 10 23 4 5 1 18 We consider, in particular, the dark QCD model of Bai, Schwaller, Stolarski, and Weiler of dark colors. Thegluons particle associated content with of thenew the force, model dark and consists force a of and mediatorfermions the particle under are dark that SM bound fermions, is QCD, themediator by charged dark to thus the under SM allowing both new hadrons. interactions the force with into quarks. dark hadrons. The dark These hadrons decay via the naturally explain the observed mass densities of baryonic matter(BSSW) and that dark matter predicts [ “emergingcharged SM jets” particles (EMJ) that [ long-lived are neutral consistent particles with (darkQCD. having hadrons), In been produced this in created model, a in dark parton-shower the QCD process decays has by of an dark new SU( candidate that interacts with quarks.fermions One called class “dark of quarks”, models Q includesmodel new, electrically-neutral (SM) buthas are confining charged properties under similar amodels based to new on quantum force the popular chromodynamics in weakly (SM the interacting neutral QCD) dark particle [ paradigm sector [ (“dark QCD”) that 1 Introduction Although many astrophysicalhas observations yet indicate to the begravitational existence observed interactions, of in many the dark compelling laboratory. models matter of While [ new it physics is contain possible a that dark dark matter matter has only The CMS collaboration 6 Systematic uncertainties 7 Results 8 Summary 3 Simulated samples 4 Event selection 5 Background estimation Contents 1 Introduction 2 The CMS detector and event reconstruction JHEP02(2019)179 ) 3 ). T / p (1.1) miss T ): p 0 DK DK 1.1 0 ¯q q Q Q , 4 ]. DK 11 X – 1 TeV m 8 DK † DK X X ], is given by eq. ( 7 DK g π , via gluon-gluon fusion (left) and m 2 GeV is the dark pion decay constant; DK 2 DK π f , left) or quark-antiquark annihilation 1 3 matrix of Yukawa couplings between the down q q × m 100 MeV DK C – 2 – 2 N DK 0 DK 0 ¯q q Q Q DK is created because of jet energy mismeasurement. We π f 2 GeV T miss are the masses of the down quark, the dark pion, and the p 4 DK 1 κ X DK † DK . X X m is a complex scalar. Under SM QCD, it is an SU(3) color triplet, and 5 ]. We abide by these restrictions by assuming that all the Yukawa via Yukawa couplings. There are restrictions on the values of the DK 11 g – , and 80 mm 8 DK ≈ DK π cτ m , . Feynman diagrams in the BSSW model for the pair production of mediator particles, , right) at the CERN LHC. The mediator has an electric charge of either 1 is the appropriate element of the g g down 1 κ 3 of the electron charge, and it can decay to a right-handed quark with the same m The signature for this search thus consists of four high transverse momentum ( The decay length of the lightest dark meson (dark pion) [ The mediator X / as described in section 2 The CMS detectorThe and CMS event detector reconstruction proton-proton is (pp) a and multipurpose heavy ion apparatus collisions. designed A to superconducting solenoid study occupies physics its processes cen- in The main background for thisas signature emerging is either SM because four-jet theystruction, production, contain where and long-lived jet(s) B large are mesons artificial tagged oruse because a of photon+jets track data misrecon- criteria sample designed to for measure emerging the jets, probability and for use an this SM probability jet in to estimating pass the selection background, jets, two from down quarksdisplaced and vertices two arising from from darkshower quarks. the and decays The fragmentation. of dark For quark the modelssize jets dark with of contain dark pions many the hadron produced decay detector, in lengths there the comparable dark to can the parton also be significant missing transverse momentum ( where mediator particle, the quarks, andand the dark quarks; mediator particle, respectively. Yukawa couplings from searches for flavor-changing neutraland currents, neutral rare meson mixing, decays [ couplings are negligible except for the coupling to the down quark [ thus can be pair produced(figure via gluon fusion (figure or 2 charge and a Q Figure 1 with each mediator decayingquark-antiquark to annihilation a (right). quark and a dark quark Q JHEP02(2019)179 ] 13 5. The is taken < 2 T ]. | p 4, the track η . 14 | 1 3. A steel and < < | | η 5 are reconstructed | η . of those jets. Other | 2 T < p | η | ]. The position of each vertex m in the transverse (longitudi- 15 10 GeV and µ < T < p ]. 12 ]. The resolution in the position is around 10– s, using information from the calorimeters and – 3 – µ 16 ] is used to reconstruct and identify each individ- 4. The first level of the CMS trigger system [ . ] with the tracks assigned to the vertex as inputs, 2 19 and 25–90 (45–150) < 18 , | T η p | 17 ]. 12 ]. The reconstruction efficiency is low for tracks with an impact , taken as the negative vector sum of the 12 miss T p ]. The tracking efficiency for prompt hadrons is typically over 98% for tracks with 12 The analysis involves two types of jets: SM QCD jets and emerging jets. For each The particle-flow (PF) algorithm [ The reconstructed vertex with the largest value of summed physics-object A more detailed description of the CMSThe pp detector, interaction together vertices are with reconstructed a by definition clustering tracks of on the the basis of their A lead tungstate crystal electromagnetic calorimeter (ECAL) and a brass/scintillator m in each of the three spatial directions [ above 1 GeV. For nonisolated particles with 1 µ coordinates along the beamline at their points of closest approach to the center of the T corresponding ECAL and HCAL energies,response corrected for functions zero-suppression of effects the andhadrons for calorimeters the is to obtained hadronic from showers. the Finally, corresponding the corrected energy ECAL of andevent, neutral HCAL the energies. reconstruction of both types of jets starts with the clustering of reconstructed the CMS detector. Thesurement, corrected energy for of zero-suppression each effects.from photon The a is energy combination directly of of each obtainedenergy, electron the from is and track the determined momentum the ECAL at energy mea- energy the of sum PV, each of the muon is all correspondingeach obtained charged ECAL bremsstrahlung from hadron cluster photons the is corresponding attached determined track to from momentum. the a The track. combination energy of of The the track momentum and the and the associated vertices in the samereferred event to due as to pileup. additional pp collisions inual the particle, same with beam an crossing optimized are combination of information from the various elements of is estimated with an12 adaptive vertex fit [ to be the primaryusing pp the interaction jet vertex (PV). finding The algorithm physics [ objects are the jets, clustered coordinate system and the relevant kinematic variables, can bez found in ref. [ luminous region using a deterministic annealing algorithm [ muon system consists ofoutside gas-ionization the detectors solenoid, embedded andis in covers designed the to steel select fluxmuon events detectors. in return less yoke The than high-levelto 4 trigger around (HLT) 1 processor kHz farm before then data reduces storage. the event rate resolutions are typically 1.5%nal) in impact parameter [ parameter larger than 25 cm [ hadron calorimeter (HCAL) surroundquartz-fiber the tracking Cherenkov volume hadron and forward cover calorimeter extends the coverage to tracker system consists of 1 440trajectories silicon of pixel charged particles and within 15 148 thefrom pseudorapidity silicon the range strip detector hits modules. infilter The the [ silicon trackingp system using an iterative procedure with a Kalman tral region, providing a magnetic field of 3.8 T parallel to the beam direction. The silicon JHEP02(2019)179 , ] 25 8.212 2.2.2 [ pythia and the quarks mass equals the ], with a distance DK mc@nlo DK a 18 , ]. We assume that all 5 ], we assume that there 6 17 7 ], while an offset correction is using the underlying-event tune 19 ]. ]. The loose working point corre- 23 MadGraph algorithm [ ]. Jet energy corrections are derived 24 of all PF candidates in an event. Its T 22 k pythia T – ~p 20 ] parton distribution functions (PDFs). The 27 – 4 – [ ]. The model has several parameters: the mass of 7 . NNPDF3.0 miss T p spectrum and detector acceptance. Additional proton-proton T p ] with the . The mass of the dark rho meson is taken to be four times larger than ]. 26 is the negative vector sum of the DK 28 of 0.4. The jet momentum is determined as the vectorial sum of the momenta (one for each dark flavor), the mass of the dark pion, the dark pion proper . For the SM jets, the momentum is found in the simulation to be within 5 8.2 [ R miss T 4 ~p DK (and therefore dark pions) are mass degenerate and that the Q Signal samples are generated with the “hidden valley” model framework in The Jets consistent with the fragmentation of b quarks are identified using the Combined pythia DK decay length, and the massare of the three dark dark rho colors meson.Q and Following ref. seven [ dark flavorsdark as force suggested confinement in scale.mass ref. of [ The the mass Q of the dark pion is assumed to be one half the using modifications discussed inthe ref. mediator [ particle, thenumber width of of dark the flavors, mediator thewith matrix particle, the same of the electric Yukawa number couplings chargeof of as between the the dark the mediator, Q colors, Q the the dark force confinement scale, the masses leading order inor the strong couplingstrong constant coupling constant using at the Zdevelopment and mass hadronization scale are is simulated set with toCUETP8M1 0.130 [ in the generator. Parton shower Simulated Monte Carlo (MC) samplesA, are defined used as for the thee.g., fraction estimation of of tracking the MC signal and events acceptance of passing other the the efficiencies. selection templates criteria, fortechniques. and These background thus estimation samples including, The and are the simulation also validation of of used SM background for estimation processes, the unless construction otherwise stated, is performed at magnitude is referred to as 3 Simulated samples Drell-Yan+jet, dijet, multijet, and photon+jet events [ Secondary Vertex version 2sponds (CSVv2) to discriminator correctly [ identifying aa b light-flavor jet quark as jet a with b a quark probability jet of with 81% a and probability misidentifying of 8.9%. interactions within the sameand or calorimetric energy nearby depositions bunch tohadrons crossings the not can jet associated momentum. contribute with To additionalusing mitigate the tracks this the PV effect, pileup are charged charged-hadronapplied removed subtraction to from algorithm correct the [ for listfrom remaining of simulation contributions reconstructed and [ particles are confirmed with in situ measurements with the energy balance of parameter of associated particles.in Additional section identification criteriato for 10% the of emerging thegluons, true jets momentum over are for the given jets, entire created from the fragmentation of SM quarks and particles with the infrared and collinear safe anti- JHEP02(2019)179 as free 0, corre- . 2 DK ]. Because π 7 < cτ | , with the mul- η | ]. 36 , pythia sum of all hadronic jets. 35 T p = 13 TeV, corresponding to an s √ of the jets in an event. At the HLT, events – 5 – T p collected by the CMS detector in 2016. The data were , and the dark pion proper decay length 1 [mm] 1, 2, 5, 25, 45, 60, 100, 150, 225, 300, 500, 1000 [GeV] 1, 2, 5, 10 [GeV] 400, 600, 800, 1000, 1250, 1500, 2000 DK − π DK DK DK m π π X ], with other squarks and gluinos decoupled. The cross section cτ m m -based simulation of the CMS detector [ 33 – 29 ]. Geant4 . Each set of values defines a single model. 34 1 Signal model parameters List of values Dark pion mass . Parameters used in generating the 336 simulated signal event samples. A sample corre- , the dark pion mass Dark mediator mass An emerging jet contains multiple displaced vertices and thus multiple tracks with For all samples, multiple minimum-bias events simulated with The range in the mediator particle mass over which the search is sensitive depends on DK Dark pion decay length X signature. large impact parameters. Since impactbetween parameter-based SM variables give and good discrimination emergingvertices of jets, the we dark do pions. not Emerging attempt jet to candidates reconstruct are required the to individual have decay were selected if they passedThis a analysis 900 used GeV only threshold a on portionrunning the period, of scalar the saturation-induced data dead collected time duringtracker. was present 2016 Such in because, data the for readout were part of notdependent of the that analyzed silicon inefficiencies because strip for of the hard-to-modelimpact instantaneous reconstruction parameters luminosity- of larger tracks, than in 10 mm particular that those are tracks key with to the selection of the emerging jet 4 Event selection The analysis is basedintegrated luminosity on of data 16.1 fb fromobtained pp using collisions a at trigger based on the tiplicity distribution matching thatinteraction observed in event data, to arethrough model superimposed the with the full the pileup primary contribution. Generated particles are processed times larger thanmass. that for We the use asimplified pair topologies calculation production [ of of theis a squark calculated single at pair next-to-leading flavor production order in ofresummation cross SM [ section QCD squark with that of next-to-leading logarithm is the soft-gluon based same on listed in table the mediator particle pairSM production quantum numbers cross as the section. supersymmetricwe partner The assume of an mediator three SM particle quark dark (squark) has colors, [ the the same signal production cross section is assumed to be three the mass of thecompared dark with pion. the The detectorm width mass of resolution. the These mediator assumptionsparameters. particle leave is Samples the are assumed mediator generated to mass for be all small permutations as of the values of these parameters Table 1 sponding to a single model was created for each possible set of parameter values. JHEP02(2019)179 , 2 ) sum B (4.1) 1 . T , a set sum of p 3 4 (where T . p + (0 = 0 B and 2 2 + ) 0 and to pass a . φ S 2 p is smaller for tracks < sum of the associated | + (∆ S/ N η ) is correlated with the 2 | T i ) D p η of the track at its closest 2D of the jet that is associated z (∆ IP , T h . The selection requirements 2 √ p ] = sig miss T is the p R IP trk 1 GeV, pass the “high-purity” quality z + [ > 2 ). They must have either two jets tagged T T p trk H z , which is the scalar from the PV, at the point of closest approach, ) is used to reject tracks from pileup vertices. for background and for signals with a mediator − z – 6 – 3D dz 01 cm for background and for signals with a mediator i . α 0 PV 2D PU z 3D α IP h s position of the track at its distance of closest approach to = z is the transverse impact parameter significance of the track N ], are used to select the emerging jets. The median of the as follows. For each variable listed in tables ], and are within a cone of D sig 37 are smaller than a threshold, divided by the scalar 1 sum of these jets ( 12 IP N T p D sum of its associated tracks. We also require that the scalar , defined as position of the primary vertex, N T position of the PV ( p z D z thresholds and the emerging jet selection criteria were optimized for each T is the p shows the distributions of shows the distributions of PV z 2 3 Selected candidate events are required to have four jets with Since the efficacy of the variables used to select emerging jets depends on the correct is azimuthal angle in radians) around the direction of the jet momentum. Emerging jet on the jet- signal model listed inof table potential selection thresholdssignal were and chosen background. based For on eachthe the permutation predicted of distribution pseudo-significance all of the for the selection each variable thresholds, signal for we model, calculated defined as the largest scalar of tracks whose extrapolated separationis in less than 0.01 cm, be larger than 10%threshold of on the the sum scalar overas all tracks. emerging, or one jet tagged as emerging and large mass of 1 TeV and a dark pion mass ofidentification 5 and GeV. reconstruction ofcases the observed PV, in additional simulated selections backgroundor events are a where used pileup the vertex to PV was remove was chosen rare either as not the PV. reconstructed We require that the chosen PV be the vertex with all associated tracks, is usedwith to prompt quantify tracks. the This fraction variableFigure of should the be large formass SM of jets 1 TeV and and small aFigure for dark emerging pion jets. of various masses and with a proper decay length of 25 mm. approach to the PV, and at its closest approach tothat the is PV, is inconsistent used with tofrom zero identify prompt within tracks particles. that uncertainties. A have antracks variable The impact called whose variable parameter values of A variable called where from electrons and photons, toto reduce the backgrounds ones from electrons. definedunsigned in Four transverse variables, impact ref. similar parameters [ ofdark associated meson tracks ( proper decayjets. length, The and distance should between be the the small PV for and SM the jets and large for emerging are associated with theselection candidate described if in they ref. have [ φ candidates are required to havecan at be least estimated. one The associated jet track candidates so are that also required the to impact have parameter less than 90% of their energy sponding to the region of the tracker where the impact parameter resolution is best. Tracks JHEP02(2019)179 1 . 3D α / 1cm) 〉 (13 TeV) (13 TeV) 2D IP 〈 0 1 log( . There are six groups of criteria . Two basic categories of selections = 1 mm = 5 mm = 25 mm = 60 mm = 100 mm = 300 mm 3 DK DK DK DK DK DK 2 π π π π π π τ τ τ τ τ τ 1 QCD light jets 1 GeV Dark pion mass Dark pion mass 2 GeV Dark pion mass 5 GeV Dark pion mass 10 GeV c c c c c c QCD light jets − – 7 – 2 − 3 − , the selection criteria used to select emerging jets are for background (black) and for signals with a mediator mass of i for background (black) and for signals with a mediator mass of 2 2D CMS CMS Simulation Simulation Simulation 3D 4 α IP 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 − 1 h 0 2 3 1 − − − 10

0.1 0.5 0.4 0.3 0.2

10 0.45 0.35 0.25 0.15 0.05 10 10

Fraction of Jets / 0.2 / Jets of Fraction Fraction of Jets / 0.05 / Jets of Fraction correspond to the number of signal and background events and the 0 (sets 1 to 7), which gives the selections on kinematic variables, along with B 3 and . Distributions of . Distributions of S the corresponding emerging jet criteria from table seven selection sets.listed. These In jet-level table selectioncomprise criteria, along the with final event-level kinematicused selection selection to criteria, criteria, select given emerginggiven in in jets. table table The seven selection sets used to define signal regions are where corresponds to an estimate of theof systematic background calculations, uncertainty. the In pseudo-significances order were toof used limit to selection the find final criteria the minimum number where number thresholds the and difference in a pseudo-significance chosen between selection the threshold best is selection no more than 10%, resulting in a total of Figure 3 1 TeV and a dark pion mass of 5 GeV for dark pion proper decay lengths ranging from 1 to 300 mm. Figure 2 1 TeV and a dark pion proper decay length of 25 mm, for various dark pion masses. JHEP02(2019)179 i for 2D IP h miss T p , and the N ) D < . The EMJ- ( 5 3D and α dz PU criteria as EMJ-3 set, but ) [cm] > N ( . Note that in addition to the D i 2D miss T p and IP h dz ) PU criteria as EMJ-1 set, but loosens only < ( i N . Selection set 3 requires that one jet satisfies 2D D – 8 – IP miss T h p 5. These two groups of jet-level criteria are more . shows an example of the signal acceptance of models 0 4 ) [cm] , and < < N ( D , favoring more displaced tracks. Selection set 3 is used for i 3D dz , α 2D dz PU IP h PU 10 and . 0 > i 2D EMJ-1 2.5 4 0.05 0.25 Criteria group EMJ-2 4.0 4 0.10 0.25 EMJ-3 4.0 20 0.25 0.25 EMJ-4 2.5 4 0.10 0.25 EMJ-5 2.5 20 0.05 0.25 EMJ-6 2.5 10 0.05 0.25 EMJ-7 2.5 4 0.05 0.40 EMJ-8 4.0 20 0.10 0.50 IP 4, while the EMJ-8 group has the same . h . Groups of requirements (associated operator indicated in parentheses) on the variables 0 requirement, the EMJ-3 group imposes the loosest criteria on < The acceptance of the selection criteria for signal events ranges from a few percent for We also define two additional groups of jet-level criteria that are used to test the Since the initial optimization only used a rough estimate of the systematic uncer- 3D miss T models with a mediatorpion mass decay of length 400 of GeV 25 to mm.with 48% dark Figure for pion mass more of massivedecay 5 mediators GeV length, as with with a a text function dark indicating of the the corresponding mediator mass selection and set the number. dark pion proper α loosens efficient for quark orimproving the gluon statistical jets power than of the those tests. used for the final selections in the analysis, tainty, the final selectionthat set gives for the most each stringent modeluncertainties. expected is limit, chosen taking into from account among more the realistic systematic seveneffectiveness as of the the one background7 estimation group methods, has described the in same section impact parameters due to theimpact b parameters lifetime; due most to SM misreconstruction. jetsthis thus The selection selected substantive requirement have set tracks on is withwhen the large requiring essential two to emerging attain jet candidates. background rejection equivalent to that obtained the emerging jet criteria, andp includes a requirement on tightest requirement on signal models with darkis pions large with enough that large it proper removes decay most lengths. events containing b The quark selection jets on with tracks with large that define the signal regions,samples while for the the groups EMJ-7 tests and of -8 the are background used estimation to methods. defineemerge. SM QCD-enhanced Other than setjet criteria, 3, and the have signal no requirement region on selection sets require two jets pass emerging Table 2 used in the identification of emerging jets. The groups EMJ-1 to -6 are used for the selection sets JHEP02(2019)179 of T p . The 2 SM QCD-enhanced ) EMJ group no. models for which the associated selection set ) [GeV], the requirements on the ≥ of 5 GeV as a function of the mediator ( 1 T . The corresponding selection set number H DK EMJ π DK n π m cτ miss T p – 9 – [GeV], the minimum number of the four leading jets 4 , ), and the EMJ criteria group described in table miss T T p p EMJ 3 n , T p 2 , T p sum of the four leading jets ( T 1 , p T p T H ) [GeV], the requirement on and the dark pion proper decay length i , T . The signal acceptance A, defined as the fraction of simulated signal events passing the p DK . The seven optimized selection sets used for this search, and the two SM QCD-enhanced X 9 900 225 100 100 100 200 1 8 8 900 225 100 100 100 0 2 7 7 1200 300 250 200 150 0 2 6 103 6 1000 250 150 100 100 0 2 5 33 5 1000 250 150 100 100 0 2 4 41 4 1100 275 250 150 150 0 2 1 49 3 900 225 100 100 100 200 1 3 96 2 900 225 100 100 100 0 2 2 2 1 900 225 100 100 100 0 2 1 12 m Set number Figure 4 selection criteria, for modelsmass with a darkfor pion each mass model is indicated as text on the plot. selections (sets 8 andcolumns 9) are: used the in scalar teststhe jets of ( the backgroundthat estimation pass methods. the emerging Thelast jet headers selection column of ( is the thegives total the number best of expected models sensitivity. defined in table Table 3 JHEP02(2019)179 (5.3) (5.4) (5.1) (5.2) lead- T p ) f . − f (1 f i f 6= Y k f f is calculated as shown f ) f jets ∈ ), EMJ − P X 5.1 (1 i,j,k,m i,j 1 4 is the probability for at least one . 6= , is the misidentification probability Y X k ) fl b f ) + f f EMJ f jets not candidate EMJ ∈ P − P i,j − jets (1 1 3 ∈ fl X X (1 events ). i,j 1 2 + = ) + i,j,k 5.4 f – 10 – b . Y 6= f f m ) + − fb f f f f f (1 = i − bkg,EMJ ). f f 6= N j Y (1 5.2 f i jets 6= ∈ j Y X f is the probability that the jet is a b jet. The methodology used i,j,k is described below. The probability b X 1 3 b is the probability for one additional jet to pass the emerging jet f jets f ∈ X jets to pass the emerging jet criteria. The sum is over all events in i + jets not candidate X ∈ T = EMJ , the background is calculated using eq. ( p P , and i,j,k jets not candidate fl is the predicted background and ∈ miss T jets passes the emerging jet selection. The misidentification probability of 1 4 EMJ i p , P T . The background contributions for each of the selection sets are calculated 1 2 + fb p = ) the sum is over jets that do not pass the emerging jet selection criteria. miss T ). p bkg,EMJ is the misidentification probability for b jets, ) as well, except that the control sample requires exactly one jet to pass the corre- 5.4 5.3 N EMJ fb P 5.1 In the first method, for selection sets 3 and 9 that require at least one emerging jet In eq. ( eq. ( sponding emerging jet criteriaset. as well In as this allrequirements, case, other and selection is requirements calculated for using the eq. selection ( The other selection setsing (1 jets to 8, to excluding pass set emerging 3) jet require selection at requirements. least two The of background the is four estimated using to estimate in eq. ( each jet is calculated using eq. ( Here for light-flavor jets, and where of the four leading a “control sample” definedrequirement using of all at the least one selectionfour emerging requirements leading jet for candidate. this Instead, set events except are for vetoed if the one of the candidate and The production of eventsjets containing pass four the SM emerging jetsartificial jet can criteria, mimic or when thein one signal two passes when different and two ways, jet ofrequirements. using mismeasurement the the results probability in for an SM QCD jet to pass the emerging jet 5 Background estimation JHEP02(2019)179 (5.5) 2) for . 6 1 . ), the parton , is determined 5.4 b f 2 (52 . shows the resulting 9 6 ) and ( 8 . 5.3 , ! f1 f2

18) and 52   ) b2 b2 b1 f f f b1 − − − f be large, the misidentification probability b1 b1 (1 i f f − 2D 30 (231 b2 b2 b2 f f – 11 – b2 IP f f h − − − − b1 b1 1 f f is determined by fitting the observed distribution of 50 GeV, beyond the one used in the misidentification shows the measured misidentification probability for   b 5 > f = T p ! fl fb 50 GeV with a CSVv2 discriminator value below 0.2. The b represent the respective misidentification probability and b jet

> b2 T f p , and f2 , 165 GeV. We do not expect any signal contamination in this sample. Two b1 f , > f1 T p The method for estimating the background was tested by using the same procedure When convolving the misidentification probabilities with the kinematic characteristics The misidentification probability is measured as a function of track multiplicity using The probability for an SM jet to pass the emerging jet selection criteria (misidentifica- agreement with the resultsFor obtained example, the when average applying expected theestimation number of selection method events criteria to obtained to simulated byselection applying samples the the in (average samples. background expected simulated number samples)selection of sets are events 8 207 passing and the 9, respectively. The background estimation method was also verified fit for the kinematicseparately for sample all events of and for selectionThe events with first set at is least 1. used one for jetselection predicting passing The the the set emerging b background to jet fraction quark require criteria. for only selection content, set one 3, emerging which jet, is the theon second only simulated for samples, the verifying other that selection the sets. predicted number of selected events was in good EMJ-1 set. and parton composition ofcomposition the of the kinematic kinematic samples samplejet and using is light-flavor jet determined eqs. templates by obtained ( fitting from MC the simulation. CSVv2 Figure distribution to b where fraction in the two samples. Figure quark fraction of eachthe subsample CSVv2 discriminator toand the the sum other of simulated two light-flavorthe templates, jets. initiating one The parton created misidentification type using probability can as simulated a then b function be jets of calculated as follows: The sample with an enhancedat fraction of least b one jets additional is jetprobability selected with by calculation, requiring the that event togreater has contain than a 0.8. valuean for The additional the sample jet with discriminator with suppressed of probability the of CSVv2 containing algorithm a b jet requires dependence on track multiplicity, ranging fromvalues a several few orders percent of at magnitude low smaller track at multiplicities, the to highesta multiplicities. sample of events collectedwith with a trigger that requiressubsamples the are created: presence of one an with isolated an photon enhanced and one with a suppressed b quark fraction. tion) depends on the flavorThe of probability the for jet a and jetof initiated on ten by the larger a number than b of that quarkEMJ-3, tracks for (b associated because a jet) with of jet to the the initiated pass jet. for requirement by the that any selection b other can jets type be of and a parton factor light-flavor (light-flavor jets jet). is For similar. The misidentification probability has a strong JHEP02(2019)179 , f1 divided by the 2 χ correspond to Clopper-Pearson f2 (13 TeV) (13 TeV) -1 -1 and b jet Light-flavor jet 16.1 fb 16.1 fb Track multiplicity f1 CSVv2 discriminator Data Light-flavor jet b jet Uncertainty /ndof = 37/20 2 χ b jet fraction: 0.080 +/- 0.003 . The red up-pointing triangles are for b jets while – 12 – 2 Selection set 1 EMJ-1 CMS CMS

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40

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10 10 10 10 0.05 / jets of Fraction 10 10 10 Fit) - (Data 10 Misidentification probability Misidentification ), where the uncertainties in 5.5 in eq. ( b2 f ]. . 38 . Measured misidentification probability distribution as a function of track multiplicity 3 . Determination of the b jet fraction by fitting the CSVv2 discriminator distribution. The , and b1 f , f2 in the upper panelthe include fit statistical uncertainties, uncertainties summed of innumber of the quadrature. degrees b The of jet goodness freedomfit and (ndof). of result, light-flavor fit divided The jet by is bottom the templates, given panelthe combination and by shows of upper the the the panel. difference statistical The between uncertainty1 of data distributions data in and are and table the derived the from uncertainty kinematic from samples resulting from selection set Figure 6 red and blue distributionsrespectively. are The black the points CSVv2 with discriminator uncertainty bars templates show of the data b distribution. jets The and uncertainties light-flavor jets, Figure 5 for the EMJ-1 criteriathe group blue defined down-pointing in triangles table indicate are the for variable light-flavor bin jets. width. The The uncertainty horizontal bars linesintervals represent [ on the the statistical data uncertainties of points JHEP02(2019)179 (5.6) i failing − (13 TeV) -1 is the number i Data Predicted Predicted unc. , 16.1 fb Track multiplicity for selection sets m 8 N ,        and 0 1 2 3 4 , , , , , t t t t t 7 N N N N N               i non-b jets, 4 4 4 4 4 , , , , , 0 1 2 3 4 − 5 10 15 20 25 30 35 40 A A A A A CMS 3 3 3 3 3 , , , , ,

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A A A A A 300 200 100 Jets (Data - Pred.) - (Data 2 2 2 2 2 , , , , , 0 1 2 3 4 A A A A A 1 1 1 1 1 , , , , , – 13 – 0 1 2 3 4 A A A A A [GeV] 0 0 0 0 0 T , , , , , 28 (98), as shown in ﬁgures H 1 2 3 4 0 (13 TeV) -1 A A A A A        Data Predicted Predicted unc. 16.1 fb =        1 2 3 4 0 , , , , , m m m m m N N N N N        (left) and number of associated tracks (right) distributions for the observed data 35 (279) and 115 T is the appropriate combination of the CSVv2 eﬃciencies for a b jet to pass H j , i is the number of events with i b jets and 4 A CMS 1000 1200 1400 1600 1800 2000 2200 2400 i ,

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N 100 150 Events (Data - Pred.) - (Data ) per event in a sample is related to the distribution of the true number of b jets per The background estimation was also tested using a second method for estimating the btag n where of events with ithem, jets and passing the CSVv2the loose identification identification requirement requirements and and 4 for a non-b jet to pass the identification requirement, in the form of a matrix: fraction of b jets in( the control samples. The distributionevent, the of the distribution measured of number thejets, of true b and number jets of the non-b misidentification jets, probability the for identification non-b probability jets. for b This relationship can be written using data in theevents are SM 317 QCD-enhanced regions,8 and and 9, the respectively. predicted Thenumber of (observed) uncertainty events in numbers in the the of predicted controlprobabilities. number sample and combines statistical those uncertainties due in to the the misidentification events (black points) and theenhanced), predicted requiring background at estimation least (blue) two jets forthe tagged difference selection by between set loose observed 8 data emerging and (SM jetthe predicted QCD- criteria. statistical background, divided uncertainty The in by bottom the data panel sum andestimation. shows in the quadrature predicted of uncertainties from misidentification probability Figure 7 JHEP02(2019)179 (5.8) (5.7) 6 for . 1 ) is the 0 ) . ) represents j comb } . p jets pass the n } ν { ν − ). ( { ϕ (1 EMJ i 5.8 n 6= . j Y ) 0 and 112 i . } p , and 2 } k ), where each probability btag 2 n EMJ . 5.7 | n Y ν ∈{ |{ i ) possibilities for the true number of ) EMJ ν btag } n . ( ( ν fb fl , n { )! } ν ( EMJ ν comb { − ) is constructed. The array is inverted to P n 4! ( w 4 =0 5.6 !(4 )) = ν X ν } }} – 14 – ν ν { = |{ ( X events ϕ X ( EMJ 4 ν k n p { ) for each of the ) = = true b jets, and is calculated using eq. ( ) = ) = btag k EMJ } ν p ν n ( , n ( } btag ν 2 in simulated samples, and are 312 { n comb . | ( 1 represents the probability of having at least n ν w |{ bkg,EMJ 1 N . EMJ EMJ P n ( EMJ 3 and 53 P . 1 is the flavor-dependent misidentification probability of jet k p The respective numbers of predicted background events for selection sets 8 and 9 are To build the matrix, first a sample of events passing all the selection requirements of a 2 . 6 Systematic uncertainties The main sources oflimited number systematic of uncertainty events inthe in the misidentification the background photon+jets probability estimate data estimation. and are in Two due the other to simulated sources the samples are used the for uncertainties in 209 data in SM QCD-enhanceddue regions. to the The control predicted sampleprimary numbers event background include statistics. estimation only The method. the predictions are uncertainty in good agreement with the Here all possible flavor assignmentsbinomial coefficient, of to the account four for combinatorics jets. in each The permutation in combinatoric factor ( The probability emerging jet selections given b quarks (0–4). Theis background weighted is with then the calculated appropriate combination usingand of eq. their misidentification ( combinatorics. probabilities, efficiencies, selection set, except the requirementThis on the sample number is of emerging dominatedone, jet by candidates, two, is SM three, selected. four-jet oris production. all counted, of and The the the numberobtain four array the of leading described probability events jets in with satisfying eq. zero, the ( CSVv2 loose working point used is a weighted sumnumber over of the events jets as infunction a the of events. function the This of number matrix of trueare identified can b known, b be the jet jets. inverted misidentification multiplicity to Once probabilitiesapplied. from get the measured the true the from b number the jet photon+jets of and data events non-b can as jet be multiplicities a including combinatorics. As these probabilities depend on the jet kinematics, the value JHEP02(2019)179 . miss T p (13 TeV) -1 predicted by b f Data Predicted Predicted unc. 16.1 fb Track multiplicity 5 10 15 20 25 30 35 40 CMS .

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100 Jets (Data - Pred.) - (Data – 15 – [GeV] T and 2D impact parameter in photon+jet MC samples H (13 TeV) -1 trk z Data Predicted Predicted unc. photon and when using a misidentiﬁcation probability de- 16.1 fb − T p PV z for each of the samples used in the misidentiﬁcation probability b f (left) and number of associated tracks (right) distributions of the observed T H CMS 1000 1200 1400 1600 1800 2000 2200 2400 . The

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Events (Data - Pred.) - (Data The uncertainty due to the track modeling in simulation is evaluated by smearing The main source of uncertainty in the estimation of the signal acceptance is the mod- the tracks in signalsimulated events distributions using of the resolutionso functions that that they respectively agreetransformation transform with is the those taken as in the data. uncertainty. The change in signal acceptance when using this eling of displaced tracksMC in modeling the simulation. ofscale Other the (JES), sources trigger pileup include reweighting, efficiency, uncertainties andMC in integrated statistical samples. PDFs, uncertainties luminosity Systematic due determination, to uncertaintieslengths. the are jet limited largest energy size for of the the models with the shortest decay by using the method onthe prediction MC when simulation. using The aof uncertainty misidentification events is probability containing estimated determined a as usingtermined high- the an difference using MC in an sample MCuncertainty sample for of each SM selection QCD set is multijet given production. in The table estimated resulting the determination of determination and the uncertainties duein to the differences sample in used the in composition determiningkinematic the of samples. misidentification the We probability non-b estimate compared jets the tosimulation that first instead in of uncertainty that the by obtained using by the the value template of fit. We estimate the second uncertainty data events (black points) andQCD-enhanced), the requiring predicted at background leastThe estimation bottom (blue) one for panel jet selection shows taggedby set the the by 9 difference sum loose (SM between in quadrature observed emergingmisidentification of data jet probability the and estimation. statistical criteria predicted uncertainty and in background, data large divided and the predicted uncertainties from Figure 8 JHEP02(2019)179 . 5 ]. The uncer- 39 for which a 95% CL 1 4 4 3 4 0 1 3 ...... 1–4 1–9 1–5 1–3 < < < < . 3 – 16 – Source of uncertainty (%) b quark fraction non-b quark composition of jets by the JES uncertainty, and measuring its effect on sig- shows a graphical representation of one of the events passing T 9 p Source Uncertainty (%) PDF JES Trigger 6–12 Pileup Integrated luminosity 2.5 MC event count 2–17 Track modeling ]. The shift in signal acceptance is taken as the uncertainty. We account . Figure view. The filled circles represent reconstructed secondary vertices, while 1 2.8 1 2 0.6 4 3 2.9 28 4 5.0 4 5 0.9 4 6 1.6 2 7 1.0 6 6 23 φ ]. The resulting ranges of the systematic uncertainties are given in table – ρ 41 Set number ] and reweighting the simulation accordingly. The effect of the JES uncertainty is . Ranges of systematic uncertainties over all models given in table . Systematic uncertainties affecting the background estimate from control samples in data. 40 The uncertainty in the integrated luminosity determination is 2.5% [ The acceptance is evaluated using both the MC trigger selection and using a trig- Table 4 For the definition of the selection sets, see table is given in table the selection requirements. Thisdisplay event passes on both the selection left settracks shows 1 in the and the four selection jets. setthe 5. grey The The lines display represent on the the innermost right layer shows of the the reconstructed silicon pixel tracker. prescription [ 7 Results The number of events passing each selection set, along with the background expectation, tainty due to pileup4.6% modeling [ is measured byevaluated by varying shifting the the total inelasticnal acceptance cross [ section by for variations of the acceptance due to the PDF uncertainties following the PDF4LHC exclusion is expected, for the uncertainties from different sources. ger efficiency determined usinguncertainty in SM the QCD acceptance. multijet events. The difference is taken as an Table 5 JHEP02(2019)179 s φ – ρ [mm] DK π cτ [GeV] DK π m ” combines the systematic Model parameters 2 [GeV] 400 1 60 ] for the profile likelihood ratio DK X 45 m = 5 GeV. The dependence of the 2 DK ”, while “syst 10 π 1 × m 2.5 1000 10 300 4.0 1000 2 150 2.0 1000 1 2 1.6 1250 1 150 4.0 600 5 1 2.6) 0.64 1250 5 225 for – 17 – 10 ) and observed event yields for each selection set. Uncer- 2 . The “Signal” column shows the expected event yield for 4 syst between 1 and 10 GeV. Dark pion decay lengths between 5 summed in quadrature. The associated model parameters are 1 5 DK π 5 131 36.7 syst m 0.3 11 20.7 0.6 14 35.3 1.5 16 15.1 5.5 20 15.6 1.4 47 (14.6 0.28 2 5.61 15 2.0 1.9 2.5 7.0 5.0 ], using an asymptotic approximation [ 0.84 44 – is weak for 42 DK π . Event display of an event passing both selection set 1 and selection set 5. The event m . Expected (mean 7 4.40 6 9.4 5 13.9 4 22.5 3 19.4 2 31.8 1 168 No significant excess with respect to the SM prediction is observed. A 95% confidence Set number Expected Observed Signal prescription [ based test statistic, whereThe the 95% systematic CL uncertainties limits are onon taken the signal as signal nuisance parameters cross parameters. are section,limit shown on expected, in and observed figure exclusion contours view. The filled bluethe circles PV. represent The reconstructed secondary solid vertices, grey while lines the represent filled the red innermost circle layer is of the silicon pixel detector. level (CL) cross section upper bound is calculated following the modified frequentist CL contains four jets (jetsmassive 1 mediator and particles, 4scenario, each pass the decaying the dark to emerging mesonsSM an jet produced particles SM criteria), via in the quark consistent the mediator,(Left) with fragmentation resulting and 3D in of the display: a displaced the decay the vertices dark dark green with ofrepresent QCD lines decay energy quark two distances represent in quark. would reconstructed on the tracks, decay the ECAL the mm (HCAL) back In red scale. detectors, to (blue) respectively. such truncated (Right) a pyramids Reconstructed tracks in Figure 9 uncertainty sources discussed inthe table heaviest mediator massfrom that sources can discussed be inspecified excluded in table for the last each three set, columns. with the systematic uncertainties Table 6 tainties due to thethe limited misidentification number probabilities of are events in denoted the by control “syst sample and statistical uncertainties in JHEP02(2019)179 DK π cτ − DK X m of 5 GeV in the DK π m – 18 – = 13 TeV corresponding to an integrated luminos- s √ . The dark quark is assumed to be charged only under a new quantum- 1 − . Upper limits at 95% CL on the signal cross section and signal exclusion contours derived model hadrons. Themodel data processes. are Limits consistent arebetween with set 5 at the and 95% expected 225 confidence mm contributionslengths level for from excluding smaller dark than dark standard mediators 5 pion with and decay massesmass greater lengths range. between than 400 The 225 and dependence mm 1250 of are GeV. the also Decay limit excluded on in the the dark lower pion part mass of is this weak for masses between A search is presentedparticle for that events consistent decays with tofrom the a proton-proton pair light production collisions quark of andity at a a of heavy new 16.1 fb mediator fermionchromodynamics-like called dark force, a and dark toing quark, form an long-lived using emerging dark data jet hadrons via that a give parton rise shower, contain- to displaced vertices when decaying to standard Decay lengths smaller than 5of and this greater mass than range. 225 mm are also excluded in the8 lower part Summary plane. The solidenclosed red in contour red is dashed thethe lines. left expected of upper The the limit, solid observed black with contour is contour its excluded. is one the standard-deviation observedand region upper 225 mm limit. are excluded The at region 95% to CL for dark mediator masses between 400 and 1250 GeV. Figure 10 from theoretical cross sections for models with dark pion mass JHEP02(2019)179 – 19 – ´ UNKP, the NKFIA research grants 123842, 123959, Individuals have received support from the Marie-Curie program and the European European Union, Regionalistry Development of Fund, Science the andHarmonia Mobility Higher 2014/14/M/ST2/00428, Plus Education, Opus program the 2014/13/B/ST2/02543,and of 2015/19/B/ST2/02861, National 2014/15/B/ST2/03998, the Sonata-bis Science 2012/07/E/ST2/01406; Min- the Centersearch National (Poland), Program Priorities by Re- contracts Qatar National Research Fund; the Programa Estatal de Fomento de la the “Excellence of Science — EOS”Youth — and be.h Sports project (MEYS) n. 30820817; ofand the the the Ministry Czech of JánosBolyai Republic; Education, Research theNew Lendület(“Momentum”) Scholarship Program National of Excellence the124845, Program Hungarian 124850 Academy and of 125105India; Sciences, the (Hungary); HOMING the the PLUS program Council of of the Foundation Science for and Polish Science, Industrial cofinanced Research, from Research Council and HorizonLeventis 2020 Foundation; the Grant, A.P. contracttion; Sloan No. the Foundation; Belgian 675440 Federal the Science (European Alexander Policydans Union); Office; l’Industrie von the et the Humboldt Fonds dans pour l’Agriculture Founda- la (FRIA-Belgium);Wetenschap Formation en the àla Recherche Agentschap Technologie voor (IWT-Belgium); Innovatie the door F.R.S.-FNRS and FWO (Belgium) under SEIDI, CPAN, PCTI, andcies FEDER (Switzerland); (Spain); MST MOSTR (Taipei);TUBITAK (Sri and ThEPCenter, Lanka); TAEK IPST, Swiss (Turkey); NASU STAR,DOE Funding and and and Agen- SFFR NSF NSTDA (U.S.A.). (Ukraine); (Thailand); STFC (United Kingdom); NKFIA (Hungary); DAE and DST (India);and IPM NRF (Iran); (Republic SFI of (Ireland); Korea);BUAP, INFN MES CINVESTAV, CONACYT, (Italy); (Latvia); LNS, MSIP LAS SEP, (Lithuania); and MOE UASLP-FAIgro); (Mexico); and MBIE MOS UM (New (Montene- (Malaysia); Zealand); PAEC (Pakistan);JINR MSHE (Dubna); and NSC MON, (Poland); RosAtom, FCT (Portugal); RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); and FWF (Austria); FNRSand and FAPESP FWO (Brazil); (Belgium); MES CNPq,CIENCIAS (Bulgaria); (Colombia); CAPES, MSES CERN; FAPERJ, and CAS, CSF FAPERGS, (Croatia); MoST,MoER, RPF (Cyprus); and ERC SENESCYT IUT, NSFC (Ecuador); and (China);CEA ERDF COL- (Estonia); and Academy CNRS/IN2P3 of (France); Finland, BMBF, MEC, DFG, and and HIP HGF (Finland); (Germany); GSRT (Greece); formance of the LHCother and CMS thank institutes the for technical theirwe and contributions gratefully to administrative acknowledge the staffs success the atComputing of computing CERN Grid the and for centers CMS delivering at effort. and soanalyses. In personnel effectively Finally, addition, the we of acknowledge computing the the infrastructureof enduring Worldwide essential support the LHC to for LHC the our and construction and the operation CMS detector provided by the following funding agencies: BMBWF particle that decays to a jet and an emerging jet. Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent per- 1 and 10 GeV. This analysis is the first dedicated search for the pair production of a new JHEP02(2019)179 ] ] 12 A 28 D 92 Phys. Rept. S08004 , 3 Astron. ]. , arXiv:1609.02366 Front. Phys. Phys. Rev. [ , , JINST SPIRE arXiv:1407.8188 ]. (2015) 059 [ IN Int. J. Mod. Phys. ][ 05 (2018) 052 , (2014) 063522 P01020 2008 , SPIRE ]. Stealth QCD-like strong 08 IN 12 ]. ][ ]. JHEP D 89 , SPIRE (2015) 095009 JHEP IN JINST , SPIRE ][ SPIRE IN IN ][ D 91 arXiv:1405.6569 2017 Phys. Rev. [ , ]. ]. , ]. 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Rept. 594 , JHEP collaboration, , ]. ]. ]. collaboration, collaboration, collaboration, (2014) 91 SPIRE SPIRE SPIRE IN IN arXiv:1803.08080 IN arXiv:1306.4676 arXiv:1502.05409 (2015) 016004 [ interactions and the [ Violation Astrophys. [ [ constraints Planck (2013) 1330028 with the CMS tracker CMS [ CMS [ CMS 537 (2017) 121201 J. Brod, J. Drobnak, A.L. Kagan, E. Stamou and J. Zupan, P. Agrawal, M. Blanke and K. Gemmler, Y. Bai and P. Schwaller, P. Schwaller, D. Stolarski and A. Weiler, K.M. Zurek, G. Bertone, D. Hooper and J. Silk, B.-L. Young, K. Petraki and R.R. Volkas, L. Calibbi, A. Crivellin and B. Zald´ıvar, S. Renner and P. Schwaller, [8] [9] [6] [7] [3] [4] [5] [1] [2] [13] [14] [10] [11] [12] Open Access. Attribution License ( any medium, provided the original author(s) and source are credited. 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Poyraz, C. Roskas, D. Trocino, 2 , V.M. Ghete, J. Hrubec, M. Jeitler 1 – 23 – , M. Zarucki 1 , F. Torres Da Silva De Araujo, A. Vilela Pereira 3 , D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, 4 , R. Schöfbeck, M. Spanring, D. Spitzbart, A. Taurok, W. Waltenberger, 1 E. Belchior Batista Das Chagas,G.G. W. Da Carvalho, Silveira J. Chinellato H. Malbouisson, D. Matos Figueiredo,H. M. Nogima, Melo De W.L. Almeida, Prado C. DaE.J. Mora Silva, Tonelli Herrera, L.J. Manganote L. Sanchez Mundim, Rosas, A. Santoro, A. Sznajder, M. Thiel, K. Piotrzkowski, A. Saggio, M. VidalCentro Marono, Brasileiro S. Wertz, de J. Pesquisas Zobec F.L. Fisicas, Alves, Rio G.A. de Alves, M. Janeiro,M.E. Correa Brazil Pol, Martins P. Junior, Rebello G. Teles Correia Silva, C.Universidade Hensel, do A. Estado Moraes, do Rio de Janeiro, Rio de Janeiro, Brazil M. Tytgat, W. Verbeke, B. Vermassen, M.UniversitéCatholique de Vit, Louvain, N. Louvain-la-Neuve, Zaganidis Belgium H. Bakhshiansohi, O.M. Bondu, S. Delcourt, Brochet, A. G. Giammanco, Bruno, C. G. Caputo, Krintiras, P. David, V. C. Lemaitre, Delaere, A. Magitteri, A. Mertens, D. Beghin, B. Bilin,G. H. Fasanella, Brun, L. B. Favart,N. R. Clerbaux, Postiau, Goldouzian, G. E. A. Starling, De L. Grebenyuk, Lentdecker, Thomas, H. A.K.Ghent C. Delannoy, University, Kalsi, Vander Ghent, B. Velde, T. P. Belgium Dorney, Vanlaer, Lenzi, D.T. J. Cornelis, Vannerom, D. Q. Luetic, Dobur, Wang A. Fagot, M. Gul, I. Khvastunov Vrije Universiteit Brussel, Brussel, Belgium S. Abu Zeid, F.tkovskyi, Blekman, S. J. Lowette, D’Hondt,S. I. Tavernier, J. Marchesini, W. De Van S. Doninck, Clercq, P. Moortgat, Van K.UniversitéLibre Mulders, L. de Deroover, I. Bruxelles, Moreels, Van G. Bruxelles, Parijs Q. Flouris, Belgium Python, D. K. Lon- Skovpen, V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen, Antwerpen, Belgium E.A. De Wolf,P. D. Van Di Mechelen, N. Croce, Van Remortel X. Janssen, J. Lauwers, M. Pieters, H. Van Haevermaet, A. Escalante Del Valle,N. M. Krammer, Flechl, I. R. D.J. Krätschmer, Frühwirth Liko, Schieck T. Madlener,J. Wittmann, I. C.-E. Mikulec, Wulz N. Rad,Institute for H. Nuclear Rohringer, Problems, Minsk, Belarus Yerevan Physics Institute, Yerevan, Armenia A.M. Sirunyan, A. Tumasyan Institut fürHochenergiephysik, Wien, Austria W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Erö, The CMS collaboration JHEP02(2019)179 , b , SãoPaulo, b , E.M. Gregores a , T. Susa 7 a , A. Spiezia, J. Tao, Z. Wang, E. Yazgan, 6 – 24 – , T.R. Fernandez Perez Tomei a , Universidade Federal do ABC a , SandraS. Padula a , L. Calligaris a 8 , J. Zhao 6 , L. Yuan 5 , S.F. Novaes b , M. Finger Jr. 8 , C.A. Bernardes , X. Gao 5 a University of Cyprus, Nicosia, Cyprus M.W. Ather, A.F. Ptochos, Attikis, P.A. Razis, M. H. Rykaczewski Kolosova,Charles G. University, Prague, Mavromanolakis, Czech Republic J.M. Finger Mousa, C. Nicolaou, University of Split, Faculty ofZ. Science, Antunovic, Split, M. Kovac Croatia Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov C.F. GonzálezHernández,M.A. Segura Delgado University of Split, Facultyand of Naval Electrical Architecture, Engineering, Split, Mechanical Croatia B. Engineering Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac Tsinghua University, Beijing, China Y. Wang Universidad de Los Andes, Bogota,C. Colombia Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez, H. Liao, Z.H. Liu, Zhang, S. F. Zhang Romeo, S.M.State Shaheen Key Laboratory ofBeijing, Nuclear China Physics andY. Technology, Peking Ban, G. University, Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang, Z. Xu Beihang University, Beijing, China W. Fang Institute of High EnergyM. Physics, Ahmad, Beijing, J.G. China Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, A. Aleksandrov, R.M. Shopova, Hadjiiska, G. Sultanov P. Iaydjiev,University of A. Sofia, Sofia, Marinov, Bulgaria A. M. Dimitrov, L. Misheva, Litov, B. Pavlov, M. P. Petkov Rodozov, Brazil S. Ahuja P.G. Mercadante Institute for NuclearSciences, Research Sofia, Bulgaria and Nuclear Energy, Bulgarian Academy of Universidade Estadual Paulista JHEP02(2019)179 – 25 – 11 ¨ O. Sahin, M. Titov , S. Khalil , D. Gelé,U. Goerlach, M. Jansová,A.-C. Le Bihan, N. Tonon, 10 13 , C. Amendola, I. Antropov, F. Beaudette, P. Busson, C. Charlot, 12 , J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov, C. Collard, , S. Elgammal 13 10 , , J.-C. Fontaine 9 13 E. Conte P. Van Hove Centre de Calcul dedes l’Institut Particules, National CNRS/IN2P3, de Villeurbanne, Physique France S. Nucleaire Gadrat et de Physique M. Nguyen, C.J.B. Ochando, Sauvan, G. Y. Sirois, Ortona, A.G. P. Stahl Leiton, Paganini,Universitéde A. Strasbourg, P. Zabi, CNRS, Pigard, A. IPHC Zghiche J. UMRJ.-L. 7178, Rembser, Agram Strasbourg, R. France Salerno, Laboratoire Leprince-Ringuet, Ecole polytechnique,Paris-Saclay, CNRS/IN2P3, Palaiseau, Université France A. Abdulsalam R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C. Martin Perez, T. Tuuva IRFU, CEA, UniversitéParis-Saclay, Gif-sur-Yvette, France M. Besancon, F.A. Couderc, Givernaud, P. M. Gras, G. Dejardin, HamelG. de D. Monchenault, Negro, P. J. Jarry, Denegri, C. Rander, Leloup, J.L. A. E. Rosowsky, Locci, Faure, M. J. F. Malcles, Ferri, S. Ganjour, J. Havukainen, J.K.K. Heikkilä, Lassila-Perini, T. S. Järvinen, V. Laurila,E. S. Tuominen, Karimäki, R. J. Lehti, Tuominiemi Kinnunen, T. Lindén,P. T. Luukka, Siikonen, Lappeenranta T. Lampén, University Mäenpää,H. of Technology, Lappeenranta, Finland M. Raidal, C. Veelken Department of Physics, University ofP. Helsinki, Eerola, Helsinki, H. Finland Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland Egyptian Network of High EnergyY. Physics, Assran Cairo, Egypt National Institute of Chemical PhysicsS. and Bhowmik, A. Biophysics, Carvalho Tallinn, Antunes Estonia De Oliveira, R.K. Dewanjee, K. Ehataht, M. Kadastik, E. Ayala Universidad San Francisco de Quito,E. Quito, Carrera Ecuador Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Escuela Politecnica Nacional, Quito, Ecuador JHEP02(2019)179 , 16 , V. Sordini, 14 15 – 26 – , A. Geiser, J.M. Grados Luyando, A. Grohsjean, 17 8 , R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, 8 18 D. Gonzalez, P. Gunnellini, J.ner, Haller, A. R. Hinzmann, Kogler, A. N. Karavdina,M. G. Kovalchuk, Kasieczka, S. Niedziela, R. Kurz, Klan- C.E.N. V.C. Kutzner, Niemeyer, Scharf, P. J. D. Schleper, Lange, S.F.M. Nowatschin, D. Schumann, Stober, J. Marconi, A. Schwandt, M. A. J. J. Stöver, Perieanu, Vanhoefer, Sonneveld, Multhaup, B. H. A. Vormwald, Stadie, I. Reimers, G. Zoi Steinbrück, O. Rieger, G. Mittag, J. Mnich,P. V. Saxena, P. Myronenko, Schütze,C. Schwanenberger, R. S.K. Shevchenko, Pflitsch, A.A. Singh, D. Vagnerini, H. G.P. Pitzl, Tholen, Van Onsem, A. O. Turkot, R. Raspereza, Walsh, M.University Y. of Savitskyi, Wen, K. Hamburg, Wichmann, Hamburg, C. Germany R. Wissing, Aggleton, O. S. Bein, Zenaiev L. Benato, A. Benecke, V. Blobel, T. Dreyer, A. Ebrahimi, E. Garutti, M.M. Defranchis, C.A. Diez Elwood, Pardos, D.M. E. Dom´ınguez Damiani, Guthoff, Eren, G. M.C. E. Eckerlin, Kleinwort, Haranko, T. Gallo J. A. Knolle, Eichhorn, W. D. W. Harb, Lohmann Krücker, Lange, J. A. Lelek, Hauk, T. Lenz, H. J. Jung, Leonard, K. M. Lipka, Kasemann, J. Keaveney, C. Pistone, O. Pooth, D. Roy,Deutsches H. Elektronen-Synchrotron, Sert, Hamburg, A. Stahl Germany M. Aldaya Martin,O. Behnke, T. U. Behrens, Arndt, A. Mart´ınez,D. Bertsche,V. Bermúdez A.A. C. Bin Botta, Anuar, Asawatangtrakuldee, K. A. Borras I. Campbell, Babounikau, P. K. Connor, Beernaert, C. Contreras-Campana, V. Danilov, A. De Wit, T. Hebbeker, C. Heidemann,A. K. Meyer, Hoepfner, P. Millet, H. S. Mukherjee, Keller, T.D. L. Pook, Teyssier, Mastrolorenzo, M. S. Radziej, M. Thüer H. Merschmeyer, Reithler, M. Rieger,RWTH A. Aachen Schmidt, University, III. PhysikalischesG. Institut O. Flügge, B, Hlushchenko, Aachen, T. Germany Kress, A. T. Künsken, Müller,A. Nehrkorn, A. Nowack, RWTH Aachen University, I. PhysikalischesC. Institut, Aachen, Autermann, Germany L.C. Feld, Schomakers, M.K. J. Kiesel, Schulz, M. K. Teroerde, B.RWTH Klein, Aachen Wittmer M. University, III. Lipinski, PhysikalischesA. M. Institut Albert, A, Preuten, D. Aachen, Duchardt, M.P. Germany M. Rauch, Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, A. Güth, Georgian Technical University, Tbilisi, Georgia A. Khvedelidze Tbilisi State University, Tbilisi, Georgia Z. Tsamalaidze de Physique Nucléairede Lyon, Villeurbanne,S. France Beauceron, C. Bernet,H. G. El Mamouni, Boudoul, J. N. Fay, L. Chanon, Finco,I.B. S. Laktineh, R. Gascon, H. Chierici, M. Gouzevitch, Lattaud, D. G. M.G. Grenier, Contardo, Lethuillier, Touquet, B. P. M. Ille, L. Depasse, F. Vander Mirabito, Lagarde, Donckt, S. S. Perries, Viret A. Popov Universitéde Lyon, UniversitéClaude Bernard Lyon 1, CNRS-IN2P3, Institut JHEP02(2019)179 , S. Kudella, 14 , S.K. Swain 22 ´ A. Vámi,V. Veszpremi, , D.K. Sahoo 23 – 27 – ´ A. Hunyadi, F. Sikler, T. , 20 , S.M. Heindl, U. Husemann, I. Katkov , A. Makovec, J. Molnar, Z. Szillasi 15 21 † , C. Kar, P. Mal, K. Mandal, A. Nayak 22 , M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O. Surányi, 19 S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute ofIndia Science Education and Research,S. HBNI, Bahinipati Bhubaneswar, N. Beni, S. Czellar, J. Karancsi Institute of Physics, University ofP. Debrecen, Raics, Debrecen, Z.L. Trocsanyi, Hungary B. Ujvari Indian Institute of Science (IISc), Bangalore, India Wigner Research Centre for Physics,G. Budapest, Bencze, Hungary C.G. Hajdu, Vesztergombi D. Horvath Institute of Nuclear Research ATOMKI, Debrecen, Hungary MTA-ELTE Particle LendületCMS and Nuclear Physics Group, EötvösLoránd University, Budapest, Hungary M. Bartók G.I. Veres K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina,Ioánnina,Greece I. Evangelou, C. Foudas,I. P. Papadopoulos, Gianneios, E. P. Paradas, Katsoulis, J. P. Strologas, Kokkas, F.A. S. Triantis, D. Mallios, Tsitsonis N. Manthos, National and Kapodistrian University ofG. Karathanasis, Athens, S. Athens, Kesisoglou, P. Greece Kontaxakis, A.E. Panagiotou, Tziaferi, I. Papavergou, K. N. Vellidis Saoulidou, National Technical University of Athens, Athens, Greece C. Wöhrmann,R. Wolf Institute of NuclearParaskevi, and Greece Particle Physics (INPP),G. NCSR Anagnostou, Demokritos, G. Daskalakis, Aghia T.Giotis Geralis, A. Kyriakis, D. Loukas, G. Paspalaki, I. Topsis- M. Akbiyik, C. Barth, M.W. Baselga, S. De Baur, E. Boer, Butz,M.A. R. Harrendorf, Caspart, A. T. F. Chwalek, Dierlamm, F. Hartmann S. Colombo, K. Mitra, El M.U.M. Morabit, Mozer, Schröder,I. N. Th. Shvetsov, Faltermann, H.J. Müller, M. Simonis, B. Musich, R. Freund, M. Ulrich, M. Plagge, S. Giffels, G. Wayand, Quast, M. Weber, K. T. Rabbertz, Weiler, Karlsruher Institut fuer Technologie, Karlsruhe, Germany JHEP02(2019)179 , , , , , , , , a 24 24 a,b a,b a,b a,b a,b , S. My , C. Ciocca a,b , Bari, Italy , A. Gelmi , E. Fontanesi, c a,b a 25 , G. Selvaggi a,b a , L. Cristella a,c , L. Fiore a , G. Miniello , S. Braibant-Giacomelli a,b a , M. Zeinali , S.S. Chhibra , A. Fanfani a,b a , Bologna, Italy a , A. Ranieri 27 b a , G. Zito , M. Khakzad, M. Mohammadi Na- a 26 , D. Creanza , F. Errico a , Politecnico di Bari b , M. Maggi a,b , F. Fabbri a a,c , F.R. Cavallo , L. Borgonovi , R. Radogna a,b a,b – 28 – a,c , P. Verwilligen a , G. Maggi , A. Colaleo , A. Di Florio a,b a,b , A. Castro a,b , S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A. Purohit, , Universitàdi Bologna , G.M. Dallavalle a , R. Bhattacharya, S. Bhattacharya, U. Bhawandeep a,b 24 , D. Bonacorsi 24 a,b , G. Pugliese , Universitàdi Bari a,b , R. Venditti a a,b a , S. Lezki , G. Majumder, K. Mazumdar, N. Sahoo, T. Sarkar a,b 25 , C. Calabria , M. De Palma , P. Capiluppi , M. Bharti , M. Cuffiani a,b , E. Eskandari Tadavani, S.M. Etesami a,c a,b 24 , C. Battilana a,b 26 a , A. Pompili , L. Silvestris , M. Ince a 24 a,b a,c A. Sharma INFN Sezione di Bologna G. Abbiendi R. Campanini G. Codispoti INFN Sezione di Bari M. Abbrescia N. De Filippis G. Iaselli S. Nuzzo S. Chenarani jafabadi, M. Naseri, F. Rezaei Hosseinabadi,University B. College Safarzadeh Dublin, Dublin,M. Ireland Felcini, M. Grunewald S. Banerjee, S. Bhattacharya,S. S. Kumar, Chatterjee, M. P. Maity Das, M.Indian Guchait, Institute Sa. of Jain, Science S.S. Education Karmakar, Chauhan, and S. Research Dube, (IISER), V. Pune, Hegde,Institute A. India for Kapoor, Research K. Kothekar, in S. Fundamental Pandey, Sciences A. (IPM), Rane, Tehran, S. Iran Sharma R. Chudasama, D. Dutta, V. Jha,Tata V. Institute Kumar, of P.K. Netrakanti, Fundamental L.M. Research-A,T. Pant, Mumbai, Aziz, P. India Shukla M.A. Bhat, S. Dugad,Tata G.B. Institute Mohanty, N. of Sur, Fundamental B. Research-B, Sutar, Mumbai, RavindraKumar India Verma S. Thakur Indian Institute of Technology Madras,P.K. Behera Madras, India Bhabha Atomic Research Centre, Mumbai, India M. Naimuddin, P. Priyanka, K. Ranjan, AashaqSaha Shah, Institute R. of Sharma NuclearR. Physics, HBNI, Bhardwaj Kolkata, India D. Bhowmik, S. Dey,P.K. S. Dutt Rout, A. Roy, S. Roy Chowdhury, G. Saha, S. Sarkar, M. Sharan, B. Singh S. Bansal, S.B.A. Beri, Kaur, V. M. Bhatnagar, Kaur,J.B. Singh, S. S. A.K. Kaur, Chauhan, Virdi, P. G. R. Kumari, Walia University Chawla, M. of Lohan, N. Delhi, A. Delhi, Dhingra,A. Mehta, India Bhardwaj, R. K. B.C. Gupta, Choudhary, Sandeep, R.B. Garg, S. M. Sharma, Gola, S. Keshri, Ashok Kumar, S. Malhotra, Panjab University, Chandigarh, India JHEP02(2019)179 , , , , , , , , , , , , , , , , a a a a a a,b 15 15 a,b a,b a,b a,b a,b a,b a,b a,b a,b a, a,b, , Roma, d , Milano, b , D. Strom , F. Fienga , A. Rossi a a , E. Focardi , D. Pedrini a,c , G. Zumerle , S. Malvezzi , P. Lariccia , R. Rossin , S. Marcellini , Napoli, Italy, a,b a,b a,b a , P. Paolucci b a,b , M.E. Dinardo a,b , F. Gasparini a,b , M. Ressegotti 15 a 15 a a,b , F. Primavera a,d, a,d, a , F. Fabozzi , P. Zotto , G. Sguazzoni , V. Re , L. Fanò a,b , P. Lujan, M. Margoni , M. Menichelli 28 a,b a,b a , Catania, Italy , S. Lo Meo a,b , Perugia, Italy a, a,b b , Firenze, Italy , Genova, Italy , C. Tuve b a,b b b , M. Malberti , Padova, Italy, Universitàdi , M. Paganoni , A. Bragagnolo, R. Carlin a,b b , U. Dosselli a a,b , S. Meola , R. D’Alessandro , P. Ronchese a a,b a a,b a , Pavia, Italy , S. Di Guida b a,b , S. Tosi 15 a , A. Perrotta , L. Russo a,b , M. Zanetti a,b, a a,b , S.P. Ratti a,b a,b , V. Mariani , F. Iemmi a,b , L. Lista , A. Di Crescenzo , A. Tricomi a a,b a,b , P. Govoni , T. Dorigo , C. Civinini – 29 – , D. Ciangottini , A. Boletti a,b a a,b , Universitàdi Milano-Bicocca a a,b a,b a,b , E. Robutti a,b , D. Zuolo , V. Ciriolo , M. Tosi a,b a , S. Paoletti , N. Pozzobon a , P. Vitulo a a,b a,b a,b a,b , S.Y. Hoh, S. Lacaprara , Potenza, Italy, UniversitàG. Marconi c a , F. Monti, L. Moroni , F.L. Navarria , Universitàdi Catania , Universitàdi Perugia , Universitàdi Firenze , Universitàdi Genova a , Universitàdi Napoli ‘Federico II’ a a , Universitàdi Padova , V. Ciulli a a a a , A. De Iorio , P. Montagna , W.A. Khan a , R. Potenza , Universitàdi Pavia , L. Guiducci a , G. Mantovani a,b a , A. Ghezzi a,b a a , C. Cecchi , N. Tosi a,c a a,b a a a , D. Bisello , I. Vai , F. Ravera a a , F. Brivio a,b b a,b , M. Meschini , J. Pazzini a,b a,b , D. Spiga , A. Gozzelino , D. Menasce , A. Tiko, E. Torassa , N. Cavallo , C. Grandi , E. Manoni , S. Gennai a , P. Salvini a,b , A. Magnani a , P. De Castro Manzano a,b a,b , G.M. Bilei , A. Di Mattia , T. Tabarelli de Fatis a,b , A. Montanari , E. Voevodina a , A. Beschi , K. Chatterjee a , G.P. Siroli a,b a a a,b a a,b , A.O.M. Iorio a,b a,b a,b a,b a a,b a , Trento, Italy , R. Mulargia , N. Bacchetta c a a C. Riccardi INFN Sezione di Perugia M. Biasini R. Leonardi A. Santocchia U. Gasparini A.T. Meneguzzo F. Simonetto INFN Sezione di Pavia A. Braghieri INFN Sezione di Padova Trento P. Azzi P. Checchia INFN Sezione di Napoli Universitàdella Basilicata Italy S. Buontempo G. Galati C. Sciacca A. Benaglia S. Fiorendi A. Massironi S. Ragazzi L. Benussi, S. Bianco, F. Fabbri,INFN D. Piccolo Sezione di Genova F. Ferro INFN Sezione diItaly Milano-Bicocca G. Barbagli G. Latino, P. Lenzi L. Viliani INFN Laboratori Nazionali di Frascati, Frascati, Italy G. Masetti T. Rovelli INFN Sezione di Catania S. Albergo INFN Sezione di Firenze P. Giacomelli JHEP02(2019)179 , , , , , , , , , , , a a a a a a,b a,b a,b a,b a,b a,c , V. Sola a,b , A. Venturi , R. Bellan a,b , M. Diemoz , L. Borrello, a , F. Pandolfi a a,b , M. Pelliccioni , V. Monaco a,b , A. Messineo a,b a , L. Giannini , R. Covarelli , G. Della Ricca a,b a,c a,c a,b a,b , Rome, Italy b , K. Shchelina , G. Tonelli , N. Bartosik a a,b , T. Boccali a,c a , N. Pastrone , F. Fiori , E. Di Marco , F. Santanastasio a , G. Organtini , Trieste, Italy a,b a , M. Costa a , E. Migliore , Torino, Italy, Universitàdel b , G. Mandorli a,b a , A. Da Rold b a a , Scuola Normale Superiore di a,c b , R. Sacchi , R. Tenchini a a,c , G. Fedi , M. Arneodo a , L. Pacher , C. Rovelli , L. Bianchini a,b a,b , D. Del Re a a,b , S. Maselli , P. Meridiani – 30 – , F. Cossutti , E. Manca a , S. Cometti a,b a a,b a,c a,b , M. Ruspa a , P. Spagnolo a,b , S. Argiro 29 a,c , R. Dell’Orso , Universitàdi Trieste , S. Rahatlou , Universitàdi Torino , G. Bagliesi a , Sapienza Universitàdi Roma a , Universitàdi Pisa a,b , M. Casarsa a a , M. Cipriani , M.M. Obertino a,b , C. Mariotti a , F. Cenna a , F. Ligabue a a,b a a a a,b , A. Staiano , Novara, Italy , B. Marzocchi c , A. Romero a,b a,b , T.J. Kim , G. Rolandi a,b 30 a,b , F. Preiato , R. Arcidiacono , P. Azzurri , A. Zanetti a , B. Kiani a,b , M.A. Ciocci , M. Monteno , F. Cavallari a,b a a , D. Soldi a , V. Candelise a,b a , M.T. Grippo a,b , N. Cartiglia , E. Longo a,b a,b a a , A. Rizzi a a,b , Pisa, Italy c Sejong University, Seoul, Korea H.S. Kim Seoul National University, Seoul, Korea J. Almond, J. Kim,S.h. Seo, J.S. U.K. Kim, Yang, H. H.D. Yoo, Lee, G.B. K. Yu Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, B. Francois, J. Goh Korea University, Seoul, Korea S. Cho, S. Choi, Y.S.K. Go, Park, D. Y. Gyun, Roh S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S. Lee, J. Lim, Chonnam National University, Institute for UniverseKwangju, and Korea Elementary Particles, H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea S. Belforte F. Vazzoler Kyungpook National University, Daegu, Korea D.H. Kim, G.N. 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JHEP02(2019)179 – 40 – University, Tehran, Iran University, Budapest, Hungary Moscow, Russia Also at University of ChineseAlso Academy at of Institute Sciences, for Beijing,Also Theoretical China at and Joint Experimental Institute Physics, for Moscow,Also Russia Nuclear at Research, Suez Dubna, University, Suez, Russia Egypt Also at Vienna University ofAlso Technology, at Vienna, IRFU, Austria CEA,Also Gif-sur-Yvette, UniversitéParis-Saclay, France at Universidade Estadual deAlso Campinas, at Campinas, Federal University Brazil ofAlso Rio at Grande UniversitéLibre de do Bruxelles, Sul, Bruxelles, Porto Belgium Alegre, Brazil Deceased Also at Universitàdegli Studi diAlso Siena, at Siena, Scuola Italy NormaleAlso e at Sezione Kyunghee dell’INFN, University, Pisa, Seoul,Also Italy Korea at International Islamic UniversityAlso of at Malaysia, Malaysian Kuala Nuclear Lumpur, Agency, MOSTI, Malaysia Kajang, Malaysia Also at Indian InstituteAlso of at Technology Bhubaneswar, Institute Bhubaneswar, of India Also Physics, Bhubaneswar, at India Shoolini University, Solan,Also India at University of Visva-Bharati,Also Santiniketan, at India Isfahan University ofAlso Technology, Isfahan, at Iran Plasma Physics Research Center, Science and Research Branch, Islamic Azad Also at University of Hamburg,Also Hamburg, at Germany Brandenburg University ofAlso Technology, Cottbus, at Germany MTA-ELTE LendületCMS Particle andAlso Nuclear at Physics Institute of Group,Also Nuclear EötvösLoránd at Research ATOMKI, Institute Debrecen, of Hungary Physics, University of Debrecen, Debrecen, Hungary Also at Department of Physics,Also King at Abdulaziz Universitéde Haute University, Alsace, Jeddah,Also Mulhouse, Saudi France Arabia at Skobeltsyn Institute ofAlso Nuclear at CERN, Physics, EuropeanAlso Organization Lomonosov at for RWTH Nuclear Moscow Aachen Research, University, Geneva, State III. Switzerland Physikalisches University, Institut A, Aachen, Germany Now at British University inAlso Egypt, at Cairo, Zewail Egypt City of Science and Technology, Zewail, Egypt : † 6: 7: 8: 9: 1: 2: 3: 4: 5: 28: 29: 30: 31: 32: 22: 23: 24: 25: 26: 27: 17: 18: 19: 20: 21: 12: 13: 14: 15: 16: 10: 11: M. Brodski, J.B. Buchanan, Gomber, C. M. Caillol,K. Grothe, Long, D. R. M. Loveless, Carlsmith, Herndon, T. Ruggles, S. A. A. Dasu, Savin, Hervé, U. V. I. Hussain, Sharma, N. De P. Smith, Bruyn, Klabbers, W.H. Smith, L. A. N. Woods Dodd, Lanaro, M.W. Arenton, P. Barria,T. B. Sinthuprasith, Y. Cox, Wang, R. E. Wolfe, Hirosky, F.Wayne M. State Xia Joyce, University, Detroit, A. U.S.A. Ledovskoy,R. H. Harr, Li, P.E. Karchin, C. N. Neu, Poudyal, J.University of Sturdy, P. Wisconsin Thapa, — S. Madison, Zaleski Madison, WI, U.S.A. University of Virginia, Charlottesville, U.S.A. JHEP02(2019)179 , Pavia, Italy b – 41 – , Universitàdi Pavia a United Kingdom Belgrade, Serbia (MEPhI), Moscow, Russia Also at Beykent University, Istanbul,Also Turkey at Bingol University, Bingol,Also Turkey at Sinop University, Sinop,Also Turkey at Mimar SinanAlso University, Istanbul, at Istanbul, Texas Turkey A&M UniversityAlso at at Qatar, Kyungpook Doha, National Qatar University, Daegu, Korea Also at Monash University, FacultyAlso of at Science, Bethel Clayton, University, Australia St.Also Paul, at U.S.A. Karamano˘gluMehmetbey University, Karaman,Also Turkey at Utah Valley University,Also Orem, at U.S.A. Purdue University, West Lafayette, U.S.A. Also at Kafkas University, Kars,Also Turkey at Istanbul University, FacultyAlso of at Science, Istanbul Istanbul, Bilgi Turkey University,Also Istanbul, at Turkey Hacettepe University, Ankara,Also Turkey at Rutherford AppletonAlso Laboratory, Didcot, at United Kingdom School of Physics and Astronomy, University of Southampton, Southampton, Also at Istanbul Aydin University,Also Istanbul, at Turkey Mersin University, Mersin,Also Turkey at Piri ReisAlso University, Istanbul, at Turkey Ozyegin University, Istanbul,Also Turkey at Izmir InstituteAlso of at Technology, Izmir, Marmara Turkey University, Istanbul, Turkey Also at National andAlso Kapodistrian at University Riga of Technical Athens, University, Athens,Also Riga, Zurich, Greece at Latvia Switzerland UniversitätZürich, Also at Stefan Meyer InstituteAlso for at Subatomic Adiyaman University, Physics Adiyaman, (SMI), Turkey Vienna, Austria Also at P.N. Lebedev PhysicalAlso Institute, at Moscow, California Russia InstituteAlso of at Technology, Pasadena, Budker U.S.A. Institute ofAlso Nuclear at Physics, Faculty of Novosibirsk, Physics, Russia Also University at of INFN Belgrade, Sezione Belgrade,Also di Serbia Pavia at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Also at Warsaw University ofAlso Technology, Institute at of Institute Electronic for Systems,Now Nuclear Warsaw, Research, Poland at Moscow, Russia National Research NuclearAlso at University St. Petersburg ‘Moscow StateAlso Polytechnical at Engineering University, University St. of Physics Petersburg, Florida, Russia Gainesville, Institute’ U.S.A. Also at Consejo Nacional de Ciencia y Tecnolog´ıa,Mexico city, Mexico 67: 68: 69: 70: 71: 72: 62: 63: 64: 65: 66: 56: 57: 58: 59: 60: 61: 50: 51: 52: 53: 54: 55: 45: 46: 47: 48: 49: 39: 40: 41: 42: 43: 44: 34: 35: 36: 37: 38: 33: