Bose-Einstein correlations of same-sign charged pions in the forward region in pp collisions at √s=7 TeV

JHEP12(2017)025 Published for SISSA by Springer Received:September 7, 2017 Revised:November 15, 2017 Accepted:November 28, 2017 Published:December 6, 2017 Bose-Einstein correlations of same-sign charged pions in the forward region in pp collisions at √s= 7 TeV The LHCb collaboration E-mail: [email protected] Abstract: Bose-Einstein correlations of same-sign charged pions, produced in protonproton collisions at a 7 TeV centre-of-mass energy, are studied using a data sample collected by the LHCb experiment. The signature for Bose-Einstein correlations is observed in the form of an enhancement of pairs of like-sign charged pions with small four-momentum difference squared. The charged-particle multiplicity dependence of the Bose-Einstein correlation parameters describing the correlation strength and the size of the emitting source is investigated, determining both the correlation radius and the chaoticity parameter. The measured correlation radius is found to increase as a function of increasing charged-particle multiplicity, while the chaoticity parameter is seen to decrease. Keywords: Hadron-Hadron scattering (experiments), Particle correlations and fluctuations, QCD ArXiv ePrint: 1709.01769 Open Access, Copyright CERN, for the benefit of the LHCb Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP12(2017)025 JHEP12(2017)025 Contents 1 Introduction 1 2 BEC measurement 2 2.1 Two-particle correlation function 2 2.2 Reference sample 3 2.3 Double ratio 3 2.4 Coulomb correction 3 3 Detector and dataset 4 4 Selection and model fitting 5 5 Systematic uncertainties 7 6 Results 9 7 Summary and conclusions 12 The LHCb collaboration 17 1 Introduction Multiparticle production within the process of hadronisation can be investigated by measuring Bose-Einstein correlations (BEC) between indistinguishable bosons [1,2]. The technique to study the BEC effect in particle physics is the analogue of the Hanbury-BrownTwiss (HBT) intensity interferometry [3–5]. The production of identical bosons that are close in phase space is enhanced by the presence of BEC. The measurements of the quantum interference effect between indistinguishable particles emitted by a finite-size source are useful to understand the space-time properties of the hadron emission volume. Since the first observation of BEC in identically charged pions produced in p¯pcollisions [6], the effect has been studied for multiboson systems produced in leptonic, hadronic and nuclear collisions [7–32]. At the LHC, the BEC effect has been studied by the ALICE, ATLAS and CMS collaborations in proton-proton [26–30], proton-lead [31] and lead-lead [31,32] collisions. Dependences of the BEC effect upon various observables have been studied, including charged-particle multiplicity, average transverse momentum of the particle pair and boson mass. The latter has been reported by the LEP experiments [7–21], and can be interpreted within some theoretical models [33–36]. – 1 – JHEP12(2017)025 In this paper, the first study of the BEC effect in pp collisions in the forward region is presented. The BEC parameters characterising the correlation radius and the chaoticity of the correlation source are measured. 2 BEC measurement Quantum interference effects are probed by studying the Lorentz invariant quantity Q[2,37] of two indistinguishable particles of rest mass mand four-momenta q1 and q2 Q=p−(q1−q2)2=pM2−4m2,(2.1) which gives a measure of the phase-space separation of the two-particle system of invariant mass M. 2.1 Two-particle correlation function The BEC effect is expected to manifest itself as an enhancement in the two-particle correlation function in the low-Qregion below ∼0.5 GeV/c2, expressed as [38] C2(Q) = ρ2(Q) ρ0 2(Q),(2.2) where ρ2(Q) is the two-particle density function for like-sign pairs of indistinguishable particles, as defined in ref. [38], and ρ0 2(Q) is the corresponding density function without the BEC effect, which is constructed as described in section 2.2. The densities ρ2(Q) and ρ0 2(Q) are normalised to unity, such that they can be interpreted as probability density functions. The correlation function C2(Q) is commonly parameterised as a Fourier transform of the source density distribution, C2(Q) = N(1 + λe−|RQ|αL) [39], where the parameter R, the correlation radius, can be interpreted as the radius of the spherically symmetric source of the emission volume, Naccounts for the overall normalisation and λis the chaoticity parameter, which accounts for the partial incoherence of the source [40]. The chaoticity parameter can vary from zero, in the case of a completely coherent source, to unity for an entirely chaotic source. The Levy index of stability [39], αL, accounts for the assumed density distribution. The radial distribution of the static source corresponding to the case of αL= 1 is used in the present analysis C2(Q) = N(1 + λe−RQ)×(1 + δ·Q),(2.3) where the δparameter accounts for long-range correlations, e.g. related to the transverse momentum conservation. This extended parameterisation follows better the Qdistribution in data, including in the low-Qregion below ∼0.5 GeV/c2[41]. The correlation function is, to first order, independent of the single-particle acceptance and efficiency. By construction of the correlation function, the effects due to the detector occupancy, acceptance and material budget are accounted for by dividing the Qdistribution for like-sign pion pairs by a reference distribution. – 2 – JHEP12(2017)025 2.2 Reference sample The reference sample used to construct the ρ0 2(Q) density function, present in the denominator of eq. (2.2), should reflect the distribution without the BEC effect while maintaining all other correlations. A number of reference samples can be constructed but none fully satisfies the above conditions. The reference sample may be constructed using experimental data, or with simulated events incorporating the detector interactions. A data-driven “event-mixed” reference sample [42] is used in the present analysis. This approach is based on the choice of two identical bosons, each originating from different events, which naturally do not contain the BEC effect. However, this method of constructing boson pairs may not contain other correlations present in the same-sign boson data sample, such as correlations due to Coulomb interactions or long-range effects. Alternative methods have been considered for constructing the reference sample. For example, the reference sample could consist of opposite-sign charged bosons originating from the same pp interaction. As in the event-mixed reference sample, the main advantage of the opposite-sign approach is that the reference distribution is derived directly from data. However, the opposite-sign charge pairs may also originate from resonances which result in local enhancements in the Qspectrum. Furthermore, correlations arising from the attraction of opposite charges are present in such a sample. Another method is to employ the simulated Qdistribution without the BEC effect. In this case, the crucial requirement is a good level of agreement between data and simulated samples in the distributions of crucial variables, e.g. the particle momenta. The absence of the Coulomb and spin effects in generators based on the Lund Model [43] may impinge on the correctness of this method. 2.3 Double ratio To account for imperfections in the reference distribution derived from the data a “double ratio” rdis commonly used in BEC studies rd(Q)≡C2(Q)data C2(Q)simulation ,(2.4) where C2(Q)data denotes the correlation function in the data constructed using the eventmixed reference sample, while C2(Q)simulation indicates the correlation function in the simulation without the BEC effect, using an event-mixed sample built with simulated events in the same way as for data. The correlation function in the simulation without the BEC effect includes the simulated long-range correlations that are also present in data. Therefore, if the long-range correlations are correctly modelled, a constant rd(Q) distribution is expected in the high-Qregion up to ∼2.0 GeV/c2. In the present analysis the BEC effect is measured by fitting the rd(Q) distribution with the event-mixed reference sample, using the parameterisation given in eq. (2.3). 2.4 Coulomb correction Final-state interactions involving both electromagnetic (Coulomb) and strong forces are present in the low-Qregion below ∼0.5 GeV/c2, and may potentially affect the distributions – 3 – JHEP12(2017)025 of the analysed observables. In the low-Qregion, the Coulomb repulsion between two identically charged hadrons alters the correlation function C2(Q) by decreasing the BEC effect. This effect is corrected for with the Gamov penetration factor [44,45], G2(Q), by applying a weight per particle pair 1/G2(Q), where G2(Q) = 2πζ e2πζ −1,ζ=±αm Q, and mand αdenote the particle rest mass and the fine-structure constant, respectively. The sign of ζ is positive for same-charge and negative for opposite-charge pairs of hadrons. The Coulomb interactions are not present in the simulated samples used in the analysis. This effect therefore has to be corrected for in the data. 3 Detector and dataset The LHCb detector [46] is a single-arm forward spectrometer designed for the study of particles containing bor cquarks. The detector includes a high-precision tracking system consisting of a silicon-strip vertex detector (VELO) [47] surrounding the pp interaction region and covering the pseudorapidity range 2 < η < 5, a large-area silicon-strip detector located upstream of a dipole magnet with a bending power of about 4 Tm, and three stations of silicon-strip detectors and straw drift tubes [48] placed downstream of the magnet. The tracking system provides a measurement of momentum, p, with a relative uncertainty that varies from 0.5% at low momentum to 1% at 200 GeV/c. The minimum distance of a track to a primary vertex (PV), the impact parameter (IP), is measured with a resolution of (15 + 29/pT)µm, where pTis the component of ptransverse to the beam, in GeV/c. Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov detectors [49]. Photon, electron and hadron candidates are identified by a calorimeter system consisting of scintillating-pad and preshower detectors, an electromagnetic calorimeter and a hadronic calorimeter. Muons are identified by a system composed of alternating layers of iron and multiwire proportional chambers [50]. The trigger [51] consists of a hardware stage, based on information from the calorimeter and muon systems, followed by a software stage, which applies a full event reconstruction. In the present analysis, a dataset of no-bias and minimum-bias triggered events collected in 2011 at a centre-of-mass energy of √s= 7 TeV is used. The no-bias trigger selects events randomly, while the minimum-bias trigger requires at least one reconstructed VELO track. The data were collected with an average number of visible interactions per bunch crossing1(pile-up) of 1.4 [52]. In order to eliminate biases related to the trigger requirements, a sample of “independent pp interactions” is constructed as described in section 4. In the simulation, pp collisions are generated using Pythia 8 [53] with a specific LHCb configuration [54] and without including the BEC effect. Decays of hadronic particles are described by EvtGen [55], in which final-state radiation is generated using Photos [56]. The interaction of the generated particles with the detector and its response are implemented using the Geant4 toolkit [57,58], as described in ref. [59]. To study systematic effects, an additional sample is simulated using Pythia 6.4 [60] with the Perugia0 [61] tune. 1A visible interaction corresponds to the PV reconstructed with at least five VELO tracks. – 4 – JHEP12(2017)025 4 Selection and model fitting The analysis uses a sample of events that may contain multiple pp collisions. In the absence of trigger requirements each pp interaction in the event can be analysed separately. Therefore, if the event is selected by the no-bias trigger, all PVs are accepted. In the case of events with multiple pp collisions selected by the minimum-bias trigger, the related biases are suppressed by randomly removing one of the PVs containing the track(s) on which the trigger is fired. The correlation function is constructed using pairs of same-sign pions. The particle identification (PID) is based on the output of a neural network employing subdetector information that quantifies the probability for a particle to be of a certain kind [62]. Such probabilities are calibrated to account for differences between data and the simulation that is used to train the neural network. The corrected values are derived from the data distributions using dedicated PID calibration samples [49]. A high purity of the pion sample has to be ensured, but without suppressing low-momentum pions which mostly contribute to the signal region at low Q. The optimal limit on the pion identification probability is applied at the point where the signal enhancement in the low-Qregion below ∼0.5 GeV/c2 for data begins to saturate. The pion purity with this selection remains high (∼98%). Additional vetoes on the kaon and proton identification probabilities are also imposed. The following single particle requirements are applied. The selection requires that all pion candidates must have reconstructed track segments in the VELO, with 2 < η < 5, and tracking stations downstream of the magnet. Each track must have a good-quality track fit, pT>0.1 GeV/c, and no associated signal in the muon stations. Both pion candidates must be assigned to the same PV. Particles are assigned to the PV for which the χ2value of the impact parameter, χ2 IP, is the smallest, where χ2 IP is defined as the difference in the vertex-fit χ2of a given PV reconstructed with and without the track under consideration. A loose requirement on the track IP, IP <0.4 mm, is applied to retain most of the particles originating from a given PV. In order to reduce the contamination from fake and clone tracks,2in the case where the tracks have all the same hits deposited in the VELO subdetector, only the track with the best χ2is retained. In addition, fake tracks are removed using the requirements on the track χ2and the output of a dedicated neural network [62]. In the region Q < 0.05 GeV/c2, the separation in momentum between two particles is degraded and is not well simulated. The discrepancy between data and simulated track pairs tends to increase as Qapproaches zero. Investigations using simulation indicate that there is a significant fraction of pion pairs containing fake and clone tracks in the region Q < 0.05 GeV/c2for all activity classes. The double ratio is approximately constant and close to unity in the high-Qregion up to Q∼2.0 GeV/c2(see figure 2), which indicates that the long-range correlations are modelled accurately in this region. Consequently, the fits to the rddistributions are restricted to the range 0.05 < Q < 2.0 GeV/c2. 2Fake tracks are wrongly reconstructed tracks which combine the hits deposited by multiple particles in the tracking detectors. Clone tracks are two or more tracks reconstructed by mistake from the hits deposited in detectors by a single particle. – 5 – JHEP12(2017)025 VELO track multiplicity per PV 0 20 40 60 Number of reconstructed PVs 10 2 10 3 10 4 10 LHCb = 7 TeVs low activity (48%) medium activity (37%) high activity (15%) Figure 1. Multiplicity of reconstructed VELO tracks assigned to a PV for the 2011 no-bias sample. Different colours indicate three activity classes defined as fractions of the full distribution. The minimum value of the track multiplicity to accept reconstructed PV is five. The BEC effect is expected to be largest in the low-Qregion below ∼0.5 GeV/c2, where it may be affected by same-sign clone tracks. Such clone pion pairs should manifest themselves as an enhancement in the distribution of the differences of the tangents of the track momenta of the two particles, where the tangents are measured in the xz and yz planes before the magnet, with the zaxis defined along the beam direction. The tangents are used to estimate the number of clone tracks remaining after the final selection, and the clone tracks can be suppressed with a requirement on the difference between the tangents of the two particles in a pair. Pion pairs are removed from the analysis if both |∆tx|and |∆ty| are less than 0.3 mrad, where ∆txand ∆tyare the differences of the tangents of the track momenta of the two particles in the xz and yz planes. After applying these requirements, the effect of the clone particles is found to be negligible in the region Q > 0.05 GeV/c2. The BEC parameters are studied as a function of the charged-particle multiplicity. However, the measured charged-particle multiplicities cannot be directly used to compare results among different experiments, mainly because the detector acceptances may not overlap and the reconstruction efficiencies may differ. This is why activity classes are introduced, reflecting the total multiplicity in the full solid angle. Three activity classes are defined in the range 2 < η < 5 according to the multiplicity of reconstructed VELO tracks assigned to a PV, which is a good probe of the total multiplicity. These activity classes are illustrated in figure 1. The low activity class corresponds to a fraction of 48% of PVs with lowest multiplicities (from 5 to 10 tracks). The medium activity class contains the 37% of PVs with higher multiplicities (from 11 to 20 tracks). Finally, the high activity class contains 15% of the highest multiplicity PVs (≥21 tracks). Using this classification, the comparison among different experiments is largely independent from specific features of the detectors. – 6 – JHEP12(2017)025 Although the activity classes have advantages in comparing results among various experiments characterised by different rapidity ranges, an unfolding procedure is performed to relate the reconstructed charged-particle multiplicities to those predicted by Pythia 8 with a specific LHCb configuration [54]. The multiplicity distributions are corrected using a Bayesian unfolding technique [63]. An unfolding matrix reflecting the probability of reconstructing a certain number of charged particles from a single PV in the range 2 < η < 5 with generated charged-particle multiplicity Nch is populated using simulation and applied to the data. It is found that the corrected multiplicities agree well with the unfolded multiplicities previously determined by LHCb in ref. [64]. The activity classes correspond to the following generated charged-particle multiplicitiy intervals: Nch ∈[8,18] (low activity), Nch ∈[19,35] (medium activity) and Nch ∈[36,96] (high activity). The distributions of the double ratio of correlation functions in data and simulation for like-sign pion pairs, determined using the event-mixed reference sample, are fitted in the range 0.05 <Q<2.0 GeV/c2for the three different activity classes using the parameterisation of eq. (2.3). The results of the binned maximum likelihood fit to the double ratio are summarised in section 6. 5 Systematic uncertainties The properties of the correlation function and the construction of the double ratio make the fitted BEC parameters insensitive to the choice of the selection requirements to a large extent. However, due to imperfections in the reference sample and possible differences between data and simulation related to the generation model, as well as subtle reconstruction effects (like the reconstruction of close tracks sharing the same VELO hits or the track reconstruction in the high-occupancy detector regions), some second-order distortions in the double ratio may appear. The systematic uncertainties on the fit parameters, Rand λ, of the exponential model are determined by performing the analysis with modifications designed to estimate the systematic effects on individual contributions to the rd(Q) distribution. The leading source of systematic uncertainty is due to differences in the event generators used to determine the correlation function for the simulation. To study this effect, a sample of minimum-bias events produced using the Pythia 6.4 generator with Perugia0 tuning is used to construct the double ratio. The corresponding contribution to the systematic uncertainty is taken as the difference between the central values of the results obtained using the Pythia 8 and Pythia 6.4 datasets. Another important source of systematic uncertainty is related to the PV multiplicity in the event. The constructed double ratio may be distorted in events containing multiple PVs, due to imperfections in the construction of the reference sample. To estimate the associated systematic uncertainty, the sample is divided into three subsamples containing events with one, two, and three or more PVs. For each subsample, the fit is performed and the maximum difference for each measured parameter is taken as a systematic uncertainty. The systematic uncertainty resulting from the PV reconstruction efficiency is also considered. To account for the effect of pile-up in the data and inefficiencies in the PV reconstruction, – 7 – JHEP12(2017)025 a systematic uncertainty is estimated as the difference between the nominal fit results and the results obtained from a fit to the data in which the PV reconstruction has been repeated after removing randomly a subset of the tracks from the event. After applying the track quality requirements, the fraction of remaining fake tracks is determined from simulation to be at the level of 1%. To determine the systematic uncertainty due to the presence of such fake tracks, the double ratio is refitted with looser track quality requirements. A similar uncertainty is obtained from a second method in which sets of randomly selected uncorrelated tracks are added. The observed change in BEC parameters is negligible with respect to the statistical uncertainty. The fraction of like-sign pion pairs containing a clone track after the selection is determined to be below 1%. The systematic uncertainty due to the presence of clone tracks is estimated by fitting the double ratio rd(Q), after applying a tight requirement on the Kullback-Leibler distance [65] such that the clone contribution is fully removed in simulation. The effect is found to be negligible for all activity classes. The systematic uncertainty due to the calibration of the particle identification in the simulation is estimated by comparing several variants of the calibration procedure with the acceptance evaluated in different binning schemes for the particle momentum, pseudorapidity and track multiplicity. The largest difference after refitting the double ratios is taken as a systematic uncertainty. As the requirement on the pion identification probability alters the contamination of pions due to misidentification, it can influence the values of the Rand λparameters. The contribution of this effect to the systematic uncertainty is estimated by refitting rd(Q) with the requirement on the pion identification probability changed to increase the fraction of misidentified pions by 50%. The systematic uncertainty derived from the fit range in the low-Q(high-Q) region is determined by changing the lower (upper) limit of the Qvalue by ±0.01 GeV/c2 (±0.2 GeV/c2). The fits to the double ratio with two different lower (upper) limits of Qare performed for the three activity classes and the largest difference is taken as a systematic uncertainty. The systematic uncertainty due to Coulomb corrections is estimated by varying the corrections by ±20%. The variation in the fit parameters is found to be less than 0.1%, and is therefore neglected. It is also found that imposing different requirements on the particle IPs has no significant influence on the measured correlation radius or chaoticity parameter. The fractions of kaon-kaon and proton-proton like-sign pairs misidentified as a pion pair in the pion sample in the BEC signal region of Q < 1.0 GeV/c2are found to be negligible. Pairings of different particle types have a negligible effect. Other effects like the fit binning, the resolution of the Qvariable, different magnet polarities, beam-gas interactions and residual acceptance effects related to possible differences between data and simulation in the low-Qregion below ∼0.2 GeV/c2, are also studied and found to be negligible. The contributions to the systematic uncertainty are listed in table 1. Correlations of the systematic uncertainties between different activity classes are negligible. – 8 – JHEP12(2017)025 [39] T. Csorgo, S. Hegyi and W.A. Zajc, Bose-Einstein correlations for Levy stable source distributions,Eur. Phys. J. C 36 (2004) 67 [nucl-th/0310042] [INSPIRE]. [40] M. 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Cenci24,t, D. Chamont7, M. Charles8, Ph. Charpentier40, G. Chatzikonstantinidis47, M. Chefdeville4, S. Chen56, S.F. Cheung57, S.-G. Chitic40, V. Chobanova39, M. Chrzaszcz42,27, A. Chubykin31, P. Ciambrone19, X. Cid Vidal39, G. Ciezarek43, P.E.L. Clarke52, M. Clemencic40, H.V. Cliff49, J. Closier40, J. Cogan6, E. Cogneras5, V. Cogoni16,f , L. Cojocariu30, P. Collins40, T. Colombo40, A. Comerma-Montells12, A. Contu40, A. Cook48, G. Coombs40, S. Coquereau38, G. Corti40, M. Corvo17,g, C.M. Costa Sobral50, B. Couturier40, G.A. Cowan52, D.C. Craik58, A. Crocombe50, M. Cruz Torres1, R. Currie52, C. D’Ambrosio40, F. Da Cunha Marinho2, E. Dall’Occo43, J. Dalseno48, A. Davis3, O. De Aguiar Francisco54, S. De Capua56, M. De Cian12, J.M. De Miranda1, L. De Paula2, M. De Serio14,d, P. De Simone19, C.T. Dean53, D. Decamp4, L. Del Buono8, H.-P. Dembinski11, M. Demmer10, A. Dendek28, D. Derkach35, O. Deschamps5, F. Dettori54, B. Dey65, A. Di Canto40, P. Di Nezza19, H. Dijkstra40, F. Dordei40, M. Dorigo40, A. Dosil Su´arez39, L. Douglas53, A. Dovbnya45, K. Dreimanis54, L. Dufour43, G. Dujany8, P. Durante40, R. Dzhelyadin37, M. Dziewiecki12, A. Dziurda40, A. Dzyuba31, S. Easo51, M. Ebert52, U. Egede55, V. Egorychev32, S. Eidelman36,w, S. Eisenhardt52, U. Eitschberger10, R. Ekelhof10, L. Eklund53, S. Ely61, S. Esen12, H.M. Evans49, T. Evans57, A. Falabella15, N. Farley47, S. Farry54, D. Fazzini21,i, L. Federici25, D. Ferguson52, G. Fernandez38, P. Fernandez Declara40, A. Fernandez Prieto39, F. Ferrari15, F. Ferreira Rodrigues2, M. Ferro-Luzzi40, S. Filippov34, R.A. Fini14, M. Fiore17,g, M. Fiorini17,g, M. Firlej28, C. Fitzpatrick41, T. Fiutowski28, F. Fleuret7,b, K. Fohl40, M. Fontana16,40, F. Fontanelli20,h, D.C. Forshaw61, R. Forty40, V. Franco Lima54, M. Frank40, C. Frei40, J. Fu22,q, W. Funk40, E. Furfaro25,j , C. F¨arber40, E. Gabriel52, A. Gallas Torreira39, D. Galli15,e, S. Gallorini23, S. Gambetta52, M. Gandelman2, P. Gandini57, Y. Gao3, L.M. Garcia Martin70, J. Garc´ıa Pardi˜nas39, J. Garra Tico49, L. Garrido38, P.J. Garsed49, D. Gascon38, C. Gaspar40, L. Gavardi10, G. Gazzoni5, D. Gerick12, E. Gersabeck12, M. Gersabeck56, T. Gershon50, – 17 – JHEP12(2017)025 Ph. Ghez4, S. Gian`ı41, V. Gibson49, O.G. Girard41, L. Giubega30, K. Gizdov52, V.V. Gligorov8, D. Golubkov32, A. Golutvin55,40, A. Gomes1,a, I.V. Gorelov33, C. Gotti21,i, E. Govorkova43, J.P. Grabowski12, R. Graciani Diaz38, L.A. Granado Cardoso40, E. Graug´es38, E. Graverini42, G. Graziani18, A. Grecu30, R. Greim9, P. Griffith16, L. Grillo21,40,i, L. Gruber40, B.R. Gruberg Cazon57, O. Gr¨unberg67, E. Gushchin34, Yu. Guz37, T. Gys40, C. G¨obel62, T. Hadavizadeh57, C. Hadjivasiliou5, G. Haefeli41, C. Haen40, S.C. Haines49, B. Hamilton60, X. Han12, T.H. Hancock57, S. Hansmann-Menzemer12, N. Harnew57, S.T. Harnew48, J. Harrison56, C. Hasse40, M. Hatch40, J. He63, M. Hecker55, K. Heinicke10, A. Heister9, K. Hennessy54, P. Henrard5, L. Henry70, E. van Herwijnen40, M. Heß67, A. Hicheur2, D. Hill57, C. Hombach56, P.H. Hopchev41, Z.C. Huard59, W. Hulsbergen43, T. Humair55, M. Hushchyn35, D. Hutchcroft54, P. Ibis10, M. Idzik28, P. Ilten58, R. Jacobsson40, J. Jalocha57, E. Jans43, A. Jawahery60, M. Jezabek27, F. Jiang3, M. John57, D. Johnson40, C.R. Jones49, C. Joram40, B. Jost40, N. Jurik57, S. Kandybei45, M. Karacson40, J.M. Kariuki48, S. Karodia53, N. Kazeev35, M. Kecke12, M. Kelsey61, M. Kenzie49, T. Ketel44, E. Khairullin35, B. Khanji12, C. Khurewathanakul41, T. Kirn9, S. Klaver56, K. Klimaszewski29, T. Klimkovich11, S. Koliiev46, M. Kolpin12, I. Komarov41, R. Kopecna12, P. Koppenburg43, A. Kosmyntseva32, S. Kotriakhova31, M. Kozeiha5, L. Kravchuk34, M. Kreps50, P. Krokovny36,w, F. Kruse10, W. Krzemien29, W. Kucewicz27,l, M. Kucharczyk27, V. Kudryavtsev36,w, A.K. Kuonen41, K. Kurek29, T. Kvaratskheliya32,40, D. Lacarrere40, G. Lafferty56, A. Lai16, G. Lanfranchi19, C. Langenbruch9, T. Latham50, C. Lazzeroni47, R. Le Gac6, A. Leflat33,40, J. Lefran¸cois7, R. Lef`evre5, F. Lemaitre40, E. Lemos Cid39, O. Leroy6, T. Lesiak27, B. Leverington12, P.-R. Li63, T. Li3, Y. Li7, Z. Li61, T. Likhomanenko68, R. Lindner40, F. Lionetto42, V. Lisovskyi7, X. Liu3, D. Loh50, A. Loi16, I. Longstaff53, J.H. Lopes2, D. Lucchesi23,o, M. Lucio Martinez39, H. Luo52, A. Lupato23, E. Luppi17,g, O. Lupton40, A. Lusiani24, X. Lyu63, F. Machefert7, F. Maciuc30, V. Macko41, P. Mackowiak10, S. Maddrell-Mander48, O. Maev31,40, K. Maguire56, D. Maisuzenko31, M.W. Majewski28, S. Malde57, B. Malecki27, A. Malinin68, T. Maltsev36,w, G. Manca16,f , G. Mancinelli6, P. Manning61, D. Marangotto22,q, J. Maratas5,v, J.F. Marchand4, U. Marconi15, C. Marin Benito38, M. Marinangeli41, P. Marino41, J. Marks12, G. Martellotti26, M. Martin6, M. Martinelli41, D. Martinez Santos39, F. Martinez Vidal70, D. Martins Tostes2, L.M. Massacrier7, A. Massafferri1, R. Matev40, A. Mathad50, Z. Mathe40, C. Matteuzzi21, A. Mauri42, E. Maurice7,b, B. Maurin41, A. Mazurov47, M. McCann55,40, A. McNab56, R. McNulty13, J.V. Mead54, B. Meadows59, C. Meaux6, F. Meier10, N. Meinert67, D. Melnychuk29, M. Merk43, A. Merli22,40,q, E. Michielin23, D.A. Milanes66, E. Millard50, M.-N. Minard4, L. Minzoni17, D.S. Mitzel12, A. Mogini8, J. Molina Rodriguez1, T. Momb¨acher10, I.A. Monroy66, S. Monteil5, M. Morandin23, M.J. Morello24,t, O. Morgunova68, J. Moron28, A.B. Morris52, R. Mountain61, F. Muheim52, M. Mulder43, D. M¨uller56, J. M¨uller10, K. M¨uller42, V. M¨uller10, P. Naik48, T. Nakada41, R. Nandakumar51, A. Nandi57, I. Nasteva2, M. Needham52, N. Neri22,40, S. Neubert12, N. Neufeld40, M. Neuner12, T.D. Nguyen41, C. Nguyen-Mau41,n, S. Nieswand9, R. Niet10, N. Nikitin33, T. Nikodem12, A. Nogay68, D.P. O’Hanlon50, A. Oblakowska-Mucha28, V. Obraztsov37, S. Ogilvy19, R. Oldeman16,f , C.J.G. Onderwater71, A. Ossowska27, J.M. Otalora Goicochea2, P. Owen42, A. Oyanguren70, P.R. Pais41, A. Palano14,d, M. Palutan19,40, A. Papanestis51, M. Pappagallo14,d, L.L. Pappalardo17,g, W. Parker60, C. Parkes56, G. Passaleva18, A. Pastore14,d, M. Patel55, C. Patrignani15,e, A. Pearce40, A. Pellegrino43, G. Penso26, M. Pepe Altarelli40, S. Perazzini40, P. Perret5, L. Pescatore41, K. Petridis48, A. Petrolini20,h, A. Petrov68, M. Petruzzo22,q, E. Picatoste Olloqui38, B. Pietrzyk4, M. Pikies27, D. Pinci26, F. Pisani40, A. Pistone20,h, A. Piucci12, V. Placinta30, S. Playfer52, M. Plo Casasus39, F. Polci8, M. Poli Lener19, A. Poluektov50,36, I. Polyakov61, E. Polycarpo2, G.J. Pomery48, S. Ponce40, A. Popov37, D. Popov11,40, S. Poslavskii37, C. Potterat2, E. Price48, – 18 – JHEP12(2017)025 J. Prisciandaro39, C. Prouve48, V. Pugatch46, A. Puig Navarro42, H. Pullen57, G. Punzi24,p, W. Qian50, R. Quagliani7,48, B. Quintana5, B. Rachwal28, J.H. Rademacker48, M. Rama24, M. Ramos Pernas39, M.S. Rangel2, I. Raniuk45,†, F. Ratnikov35, G. Raven44, M. Ravonel Salzgeber40, M. Reboud4, F. Redi55, S. Reichert10, A.C. dos Reis1, C. Remon Alepuz70, V. Renaudin7, S. Ricciardi51, S. Richards48, M. Rihl40, K. Rinnert54, V. Rives Molina38, P. Robbe7, A. Robert8, A.B. Rodrigues1, E. Rodrigues59, J.A. Rodriguez Lopez66, P. Rodriguez Perez56,†, A. Rogozhnikov35, S. Roiser40, A. Rollings57, V. Romanovskiy37, A. Romero Vidal39, J.W. Ronayne13, M. Rotondo19, M.S. Rudolph61, T. Ruf40, P. Ruiz Valls70, J. Ruiz Vidal70, J.J. Saborido Silva39, E. Sadykhov32, N. Sagidova31, B. Saitta16,f , V. Salustino Guimaraes1, C. Sanchez Mayordomo70, B. Sanmartin Sedes39, R. Santacesaria26, C. Santamarina Rios39, M. Santimaria19, E. Santovetti25,j , G. Sarpis56, A. Sarti26, C. Satriano26,s, A. Satta25, D.M. Saunders48, D. Savrina32,33, S. Schael9, M. Schellenberg10, M. Schiller53, H. Schindler40, M. Schlupp10, M. Schmelling11, T. Schmelzer10, B. Schmidt40, O. Schneider41, A. Schopper40, H.F. Schreiner59, K. Schubert10, M. Schubiger41, M.-H. Schune7, R. Schwemmer40, B. Sciascia19, A. Sciubba26,k, A. Semennikov32, E.S. Sepulveda8, A. Sergi47, N. Serra42, J. Serrano6, L. Sestini23, P. Seyfert40, M. Shapkin37, I. Shapoval45, Y. Shcheglov31, T. Shears54, L. Shekhtman36,w, V. Shevchenko68, B.G. Siddi17,40, R. Silva Coutinho42, L. Silva de Oliveira2, G. Simi23,o, S. Simone14,d, M. Sirendi49, N. Skidmore48, T. Skwarnicki61, E. Smith55, I.T. Smith52, J. Smith49, M. Smith55, l. Soares Lavra1, M.D. Sokoloff59, F.J.P. Soler53, B. Souza De Paula2, B. Spaan10, P. Spradlin53, S. Sridharan40, F. Stagni40, M. Stahl12, S. Stahl40, P. Stefko41, S. Stefkova55, O. Steinkamp42, S. Stemmle12, O. Stenyakin37, M. Stepanova31, H. Stevens10, S. Stone61, B. Storaci42, S. Stracka24,p, M.E. Stramaglia41, M. Straticiuc30, U. Straumann42, J. Sun3, L. Sun64, W. Sutcliffe55, K. Swientek28, V. Syropoulos44, M. Szczekowski29, T. Szumlak28, M. Szymanski63, S. T’Jampens4, A. Tayduganov6, T. Tekampe10, G. Tellarini17,g, F. Teubert40, E. Thomas40, J. van Tilburg43, M.J. Tilley55, V. Tisserand4, M. Tobin41, S. Tolk49, L. Tomassetti17,g, D. Tonelli24, F. Toriello61, R. Tourinho Jadallah Aoude1, E. Tournefier4, M. Traill53, M.T. Tran41, M. Tresch42, A. Trisovic40, A. Tsaregorodtsev6, P. Tsopelas43, A. Tully49, N. Tuning43,40, A. Ukleja29, A. Usachov7, A. Ustyuzhanin35, U. Uwer12, C. Vacca16,f , A. Vagner69, V. Vagnoni15,40, A. Valassi40, S. Valat40, G. Valenti15, R. Vazquez Gomez19, P. Vazquez Regueiro39, S. Vecchi17, M. van Veghel43, J.J. Velthuis48, M. Veltri18,r, G. Veneziano57, A. Venkateswaran61, T.A. Verlage9, M. Vernet5, M. Vesterinen57, J.V. Viana Barbosa40, B. Viaud7, D. Vieira63, M. Vieites Diaz39, H. Viemann67, X. Vilasis-Cardona38,m, M. Vitti49, V. Volkov33, A. Vollhardt42, B. Voneki40, A. Vorobyev31, V. Vorobyev36,w, C. Voß9, J.A. de Vries43, C. V´azquez Sierra39, R. Waldi67, C. Wallace50, R. Wallace13, J. Walsh24, J. Wang61, D.R. Ward49, H.M. Wark54, N.K. Watson47, D. Websdale55, A. Weiden42, M. Whitehead40, J. Wicht50, G. Wilkinson57,40, M. Wilkinson61, M. Williams56, M.P. Williams47, M. Williams58, T. Williams47, F.F. Wilson51, J. Wimberley60, M. Winn7, J. Wishahi10, W. Wislicki29, M. Witek27, G. Wormser7, S.A. Wotton49, K. Wraight53, K. Wyllie40, Y. Xie65, Z. Xu4, Z. Yang3, Z. Yang60, Y. Yao61, H. Yin65, J. Yu65, X. Yuan61, O. Yushchenko37, K.A. Zarebski47, M. Zavertyaev11,c, L. Zhang3, Y. Zhang7, A. Zhelezov12, Y. Zheng63, X. Zhu3, V. Zhukov33, J.B. Zonneveld52, S. Zucchelli15. 1Centro Brasileiro de Pesquisas F´ısicas (CBPF), Rio de Janeiro, Brazil 2Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil 3Center for High Energy Physics, Tsinghua University, Beijing, China 4LAPP, Universit´e Savoie Mont-Blanc, CNRS/IN2P3, Annecy-Le-Vieux, France 5Clermont Universit´e, Universit´e Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand, France 6Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France 7LAL, Universit´e Paris-Sud, CNRS/IN2P3, Orsay, France – 19 – JHEP12(2017)025 8LPNHE, Universit´e Pierre et Marie Curie, Universit´e Paris Diderot, CNRS/IN2P3, Paris, France 9I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany 10 Fakult¨at Physik, Technische Universit¨at Dortmund, Dortmund, Germany 11 Max-Planck-Institut f¨ur Kernphysik (MPIK), Heidelberg, Germany 12 Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany 13 School of Physics, University College Dublin, Dublin, Ireland 14 Sezione INFN di Bari, Bari, Italy 15 Sezione INFN di Bologna, Bologna, Italy 16 Sezione INFN di Cagliari, Cagliari, Italy 17 Universita e INFN, Ferrara, Ferrara, Italy 18 Sezione INFN di Firenze, Firenze, Italy 19 Laboratori Nazionali dell’INFN di Frascati, Frascati, Italy 20 Sezione INFN di Genova, Genova, Italy 21 Universita & INFN, Milano-Bicocca, Milano, Italy 22 Sezione di Milano, Milano, Italy 23 Sezione INFN di Padova, Padova, Italy 24 Sezione INFN di Pisa, Pisa, Italy 25 Sezione INFN di Roma Tor Vergata, Roma, Italy 26 Sezione INFN di Roma La Sapienza, Roma, Italy 27 Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Krak´ow, Poland 28 AGH - University of Science and Technology, Faculty of Physics and Applied Computer Science, Krak´ow, Poland 29 National Center for Nuclear Research (NCBJ), Warsaw, Poland 30 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania 31 Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia 32 Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia 33 Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia 34 Institute for Nuclear Research of the Russian Academy of Sciences (INR RAN), Moscow, Russia 35 Yandex School of Data Analysis, Moscow, Russia 36 Budker Institute of Nuclear Physics (SB RAS), Novosibirsk, Russia 37 Institute for High Energy Physics (IHEP), Protvino, Russia 38 ICCUB, Universitat de Barcelona, Barcelona, Spain 39 Universidad de Santiago de Compostela, Santiago de Compostela, Spain 40 European Organization for Nuclear Research (CERN), Geneva, Switzerland 41 Institute of Physics, Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland 42 Physik-Institut, Universit¨at Z¨urich, Z¨urich, Switzerland 43 Nikhef National Institute for Subatomic Physics, Amsterdam, The Netherlands 44 Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam, The Netherlands 45 NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine 46 Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine 47 University of Birmingham, Birmingham, U.K. 48 H.H. Wills Physics Laboratory, University of Bristol, Bristol, U.K. 49 Cavendish Laboratory, University of Cambridge, Cambridge, U.K. 50 Department of Physics, University of Warwick, Coventry, U.K. 51 STFC Rutherford Appleton Laboratory, Didcot, U.K. 52 School of Physics and Astronomy, University of Edinburgh, Edinburgh, U.K. 53 School of Physics and Astronomy, University of Glasgow, Glasgow, U.K. 54 Oliver Lodge Laboratory, University of Liverpool, Liverpool, U.K. 55 Imperial College London, London, U.K. 56 School of Physics and Astronomy, University of Manchester, Manchester, U.K. – 20 – JHEP12(2017)025 57 Department of Physics, University of Oxford, Oxford, U.K. 58 Massachusetts Institute of Technology, Cambridge, MA, U.S.A. 59 University of Cincinnati, Cincinnati, OH, U.S.A. 60 University of Maryland, College Park, MD, U.S.A. 61 Syracuse University, Syracuse, NY, U.S.A. 62 Pontif´ıcia Universidade Cat´olica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to 2 63 University of Chinese Academy of Sciences, Beijing, China, associated to 3 64 School of Physics and Technology, Wuhan University, Wuhan, China, associated to 3 65 Institute of Particle Physics, Central China Normal University, Wuhan, Hubei, China, associated to 3 66 Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia, associated to 8 67 Institut f¨ur Physik, Universit¨at Rostock, Rostock, Germany, associated to 12 68 National Research Centre Kurchatov Institute, Moscow, Russia, associated to 32 69 National Research Tomsk Polytechnic University, Tomsk, Russia, associated to 32 70 Instituto de Fisica Corpuscular, Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain, associated to 38 71 Van Swinderen Institute, University of Groningen, Groningen, The Netherlands, associated to 43 aUniversidade Federal do Triˆangulo Mineiro (UFTM), Uberaba-MG, Brazil bLaboratoire Leprince-Ringuet, Palaiseau, France cP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, Russia dUniversit`a di Bari, Bari, Italy eUniversit`a di Bologna, Bologna, Italy fUniversit`a di Cagliari, Cagliari, Italy gUniversit`a di Ferrara, Ferrara, Italy hUniversit`a di Genova, Genova, Italy iUniversit`a di Milano Bicocca, Milano, Italy jUniversit`a di Roma Tor Vergata, Roma, Italy kUniversit`a di Roma La Sapienza, Roma, Italy lAGH - University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krak´ow, Poland mLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain nHanoi University of Science, Hanoi, Viet Nam oUniversit`a di Padova, Padova, Italy pUniversit`a di Pisa, Pisa, Italy qUniversit`a degli Studi di Milano, Milano, Italy rUniversit`a di Urbino, Urbino, Italy sUniversit`a della Basilicata, Potenza, Italy tScuola Normale Superiore, Pisa, Italy uUniversit`a di Modena e Reggio Emilia, Modena, Italy vIligan Institute of Technology (IIT), Iligan, Philippines wNovosibirsk State University, Novosibirsk, Russia †Deceased – 21 –