First measurement of the differential branching fraction and CP asymmetry of the B ± → π ± μ + μ − decay

JHEP10(2015)034 Published for SISSA by Springer Received:September 2, 2015 Accepted:September 5, 2015 Published:October 6, 2015 First measurement of the differential branching fraction and CP asymmetry of the B±→π±µ+µ− decay The LHCb collaboration E-mail: [email protected] Abstract: The differential branching fraction with respect to the dimuon invariant mass squared, and the CP asymmetry of the B±→π±µ+µ−decay are measured for the first time. The CKM matrix elements |Vtd|and |Vts|, and the ratio |Vtd/Vts|are determined. The analysis is performed using proton-proton collision data corresponding to an integrated luminosity of 3.0 fb−1, collected by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. The total branching fraction and CP asymmetry of B±→π±µ+µ−decays are measured to be B(B±→π±µ+µ−) = (1.83 ±0.24 ±0.05) ×10−8and ACP (B±→π±µ+µ−) = −0.11 ±0.12 ±0.01 , where the first uncertainties are statistical and the second are systematic. These are the most precise measurements of these observables to date, and they are compatible with the predictions of the Standard Model. Keywords: Rare decay, CP violation, Hadron-Hadron Scattering, Branching fraction, B physics ArXiv ePrint: 1509.00414 Open Access, Copyright CERN, for the benefit of the LHCb Collaboration. Article funded by SCOAP3. doi:10.1007/JHEP10(2015)034 JHEP10(2015)034 Contents 1 Introduction 1 2 Detector and simulation 2 3 Event selection 3 4 Event yields 5 5 Results 8 5.1 Differential branching fraction 8 5.2 CKM matrix elements 9 5.3 CP asymmetry 11 6 Summary 12 The LHCb collaboration 16 1 Introduction The decay B+→π+µ+µ−is a b→dflavour-changing neutral-current process, which is suppressed in the Standard Model (SM).1The suppression arises since the b→d`+`− transition proceeds only through amplitudes involving the electroweak loop (penguin and box) diagrams shown in figure 1. In the SM, the top quark contribution dominates the loops, and an additional suppression occurs through the factor Vtd from the CabbiboKobayashi-Maskawa (CKM) matrix. The decay is therefore sensitive to the presence of new particles that are predicted to exist in extensions of the SM, particularly in models where the flavour structure differs from that of the SM [1–7]. The ratio of CKM matrix elements |Vtd/Vts|has been measured [8,9] via B0and B0 smixing processes [10,11] and b→s(d)γ decays [12]; it can also be determined from a measurement of the ratio of the branching fractions of the B+→π+µ+µ−decay to the more precisely measured B+→K+µ+µ− decay [13]. Such ratios are also sensitive to the flavour structure of physics beyond the SM. The CP asymmetry of B±→π±µ+µ−is defined as the relative difference between the decay widths, Γ, of the two charge conjugate modes, ACP ≡Γ(B−→π−µ+µ−)−Γ(B+→π+µ+µ−) Γ(B−→π−µ+µ−) + Γ(B+→π+µ+µ−).(1.1) The CP asymmetry is predicted to be non-zero due to interference between amplitudes that are proportional to the CKM matrix elements involved in the B+→π+µ+µ−decay, 1Unless explicitly stated, the inclusion of charge-conjugate processes is implied. – 1 – JHEP10(2015)034 u/c/t W u/c/t Z0/γ b µ+ µ− du/c/t νµ WW b µ+ µ− d Figure 1. Feynman diagrams of the penguin and box loop contributions to the b→d`+`−process. namely VubV∗ ud and VtbV∗ td. Recent predictions for the CP asymmetry are given in ref. [6]. The B+→π+µ+µ−decay was first observed by the LHCb collaboration [14] and the total branching fraction was measured to be B(B+→π+µ+µ−) = (2.3±0.6 (stat) ±0.1 (syst)) ×10−8. This paper describes measurements of the differential branching fraction and CP asymmetry of the B±→π±µ+µ−decay. The differential branching fraction is measured in bins of dilepton invariant mass squared, q2, and normalised to B+→ J/ψ(µ+µ−)K+decays. These measurements are performed through fits to the invariant mass distributions. The branching fraction and the ratio of the branching fractions B(B+→π+µ+µ−)/B(B+→K+µ+µ−) are used to determine the CKM matrix elements |Vtd|and |Vts|, and the ratio |Vtd/Vts|, respectively. The measurements are based on 3.0 fb−1 of pp collision data recorded using the LHCb detector at centre-of-mass energies of 7 TeV and 8 TeV. 2 Detector and simulation The LHCb detector [15,16] is a single-arm forward spectrometer covering the pseudorapidity range 2 < η < 5, designed for the study of particles containing bor cquarks. The detector includes a high-precision tracking system consisting of a silicon-strip vertex detector surrounding the pp interaction region, 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 placed downstream of the magnet. The tracking system provides a measurement of the momentum, p, of charged particles with a relative uncertainty that varies from 0.5% at low momentum to 1.0% at 200 GeV/c. The minimum distance of a track to a primary vertex, the impact parameter, is measured with a resolution of (15 + 29/pT)µm, where pTis the component of the momentum transverse to the beam, in GeV/c. The magnetic field polarity is inverted with a period of several weeks during data taking, which allows the charge asymmetries due to the detector geometry to be determined. The different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov detectors. Photons, electrons and hadrons are identified by a – 2 – JHEP10(2015)034 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. The online event selection is performed by a trigger, which consists of a hardware stage, based on information from the calorimeter and muon systems, followed by a software stage, which reconstructs the full event. Samples of simulated B+→π+µ+µ−,B+→K+µ+µ−and B+→J/ψ(µ+µ−)K+ decays are produced from pp collisions generated using Pythia [17,18] with a specific LHCb configuration [19]. Decays of hadronic particles are described by EvtGen [20], in which final-state radiation is generated using Photos [21]. The interaction of the generated particles with the detector, and its response, are implemented using the Geant4 toolkit [22,23] as described in ref. [24]. The simulated events are reweighted to account for known differences relative to the data in the transverse momentum spectrum of the B+ meson and the detector occupancy of the event. 3 Event selection Events are required to satisfy a hardware trigger, which selects muons with pT>1.48 GeV/c in the 7 TeV data and pT>1.76 GeV/c in the 8 TeV data. In the subsequent software trigger, at least one of the final-state particles is required to have both pT>0.8 GeV/c and impact parameter greater than 100 µm with respect to all primary pp interaction vertices (PVs) in the event. Finally, the tracks of at least two of the final-state particles are required to form a vertex that is significantly displaced from the PVs, and a multivariate algorithm is used to identify secondary vertices that are consistent with the decay of a bhadron [16]. Candidates are formed from pairs of well-reconstructed oppositely-charged tracks identified as muons, combined with an additional track that is identified as either a charged pion or a charged kaon for B+→π+µ+µ−or B+→K+µ+µ−decays, respectively. Each track is required to have a good fit quality, a low probability of overlapping with any other track, pT>300 MeV/c and to be inconsistent with originating from any PV. Candidates are required to have a good quality vertex fit and to be consistent with originating from a PV with the candidate’s momentum vector aligned with the direction between the primary and secondary vertices. Separation of the signal decay from combinatorial background is achieved using a multivariate classifier. A boosted decision tree (BDT) [25,26] is trained using supervised learning with ten-fold cross validation [27] to achieve an unbiased classifier response. The background sample used to train the BDT consists of data from the upper sideband of the π+µ+µ−invariant mass distribution in the region greater than 5500 MeV/c2; the B+→π+µ+µ−signal sample is obtained from the simulation. As no particle identification information is used in the classifier, it can be applied to both the pion and kaon modes. The features of the data that are used to classify the π+µ+µ−candidate as signalor background-like are the properties of the pion and muon tracks, and properties of the π+µ+µ−candidate. For the pion and muon tracks, the features used are the transverse momentum of the tracks, the impact parameter of the track, and the track quality. For – 3 – JHEP10(2015)034 the π+µ+µ−candidate, the features used are the angle between its momentum vector and the direction vector between the primary vertex and the secondary vertex, and its flight distance, transverse momentum, and vertex quality. Two isolation variables [28] and the absolute difference in momentum between each of the muons are also used in the classifier. The output of the multivariate classifier and the particle identification requirements are simultaneously optimised to maximise signal significance. Pseudo-datasets were constructed from simulated signal events and combinatorial background events taken from the upper mass sideband of data. Trial BDT and particle identification cuts were applied and an expected misidentified-kaon component added to the pseudo-datasets. Wilks’ theorem [29] was used to determine a signal significance from fits to the pseudo-dataset, the value of which was passed to a maximisation algorithm that could vary the trial cut values. The classifier and particle identification cut values used to separate signal and background decays are chosen at the point of highest significance. Operating at this point, the classifier has a combinatorial background rejection of 99.8%, whilst retaining 66.9% of signal events, and each event contains only a single candidate. As the classifier separates B+decays from combinatorial background, relatively pure samples of B+→K+µ+µ−and B+→J/ψ(µ+µ−)K+events are also obtained using the same classifier requirements, when requiring a positively identified kaon. The charmonium resonances are removed from the samples of B+→π+µ+µ− and B+→K+µ+µ−candidates by vetoing the regions 8.0< q2<11.0 GeV2 /c4and 12.5< q2<15.0 GeV2 /c4. There are several other b-hadron decays that could mimic the B+→π+µ+µ−signal. Decays such as B+→π+π−π+and B+→J/ψ(µ+µ−)K+, where there is double hadron-muon misidentification, are excluded from the B+→π+µ+µ− dataset by muon identification criteria and the expected number of background events is found to be negligible. Partially reconstructed decays such as B0→K∗0(K+π−)µ+µ−, B0→K0 S(π+π−)µ+µ−and B0→ρ(π+π−)µ+µ−, where a kaon or a pion is missed, may satisfy the selection; however, simulation indicates that such events have a reconstructed mass that lies more than 100 MeV/c2below the measured B+mass. Therefore, such background events do not affect the signal yield extraction. There are two types of semileptonic decays that feature as backgrounds, B+→D0(K+µ−νµ)π+decays with kaon-muon misidentification, and the double semileptonic decay B+→D0(h+µ−νµ)µ+νµ, where h+can be a pion or kaon. The former decay is suppressed by requiring the µ+to have a low probability of being a kaon. The latter decay has the same final state as the signal and cannot be completely removed by the selection. However, the distribution of double semileptonic decays as a function of the π+µ+µ−invariant mass varies smoothly, and can be modelled well in the fit from which the signal yield is extracted. The pion-kaon separation is not completely efficient: 6% of B+→K+µ+µ−events are selected as B+→π+µ+µ−events, and are modelled as a specific background. The normalisation sample of B+→J/ψ (µ+µ−)K+candidates is selected using the dilepton invariant-mass region around the J/ψ mass, i.e. 3096±50 MeV/c2. To remove much of the contribution from partially reconstructed decays, whilst keeping enough information to determine any effect on the signal, the π+µ+µ−invariant-mass range 5040 < m(π+µ+µ−)<6000 MeV/c2is used to extract the signal yield. – 4 – JHEP10(2015)034 4 Event yields The yields of B+→π+µ+µ−,B+→K+µ+µ−and B+→J/ψ (µ+µ−)K+candidates are extracted by performing simultaneous, extended, unbinned maximum-likelihood fits to the invariant mass distributions m(π+µ+µ−) and m(K+µ+µ−) of the selected candidates. The total model for the invariant mass distribution is composed of a signal model, a combinatorial background model, a model to describe partially reconstructed b-meson decays and a model to describe b-hadron decays with misidentified final-state particles. The signal model is an empirical function that consists of two Gaussian functions with power-law tails on both sides [30], and the same parameters are used for the B+→π+µ+µ−,B+→K+µ+µ−, and B+→J/ψ (µ+µ−)K+decay modes. The model for the combinatorial background is described by a separate exponential function for each decay. In the B+→π+µ+µ−data sample, the misidentified B+→K+µ+µ−decays where a kaon has been misidentified as a pion, are described by a single Gaussian function with a power-law tail on the lower-mass side. The yield of misidentified B+→K+µ+µ−decays is constrained using the measured branching fraction [13] and the observed pion-kaon misidentification efficiency. The mass distribution of the misidentified B+→K+µ+µ−candidates is obtained by fitting the invariant mass distribution of B+→J/ψ(µ+µ−)K+candidates, where the kaon is required to have the pion mass, and which has been corrected to account for differences in the particle identification efficiencies that arise from the differing kinematics. The partially reconstructed B+decays in the B+→K+µ+µ−and the B+→J/ψ (µ+µ−)K+data are described by an empirical function, which consists of a rising exponential function that makes a smooth transition to a Gaussian function. This description allows the mixture of partially reconstructed b-hadron decays to be limited to less than the maximum physical value of the B+mass minus the pion mass, with a Gaussian resolution-smearing effect. The partially reconstructed b-hadron decays in the B+→π+µ+µ−sample are separated into three explicit components. Firstly, the double semileptonic decay B+→D0(π+µ−νµ)µ+νµis included, as this is an irreducible background that ends at the B+mass. This is modelled by a falling exponential function that makes a smooth transition to a Gaussian function at high mass, where the parameters are fixed from a fit to simulated events. The yield of this component is left to vary in the fit. Secondly, the decays B+→ρ+(π+π0)µ+µ−and B0→ρ0(π+π−)µ+µ−are estimated to contribute a total of 34 ±7 events to the data, from the measured branching fraction of B0→ρ0(π+π−)µ+µ−[31] and assuming isospin invariance. Lastly, the decay B0 s→f0(π+π−)µ+µ−is estimated to contribute 10 ±2 events to the data, also below the B+mass. Each of these decays is modelled by a separate kernel-estimation probability density function (PDF) with a shape taken from simulated events reconstructed under the π+µ+µ−hypothesis. The yield of each of these decays has a Gaussian constraint applied with a central value and width set to the expected yield and its uncertainty. The invariant mass distributions of selected π+µ+µ−and K+µ+µ−candidates are shown in figure 2, along with the total fitted model, signal component, and each background component. The fit gives yields of 94 ±12 B+→π+µ+µ−, 2922 ±55 B+→K+µ+µ−, and (609.5±0.8) ×103B+→J/ψ (µ+µ−)K+candidates, where the uncertainties are statisti- – 5 – JHEP10(2015)034 ) 2 ) (MeV/c - µ + µ + π(m 5200 5400 5600 5800 6000 ) 2 cCandidates / ( 30 MeV/ 0 10 20 30 40 50 60 70 LHCb - µ + µ + π→ + B - µ + µ + K→ + B ν + µ 0 D→ + B - µ + µ 0,+ ρ→ 0,+ B - µ + µ 0 f→ s 0 B Combinatorial ) 2 ) (MeV/c - µ + µ + K(m 5200 5400 5600 5800 6000 ) 2 cCandidates / ( 10 MeV/ 0 100 200 300 400 500 600 LHCb - µ + µ + K→ + B X - µ + µ + K→ + B Combinatorial Figure 2. The fit to the invariant mass distribution of (left) selected B+→π+µ+µ−candidates and (right) selected B+→K+µ+µ−candidates, with the total model and separate components as described in the legend. q2bin ( GeV2 /c4)B+→π+µ+µ− 0.1 – 2.0 22.5+ −5.5 4.8 2.0 – 4.0 7.5+ −4.9 4.0 4.0 – 6.0 11.1+ −4.2 3.5 6.0 – 8.0 9.5±3.9 11.0 – 12.5 10.5±3.7 15.0 – 17.0 9.7±3.3 17.0 – 19.0 6.2±2.9 19.0 – 22.0 7.8±3.4 22.0 – 25.0 2.3+ −2.1 1.5 0.0 – 25.0 93.6±11.5 1.0 – 6.0 28.8+ −6.7 6.2 15.0 – 22.0 24.1+ −6.0 5.2 Table 1. The yields of B+→π+µ+µ−decays in bins of dilepton invariant mass squared, with statistical uncertainties. cal. The yield of B+→π+µ+µ−in each q2bin is given in table 1. The ratio of CKM matrix elements is determined in the theoretically favourable [1] bins 1.0< q2<6.0 GeV2 /c4(lowq2) and 15.0< q2<22.0 GeV2 /c4(high-q2). The B+→K+µ+µ−yields are 879 ±30 in the low-q2bin and 793 ±28 in the high-q2bin. The results of a simultaneous fit to the invariant mass distribution of B+→π+µ+µ−and B−→π−µ+µ−candidates are shown in figure 3and the measured yields are given in table 2. The small difference in total signal – 6 – JHEP10(2015)034 N(B±→π±µ+µ−)N(B+→π+µ+µ−)N(B−→π−µ+µ−) 92.7 ±11.5 51.7±8.3 41.1±7.9 Table 2. The measured total yield from the simultaneous fit to the charge separated data, and the inferred yields of B+→π+µ+µ−and B−→π−µ+µ−decays. ) 2 c) (MeV/ - µ + µ + π(m 5200 5400 5600 5800 6000 ) 2 cCandidates / ( 30 MeV/ 0 5 10 15 20 25 30 35 40 LHCb - µ + µ + π→ + B - µ + µ + K→ + B ν + µ 0 D→ + B - µ + µ 0,+ ρ→ 0,+ B - µ + µ 0 f→ s 0 B Combinatorial ) 2 c) (MeV/ - µ + µ - π(m 5200 5400 5600 5800 6000 ) 2 cCandidates / ( 30 MeV/ 0 5 10 15 20 25 30 35 40 LHCb - µ + µ - π→ - B - µ + µ - K→ - B ν + µ 0 D→ - B - µ + µ 0,- ρ→ 0,- B - µ + µ 0 f→ s 0 B Combinatorial Figure 3. The fit to the invariant mass distribution of (left) selected B+→π+µ+µ−candidates and (right) selected B−→π−µ+µ−candidates, with the total model and separate components as described in the legend. yield between this fit and that given in table 1is due to the systematic effect of separating the background distributions by charge. Consistent results are obtained from datasets split between the two magnet polarities. The choice of models used for the partially reconstructed backgrounds, the semileptonic backgrounds, the misidentified K+µ+µ−background, and the combinatorial background could all contribute as potential sources of systematic uncertainty. The dependence of the fitted yields on these models is assessed by replacing the relevant component with an alternative model, as follows, and evaluating the change in yield in simulation studies and in the fits to data. The largest change in yield is assigned as the systematic uncertainty. Changing the models for the B+→ρ+(π+π0)µ+µ−and B0→ρ0(π+π−)µ+µ−decays to an exponential function with a Gaussian high-mass endpoint contributes 0.6% uncertainty to the measured B+→π+µ+µ−yield, and using an analogous shape for the B0 s→f0(π+π−)µ+µ− decays contributes 0.7%. The parameters of the models are fixed to values obtained from a fit to the simulation. The systematic uncertainty of the model used for the semileptonic backgrounds is evaluated by allowing the exponent in the model to vary within the uncertainties produced by a fit to the simulation. This change contributes 0.3% uncertainty to the measured B+→π+µ+µ−yield. There is a negligible contribution from altering the model of the misidentified decays or combinatorial background, and from changing the upper mass end-point of the fit range from 6000 MeV/c2to either 5500 or 7000 MeV/c2. – 7 – JHEP10(2015)034 5 Results 5.1 Differential branching fraction The differential branching fraction of B+→π+µ+µ−in a bin of width ∆q2is calculated relative to the normalisation channel B+→J/ψ (µ+µ−)K+as dB(B+→π+µ+µ−) dq2=NB+ →π+µ+µ− B+ →π+µ+µ− ×B+ →J/ψ (µ+µ−)K+ NB+ →J/ψ (µ+µ−)K+ ×B(B+→J/ψ (µ+µ−)K+) ∆q2, (5.1) where Nis the event yield, is the total efficiency to select the decay, both of which are functions of q2, and B(B+→J/ψ (µ+µ−)K+) = (1.05±0.05)×10−3is the measured branching fraction of the normalisation channel, with B(J/ψ →µ+µ−) = (5.961 ±0.033)% [8,9]. The total efficiency to select the candidates for the decays considered is computed from the product of the efficiencies to trigger, reconstruct and select the final-state particles and the B+candidate. This includes the geometrical acceptance of the LHCb detector and the efficiencies of the trigger and selection algorithms. These efficiencies are calculated using a combination of simulated signal events and data-driven methods. The use of the ratio of efficiencies of the decay modes ensures that many of the possible sources of systematic uncertainty largely cancel. The efficiency of the trigger depends on the kinematics of the muons, and this dependence contributes a source of systematic uncertainty relative to the signal yield at the level of 2%. The dependence of the particle identification efficiency on the kinematic distributions contributes a systematic uncertainty of <0.1% for the muons, 2% for the pions and <0.1% for the kaons. These uncertainties are evaluated by varying the binning of the kinematic variables, and include a contribution from the size of the calibration samples used. The calculation of the BDT efficiency is affected by small differences between the simulation and data. The dependence of the signal yield on these differences is assessed using the B+→J/ψ (µ+µ−)K+and B+→J/ψ (µ+µ−)π+decays. The relatively large yield allows precise comparisons of data and simulation. The impact of using simulation to calculate the efficiency of the BDT is assessed using the observed differences between data and simulation in the normalisation channel; a systematic uncertainty of 1.4% is assigned. The measured values of the differential branching fraction are shown in figure 4and given in table 3. The branching fraction agrees with SM predictions from refs. [1,6], although agreement in the lowest-q2bin is only achieved when contributions from low-q2 resonances are taken into account, as in ref. [6]. The q2spectrum of candidates below 1 GeV2 /c4in a ±50 MeV window around the nominal B+mass is shown in figure 5, with hints of a peaking structure in the vicinity of the ρ0and ωmasses. The total branching fraction is computed from the integral over the measured bins multiplied by a scaling factor to account for the regions of q2not measured in this analysis. This factor is taken from simulation to be 1.333 ±0.004, where the uncertainty combines the statistical and systematic uncertainties evaluated by using two different form factor models. The total branching fraction is therefore B(B+→π+µ+µ−) = (1.83 ±0.24 (stat) ±0.05 (syst)) ×10−8. – 8 – JHEP10(2015)034 [33] C. Bourrely, I. Caprini and L. Lellouch, Model-independent description of B→π`ν decays and a determination of |Vub|,Phys. Rev. D 79 (2009) 013008 [Erratum ibid. D 82 (2010) 099902] [arXiv:0807.2722] [INSPIRE]. [34] I. Sentitemsu Imsong, A. Khodjamirian, T. Mannel and D. van Dyk, Extrapolation and unitarity bounds for the B→πform factor,JHEP 02 (2015) 126 [arXiv:1409.7816] [INSPIRE]. [35] P. Ball and R. Zwicky, New results on B→π, K, η decay formfactors from light-cone sum rules,Phys. Rev. D 71 (2005) 014015 [hep-ph/0406232] [INSPIRE]. [36] LHCb collaboration, Measurement of the semileptonic CP asymmetry in B0-B0mixing, Phys. Rev. Lett. 114 (2015) 041601 [arXiv:1409.8586] [INSPIRE]. [37] LHCb collaboration, Measurement of the D+ s-D− sproduction asymmetry in 7TeV pp collisions,Phys. Lett. B 713 (2012) 186 [arXiv:1205.0897] [INSPIRE]. – 15 – JHEP10(2015)034 The LHCb collaboration R. Aaij38, B. Adeva37, M. Adinolfi46, A. Affolder52, Z. Ajaltouni5, S. Akar6, J. Albrecht9, F. Alessio38, M. Alexander51, S. Ali41, G. Alkhazov30, P. Alvarez Cartelle53, A.A. Alves Jr57, S. Amato2, S. Amerio22, Y. Amhis7, L. An3, L. Anderlini17, J. Anderson40, G. Andreassi39, M. Andreotti16,f , J.E. Andrews58, R.B. Appleby54, O. Aquines Gutierrez10, F. Archilli38, P. d’Argent11, A. Artamonov35, M. Artuso59, E. Aslanides6, G. Auriemma25,m, M. Baalouch5, S. Bachmann11, J.J. Back48, A. Badalov36, C. Baesso60, W. Baldini16,38, R.J. Barlow54, C. Barschel38, S. Barsuk7, W. Barter38, V. Batozskaya28, V. Battista39, A. Bay39, L. Beaucourt4, J. Beddow51, F. Bedeschi23, I. Bediaga1, L.J. Bel41, V. Bellee39, N. Belloli20, I. Belyaev31, E. Ben-Haim8, G. Bencivenni18, S. Benson38, J. Benton46, A. Berezhnoy32, R. Bernet40, A. Bertolin22, M.-O. Bettler38, M. van Beuzekom41, A. Bien11, S. Bifani45, P. Billoir8, T. Bird54, A. Birnkraut9, A. Bizzeti17,h, T. Blake48, F. Blanc39, J. Blouw10, S. Blusk59, V. Bocci25, A. Bondar34, N. Bondar30,38, W. Bonivento15, S. Borghi54, M. Borsato7, T.J.V. Bowcock52, E. Bowen40, C. Bozzi16, S. Braun11, M. Britsch10, T. Britton59, J. Brodzicka54, N.H. Brook46, E. Buchanan46, A. Bursche40, J. Buytaert38, S. Cadeddu15, R. Calabrese16,f , M. Calvi20,j , M. Calvo Gomez36,o, P. Campana18, D. Campora Perez38, L. Capriotti54, A. Carbone14,d, G. Carboni24,k, R. Cardinale19,i, A. Cardini15, P. Carniti20, L. Carson50, K. Carvalho Akiba2,38, G. Casse52, L. Cassina20,j , L. Castillo Garcia38, M. Cattaneo38, Ch. Cauet9, G. Cavallero19, R. Cenci23,s, M. Charles8, Ph. Charpentier38, M. Chefdeville4, S. Chen54, S.-F. Cheung55, N. Chiapolini40, M. Chrzaszcz40, X. Cid Vidal38, G. Ciezarek41, P.E.L. Clarke50, M. Clemencic38, H.V. Cliff47, J. Closier38, V. Coco38, J. Cogan6, E. Cogneras5, V. Cogoni15,e, L. Cojocariu29, G. Collazuol22, P. Collins38, A. Comerma-Montells11, A. Contu15, A. Cook46, M. Coombes46, S. Coquereau8, G. Corti38, M. Corvo16,f , B. Couturier38, G.A. Cowan50, D.C. Craik48, A. Crocombe48, M. Cruz Torres60, S. Cunliffe53, R. Currie53, C. D’Ambrosio38, E. Dall’Occo41, J. Dalseno46, P.N.Y. David41, A. Davis57, K. De Bruyn41, S. De Capua54, M. De Cian11, J.M. De Miranda1, L. De Paula2, P. De Simone18, C.-T. Dean51, D. Decamp4, M. Deckenhoff9, L. Del Buono8, N. D´el´eage4, M. Demmer9, D. Derkach55, O. Deschamps5, F. Dettori38, B. Dey21, A. Di Canto38, F. Di Ruscio24, H. Dijkstra38, S. Donleavy52, F. Dordei11, M. Dorigo39, A. Dosil Su´arez37, D. Dossett48, A. Dovbnya43, K. Dreimanis52, L. Dufour41, G. Dujany54, F. Dupertuis39, P. Durante38, R. Dzhelyadin35, A. Dziurda26, A. Dzyuba30, S. Easo49,38, U. Egede53, V. Egorychev31, S. Eidelman34, S. Eisenhardt50, U. Eitschberger9, R. Ekelhof9, L. Eklund51, I. El Rifai5, Ch. Elsasser40, S. Ely59, S. Esen11, H.M. Evans47, T. Evans55, A. Falabella14, C. F¨arber38, N. Farley45, S. Farry52, R. Fay52, D. Ferguson50, V. Fernandez Albor37, F. Ferrari14, F. Ferreira Rodrigues1, M. Ferro-Luzzi38, S. Filippov33, M. Fiore16,38,f , M. Fiorini16,f , M. Firlej27, C. Fitzpatrick39, T. Fiutowski27, K. Fohl38, P. Fol53, M. Fontana15, F. Fontanelli19,i, R. Forty38, O. Francisco2, M. Frank38, C. Frei38, M. Frosini17, J. Fu21, E. Furfaro24,k, A. Gallas Torreira37, D. Galli14,d, S. Gallorini22, S. Gambetta50, M. Gandelman2, P. Gandini55, Y. Gao3, J. Garc´ıa Pardi˜nas37, J. Garra Tico47, L. Garrido36, D. Gascon36, C. Gaspar38, R. Gauld55, L. Gavardi9, G. Gazzoni5, D. Gerick11, E. Gersabeck11, M. Gersabeck54, T. Gershon48, Ph. Ghez4, S. Gian`ı39, V. Gibson47, O. G. Girard39, L. Giubega29, V.V. Gligorov38, C. G¨obel60, D. Golubkov31, A. Golutvin53,31,38, A. Gomes1,a, C. Gotti20,j , M. Grabalosa G´andara5, R. Graciani Diaz36, L.A. Granado Cardoso38, E. Graug´es36, E. Graverini40, G. Graziani17, A. Grecu29, E. Greening55, S. Gregson47, P. Griffith45, L. Grillo11, O. Gr¨unberg63, B. Gui59, E. Gushchin33, Yu. Guz35,38, T. Gys38, T. Hadavizadeh55, C. Hadjivasiliou59, G. Haefeli39, C. Haen38, S.C. Haines47, S. Hall53, B. Hamilton58, X. Han11, S. Hansmann-Menzemer11, N. Harnew55, S.T. Harnew46, J. Harrison54, J. He38, T. Head39, V. Heijne41, K. Hennessy52, P. Henrard5, L. Henry8, E. van Herwijnen38, M. Heß63, A. Hicheur2, – 16 – JHEP10(2015)034 D. Hill55, M. Hoballah5, C. Hombach54, W. Hulsbergen41, T. Humair53, N. Hussain55, D. Hutchcroft52, D. Hynds51, M. Idzik27, P. Ilten56, R. Jacobsson38, A. Jaeger11, J. Jalocha55, E. Jans41, A. Jawahery58, F. Jing3, M. John55, D. Johnson38, C.R. Jones47, C. Joram38, B. Jost38, N. Jurik59, S. Kandybei43, W. Kanso6, M. Karacson38, T.M. Karbach38,†, S. Karodia51, M. Kecke11, M. Kelsey59, I.R. Kenyon45, M. Kenzie38, T. Ketel42, B. Khanji20,38,j, C. Khurewathanakul39, S. Klaver54, K. Klimaszewski28, O. Kochebina7, M. Kolpin11, I. Komarov39, R.F. Koopman42, P. Koppenburg41,38, M. Kozeiha5, L. Kravchuk33, K. Kreplin11, M. Kreps48, G. Krocker11, P. Krokovny34, F. Kruse9, W. Krzemien28, W. Kucewicz26,n, M. Kucharczyk26, V. Kudryavtsev34, A. K. Kuonen39, K. Kurek28, T. Kvaratskheliya31, D. Lacarrere38, G. Lafferty54, A. Lai15, D. Lambert50, G. Lanfranchi18, C. Langenbruch48, B. Langhans38, T. Latham48, C. Lazzeroni45, R. Le Gac6, J. van Leerdam41, J.-P. Lees4, R. Lef`evre5, A. Leflat32,38, J. Lefran¸cois7, E. Lemos Cid37, O. Leroy6, T. Lesiak26, B. Leverington11, Y. Li7, T. Likhomanenko65,64, M. Liles52, R. Lindner38, C. Linn38, F. Lionetto40, B. Liu15, X. Liu3, D. Loh48, I. Longstaff51, J.H. Lopes2, D. Lucchesi22,q, M. Lucio Martinez37, H. Luo50, A. Lupato22, E. Luppi16,f , O. Lupton55, A. Lusiani23, F. Machefert7, F. Maciuc29, O. Maev30, K. Maguire54, S. Malde55, A. Malinin64, G. Manca7, G. Mancinelli6, P. Manning59, A. Mapelli38, J. Maratas5, J.F. Marchand4, U. Marconi14, C. Marin Benito36, P. Marino23,38,s, J. Marks11, G. Martellotti25, M. Martin6, M. Martinelli39, D. Martinez Santos37, F. Martinez Vidal66, D. Martins Tostes2, A. Massafferri1, R. Matev38, A. Mathad48, Z. Mathe38, C. Matteuzzi20, A. Mauri40, B. Maurin39, A. Mazurov45, M. McCann53, J. McCarthy45, A. McNab54, R. McNulty12, B. Meadows57, F. Meier9, M. Meissner11, D. Melnychuk28, M. Merk41, E Michielin22, D.A. Milanes62, M.-N. Minard4, D.S. Mitzel11, J. Molina Rodriguez60, I.A. Monroy62, S. Monteil5, M. Morandin22, P. Morawski27, A. Mord`a6, M.J. Morello23,s, J. Moron27, A.B. Morris50, R. Mountain59, F. Muheim50, D. M¨uller54, J. M¨uller9, K. M¨uller40, V. M¨uller9, M. Mussini14, B. Muster39, P. Naik46, T. Nakada39, R. Nandakumar49, A. Nandi55, I. Nasteva2, M. Needham50, N. Neri21, S. Neubert11, N. Neufeld38, M. Neuner11, A.D. Nguyen39, T.D. Nguyen39, C. Nguyen-Mau39,p, V. Niess5, R. Niet9, N. Nikitin32, T. Nikodem11, D. Ninci23, A. Novoselov35, D.P. O’Hanlon48, A. Oblakowska-Mucha27, V. Obraztsov35, S. Ogilvy51, O. Okhrimenko44, R. Oldeman15,e, C.J.G. Onderwater67, B. Osorio Rodrigues1, J.M. Otalora Goicochea2, A. Otto38, P. Owen53, A. Oyanguren66, A. Palano13,c, F. Palombo21,t, M. Palutan18, J. Panman38, A. Papanestis49, M. Pappagallo51, L.L. Pappalardo16,f , C. Pappenheimer57, C. Parkes54, G. Passaleva17, G.D. Patel52, M. Patel53, C. Patrignani19,i, A. Pearce54,49, A. Pellegrino41, G. Penso25,l, M. Pepe Altarelli38, S. Perazzini14,d, P. Perret5, L. Pescatore45, K. Petridis46, A. Petrolini19,i, M. Petruzzo21, E. Picatoste Olloqui36, B. Pietrzyk4, T. Pilaˇr48, D. Pinci25, A. Pistone19, A. Piucci11, S. Playfer50, M. Plo Casasus37, T. Poikela38, F. Polci8, A. Poluektov48,34, I. Polyakov31, E. Polycarpo2, A. Popov35, D. Popov10,38, B. Popovici29, C. Potterat2, E. Price46, J.D. Price52, J. Prisciandaro39, A. Pritchard52, C. Prouve46, V. Pugatch44, A. Puig Navarro39, G. Punzi23,r, W. Qian4, R. Quagliani7,46, B. Rachwal26, J.H. Rademacker46, M. Rama23, M.S. Rangel2, I. Raniuk43, N. Rauschmayr38, G. Raven42, F. Redi53, S. Reichert54, M.M. Reid48, A.C. dos Reis1, S. Ricciardi49, S. Richards46, M. Rihl38, K. Rinnert52, V. Rives Molina36, P. Robbe7,38, A.B. Rodrigues1, E. Rodrigues54, J.A. Rodriguez Lopez62, P. Rodriguez Perez54, S. Roiser38, V. Romanovsky35, A. Romero Vidal37, J. W. Ronayne12, M. Rotondo22, J. Rouvinet39, T. Ruf38, P. Ruiz Valls66, J.J. Saborido Silva37, N. Sagidova30, P. Sail51, B. Saitta15,e, V. Salustino Guimaraes2, C. Sanchez Mayordomo66, B. Sanmartin Sedes37, R. Santacesaria25, C. Santamarina Rios37, M. Santimaria18, E. Santovetti24,k, A. Sarti18,l, C. Satriano25,m, A. Satta24, D.M. Saunders46, D. Savrina31,32, M. Schiller38, H. Schindler38, M. Schlupp9, M. Schmelling10, T. Schmelzer9, B. Schmidt38, O. Schneider39, A. Schopper38, – 17 – JHEP10(2015)034 M. Schubiger39, M.-H. Schune7, R. Schwemmer38, B. Sciascia18, A. Sciubba25,l, A. Semennikov31, N. Serra40, J. Serrano6, L. Sestini22, P. Seyfert20, M. Shapkin35, I. Shapoval16,43,f , Y. Shcheglov30, T. Shears52, L. Shekhtman34, V. Shevchenko64, A. Shires9, B.G. Siddi16, R. Silva Coutinho48,40, L. Silva de Oliveira2, G. Simi22, M. Sirendi47, N. Skidmore46, I. Skillicorn51, T. Skwarnicki59, E. Smith55,49, E. Smith53, I. T. Smith50, J. Smith47, M. Smith54, H. Snoek41, M.D. Sokoloff57,38, F.J.P. Soler51, F. Soomro39, D. Souza46, B. Souza De Paula2, B. Spaan9, P. Spradlin51, S. Sridharan38, F. Stagni38, M. Stahl11, S. Stahl38, S. Stefkova53, O. Steinkamp40, O. Stenyakin35, S. Stevenson55, S. Stoica29, S. Stone59, B. Storaci40, S. Stracka23,s, M. Straticiuc29, U. Straumann40, L. Sun57, W. Sutcliffe53, K. Swientek27, S. Swientek9, V. Syropoulos42, M. Szczekowski28, P. Szczypka39,38, T. Szumlak27, S. T’Jampens4, A. Tayduganov6, T. Tekampe9, M. Teklishyn7, G. Tellarini16,f , F. Teubert38, C. Thomas55, E. Thomas38, J. van Tilburg41, V. Tisserand4, M. Tobin39, J. Todd57, S. Tolk42, L. Tomassetti16,f , D. Tonelli38, S. Topp-Joergensen55, N. Torr55, E. Tournefier4, S. Tourneur39, K. Trabelsi39, M.T. Tran39, M. Tresch40, A. Trisovic38, A. Tsaregorodtsev6, P. Tsopelas41, N. Tuning41,38, A. Ukleja28, A. Ustyuzhanin65,64, U. Uwer11, C. Vacca15,e, V. Vagnoni14, G. Valenti14, A. Vallier7, R. Vazquez Gomez18, P. Vazquez Regueiro37, C. V´azquez Sierra37, S. Vecchi16, J.J. Velthuis46, M. Veltri17,g, G. Veneziano39, M. Vesterinen11, B. Viaud7, D. Vieira2, M. Vieites Diaz37, X. Vilasis-Cardona36,o, V. Volkov32, A. Vollhardt40, D. Volyanskyy10, D. Voong46, A. Vorobyev30, V. Vorobyev34, C. Voß63, J.A. de Vries41, R. Waldi63, C. Wallace48, R. Wallace12, J. Walsh23, S. Wandernoth11, J. Wang59, D.R. Ward47, N.K. Watson45, D. Websdale53, A. Weiden40, M. Whitehead48, G. Wilkinson55,38, M. Wilkinson59, M. Williams38, M.P. Williams45, M. Williams56, T. Williams45, F.F. Wilson49, J. Wimberley58, J. Wishahi9, W. Wislicki28, M. Witek26, G. Wormser7, S.A. Wotton47, S. Wright47, K. Wyllie38, Y. Xie61, Z. Xu39, Z. Yang3, J. Yu61, X. Yuan34, O. Yushchenko35, M. Zangoli14, M. Zavertyaev10,b, L. Zhang3, Y. Zhang3, A. Zhelezov11, A. Zhokhov31, L. Zhong3and S. Zucchelli14. 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 6CPPM, Aix-Marseille Universit´e, CNRS/IN2P3, Marseille, France 7LAL, Universit´e Paris-Sud, CNRS/IN2P3, Orsay, France 8LPNHE, Universit´e Pierre et Marie Curie, Universit´e Paris Diderot, CNRS/IN2P3, Paris, France 9Fakult¨at Physik, Technische Universit¨at Dortmund, Dortmund, Germany 10 Max-Planck-Institut f¨ur Kernphysik (MPIK), Heidelberg, Germany 11 Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany 12 School of Physics, University College Dublin, Dublin, Ireland 13 Sezione INFN di Bari, Bari, Italy 14 Sezione INFN di Bologna, Bologna, Italy 15 Sezione INFN di Cagliari, Cagliari, Italy 16 Sezione INFN di Ferrara, Ferrara, Italy 17 Sezione INFN di Firenze, Firenze, Italy 18 Laboratori Nazionali dell’INFN di Frascati, Frascati, Italy 19 Sezione INFN di Genova, Genova, Italy 20 Sezione INFN di Milano Bicocca, Milano, Italy 21 Sezione INFN di Milano, Milano, Italy 22 Sezione INFN di Padova, Padova, Italy 23 Sezione INFN di Pisa, Pisa, Italy 24 Sezione INFN di Roma Tor Vergata, Roma, Italy – 18 – JHEP10(2015)034 25 Sezione INFN di Roma La Sapienza, Roma, Italy 26 Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Krak´ow, Poland 27 AGH - University of Science and Technology, Faculty of Physics and Applied Computer Science, Krak´ow, Poland 28 National Center for Nuclear Research (NCBJ), Warsaw, Poland 29 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania 30 Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia 31 Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia 32 Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia 33 Institute for Nuclear Research of the Russian Academy of Sciences (INR RAN), Moscow, Russia 34 Budker Institute of Nuclear Physics (SB RAS) and Novosibirsk State University, Novosibirsk, Russia 35 Institute for High Energy Physics (IHEP), Protvino, Russia 36 Universitat de Barcelona, Barcelona, Spain 37 Universidad de Santiago de Compostela, Santiago de Compostela, Spain 38 European Organization for Nuclear Research (CERN), Geneva, Switzerland 39 Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland 40 Physik-Institut, Universit¨at Z¨urich, Z¨urich, Switzerland 41 Nikhef National Institute for Subatomic Physics, Amsterdam, The Netherlands 42 Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam, The Netherlands 43 NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine 44 Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine 45 University of Birmingham, Birmingham, United Kingdom 46 H.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom 47 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 48 Department of Physics, University of Warwick, Coventry, United Kingdom 49 STFC Rutherford Appleton Laboratory, Didcot, United Kingdom 50 School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 51 School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 52 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 53 Imperial College London, London, United Kingdom 54 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 55 Department of Physics, University of Oxford, Oxford, United Kingdom 56 Massachusetts Institute of Technology, Cambridge, MA, United States 57 University of Cincinnati, Cincinnati, OH, United States 58 University of Maryland, College Park, MD, United States 59 Syracuse University, Syracuse, NY, United States 60 Pontif´ıcia Universidade Cat´olica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to 2 61 Institute of Particle Physics, Central China Normal University, Wuhan, Hubei, China, associated to 3 62 Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia, associated to 8 63 Institut f¨ur Physik, Universit¨at Rostock, Rostock, Germany, associated to 11 64 National Research Centre Kurchatov Institute, Moscow, Russia, associated to 31 65 Yandex School of Data Analysis, Moscow, Russia, associated to 31 66 Instituto de Fisica Corpuscular (IFIC), Universitat de Valencia-CSIC, Valencia, Spain, associated to 36 67 Van Swinderen Institute, University of Groningen, Groningen, The Netherlands, associated to 41 aUniversidade Federal do Triˆangulo Mineiro (UFTM), Uberaba-MG, Brazil – 19 – JHEP10(2015)034 bP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, Russia cUniversit`a di Bari, Bari, Italy dUniversit`a di Bologna, Bologna, Italy eUniversit`a di Cagliari, Cagliari, Italy fUniversit`a di Ferrara, Ferrara, Italy gUniversit`a di Urbino, Urbino, Italy hUniversit`a di Modena e Reggio Emilia, Modena, Italy iUniversit`a di Genova, Genova, Italy jUniversit`a di Milano Bicocca, Milano, Italy kUniversit`a di Roma Tor Vergata, Roma, Italy lUniversit`a di Roma La Sapienza, Roma, Italy mUniversit`a della Basilicata, Potenza, Italy nAGH - University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krak´ow, Poland oLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain pHanoi University of Science, Hanoi, Viet Nam qUniversit`a di Padova, Padova, Italy rUniversit`a di Pisa, Pisa, Italy sScuola Normale Superiore, Pisa, Italy tUniversit`a degli Studi di Milano, Milano, Italy †Deceased – 20 –