Observation of the Λ0b → J/ψ pπ − decay

JHEP07(2014)103 Published for SISSA by Springer Received:June 4, 2014 Accepted:June 28, 2014 Published:July 22, 2014 Observation of the Λ0 b→J/ψ pπ−decay The LHCb collaboration E-mail: [email protected] Abstract: The first observation of the Cabibbo-suppressed decay Λ 0 b→J/ψ pπ− is reported using a data sample of proton-proton collisions at 7 and 8 TeV, corresponding to an integrated luminosity of 3 fb −1 . A prominent signal is observed and the branching fraction relative to the decay mode Λ0 b→J/ψ pK−is determined to be B(Λ0 b→J/ψ pπ−) B(Λ0 b→J/ψ pK−)= 0.0824 ±0.0025 (stat) ±0.0042 (syst). A search for direct CP violation is performed. The difference in the CP asymmetries between these two decays is found to be ACP (Λ0 b→J/ψ pπ−)−ACP (Λ0 b→J/ψ pK−) = (+5.7±2.4 (stat) ±1.2 (syst))%, which is compatible with CP symmetry at the 2.2σlevel. Keywords: B physics, CP violation, Branching fraction, Flavor physics, Hadron-Hadron Scattering ArXiv ePrint: 1406.0755 Open Access, Copyright CERN, for the benefit of the LHCb Collaboration. Article funded by SCOAP3. doi:10.1007/JHEP07(2014)103 JHEP07(2014)103 Contents 1 Introduction 1 2 Detector and software 2 3 Event selection 2 4 Signal and background description 4 5CP asymmetry 6 6 Efficiency corrections and systematic uncertainties 7 7 Results and conclusions 9 The LHCb collaboration 14 1 Introduction The study of b -baryon decays is of considerable interest both to probe the dynamics of heavy flavour decay processes and to search for the effects of physics beyond the Standard Model. Owing to their non-zero spin, b baryons provide the potential to improve the limited understanding of the helicity structure of the underlying Hamiltonian [1,2]. Beauty baryons are copiously produced at the LHC, where the Λ0 b baryon cross-section is about half of the size of the B0 meson production in the forward region [ 3 , 4 ]. The ATLAS, CMS and LHCb collaborations measured the Λ0 b lifetime [ 5 – 8 ], and the masses of the ground [ 8 , 9 ] and first excited states [ 10 ]. The Λ0 b polarisation has been measured and found to be compatible with zero [ 11 ]. The LHCb collaboration has studied Λ0 b decays to charmonium [ 11 , 12 ], open charm [ 13 , 14 ], charmless states [ 15 ] and final states induced by electroweak penguins [ 16 ]. No evidence for CP violation has been reported in decays of baryons. Searches with b -baryon decays have been performed with the decay channels Λ0 b→pπ− , pK− [ 17 ] and K0 Spπ− [ 15 ]. The corresponding theoretical literature is still limited compared to that on Bmeson decays. The study of b→ccq decays can be used to constrain penguin pollution in the determination of the CP -violating phases in B0 and B0 s mixing [ 18 , 19 ]. While decays originating from the b→ccs transitions, such as Λ0 b→J/ψΛ or Λ0 b→J/ψpK− , are largely dominated by the tree amplitudes, penguins amplitudes are enhanced in Cabibbo-suppressed b→ccd transitions, such as the Λ0 b→J/ψpπ−decay. This article reports the first observation of the Λ0 b→J/ψpπ− decay and the determination of its branching fraction relative to the Cabibbo-favoured mode Λ0 b→J/ψpK− . The – 1 – JHEP07(2014)103 latter, which was recently observed, has been used to obtain a precise measurement of the ratio of Λ0 b to B0 lifetimes [ 5 , 12 ]. Its absolute branching ratio is yet to be determined. A measurement of the CP asymmetry difference between the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays is also reported. The analysis is based on a data sample of proton-proton collisions, corresponding to an integrated luminosity of 1 fb −1 at a centre-of-mass energy of 7 TeV and 2 fb−1at 8 TeV, collected with the LHCb detector. 2 Detector and software The LHCb detector [ 20 ] is a single-arm forward spectrometer covering the pseudorapidity range 2 < η < 5, designed for the study of particles containing b or c quarks. The detector includes a high-precision tracking system consisting of a silicon-strip vertex detector surrounding the proton-proton 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 [ 21 ] placed downstream of the magnet. The combined tracking system provides a momentum measurement with a relative uncertainty that varies from 0.4% at low momentum to 0.6% at 100 GeV/c , and an impact parameter measurement with a resolution of 20 µm for charged particles with large transverse momentum, pT . Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov (RICH) detectors [ 22 ]. 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 [ 23 ]. The trigger [ 24 ] 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. Candidate events are first required to pass the hardware trigger, which selects muons with pT> 1 . 48 GeV/c . In the subsequent software trigger, at least one of the candidate muons is required to be inconsistent with originating from any primary interaction. Finally, the muon pair is required to form a vertex that is significantly displaced from all primary vertices (PV) and to have a mass within 120 MeV/c2of the known J/ψ mass. In the simulation, proton-proton collisions are generated using Pythia [ 25 , 26 ] with a specific LHCb configuration [ 27 ]. Decays of hadronic particles are described by EvtGen [ 28 ], in which final state radiation is generated using Photos [ 29 ]. The interaction of the generated particles with the detector and its response are implemented using the Geant4 toolkit [30,31] as described in ref. [32]. 3 Event selection The Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays are reconstructed with the J/ψ decaying to two muons. Charge conjugation is implied throughout except in the definition of the CP asymmetry. Candidate J/ψ →µ+µ− decays are reconstructed from oppositely charged particles passing loose muon-identification requirements and with pT> 500 MeV/c . They are required – 2 – JHEP07(2014)103 to form a good quality vertex and have a mass in the range [3030 , 3150] MeV/c2 . This interval corresponds to about eight times the µ+µ− mass resolution at the J/ψ mass and covers part of the J/ψ meson radiative tail. Candidate Λ0 b baryons are selected from combinations of J/ψ candidates and two oppositely charged particles, one of which must be compatible with the proton hypothesis. The proton candidate is required to have a momentum, p , larger than 5 GeV/c , while the second charged particle must have p > 3 GeV/c . Both particles must have pT> 500 MeV/c and be inconsistent with coming from any PV. All four charged particles are required to be consistent with coming from a common vertex. The reconstructed mass and decay time of the Λ0 b candidates are obtained from a kinematic fit [ 33 ] that constrains the mass of the µ+µ− pairs to the known J/ψ mass and the Λ0 b candidate to originate from the PV. If the event has multiple PVs, all combinations are considered. Candidates are required to have a reconstructed decay time larger than 0 . 2 ps . To remove backgrounds from Λ0 b→J/ψΛ decays, candidates that have a pπ− mass within 5 MeV/c2 of the Λ baryon mass are vetoed. To remove reflections from B0 s→J/ψφ decays, candidates are also vetoed if the hadron-pair mass is less than 1035 MeV/c2 when applying a K+mass hypothesis to both particles. The remaining candidates are split into samples of Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− according to the estimated probabilities that the charged meson candidate is a kaon or a pion. These probabilities are determined using a neural network (NN) exploiting information from the RICH detectors, calorimeter and muon systems, as well as track quality. Particles with a larger pion probability are treated as Λ0 b→J/ψpπ− candidates, otherwise they are treated as Λ0 b→J/ψpK− candidates. In addition, the larger of these two probabilities is required to be in excess of 5%. The Λ0 b candidates are required to be in the mass range [4900 , 6100] MeV/c2 . After this selection 4 . 3 × 10 5Λ0 b→J/ψpπ− and 1 . 9 × 10 5Λ0 b→J/ψpK− candidates remain. The selection described above is not sufficient to isolate the small Λ0 b→J/ψpπ− signal from the combinatorial background. The initial selection is therefore followed by a multivariate analysis, based on another NN [ 34 ]. The NN classifier’s output is used as the final selection variable. The NN is trained entirely on data, using the Λ0 b→J/ψpK− signal as a proxy for the Λ0 b→J/ψpπ− decay. The training is performed using half of the Λ0 b→J/ψpK− candidates chosen at random. The other half is used to define the normalisation sample, allowing an unbiased measurement of the Λ0 b→J/ψpK− yield. The training uses signal and background weights determined using the sPlot technique [ 35 ] and obtained by performing a maximum likelihood fit to the unbinned mass distribution of the candidates meeting the loose selection criteria. The fit probability density function (PDF) is defined as the sum of the Λ0 b signal component and the combinatorial background components. The parameterisation of the individual components is described in the next section. Several reflections from B0 , B0 s and Λ0 b decays, reconstructed using misidentified particles, must be accounted for in the mass spectrum. In order to avoid the training being biased by these reflections, all candidates that have a mass compatible with the B0 , B0 s or – 3 – JHEP07(2014)103 Λ0 b mass after swapping the p and K assignments with any of π , K , or p are removed from the training. The NN classifier uses information about the candidate kinematic distributions, vertex and track quality, impact parameter and particle identification information on the proton. The most discriminating quantities are the proton particle identification probability, the kinematic fit quality and the kaon separation of the PV in this order. The variables that are used in the NN are chosen to avoid correlations with the reconstructed Λ0 b mass and to have identical distributions in Λ0 b→J/ψpπ−and Λ0 b→J/ψpK−simulated data. Final selection requirements of the NN classifier output are chosen to optimise the expected statistical precision on the Λ0 b→J/ψpπ− signal yield. The expected signal and background yields entering the sensitivity estimation are obtained from the training sample by scaling the number of surviving Λ0 b→J/ψpK− candidates by the expected yield based on an assumed branching fraction ratio of 0 . 1. The expected background is extrapolated from the number of Λ0 b→J/ψpπ− candidates in the mass range [5770 , 6100] MeV/c2 . After applying the final requirement on the NN classifier output, the multivariate selection rejects 99% of the background while keeping 75% of the Λ0 b→J/ψpK− signal, relative to the initial selection. After applying the full selection, about 0 . 1% of the selected events have more than one candidate sharing at least one track, or more than one PV that can be used to determine the kinematic properties of the candidate. In these cases one of the candidates or PVs is used at random. 4 Signal and background description For the candidates passing the NN requirements, the yields of Λ0 b→J/ψpπ− and Λ0 b→ J/ψpK− decays are determined from unbinned maximum likelihood fits to the mass distributions of reconstructed Λ0 b candidates. The PDF is defined as the sum of a Λ0 b signal component, a combinatorial background and the sum of several reflections. The signal shape is parametrised by a Gaussian distribution with power-law tails on both sides, as indicated by simulation. The parameters describing the tails are taken from simulation, while the mean and width of the Gaussian are allowed to vary in the fit. The combinatorial background contribution is described by an exponential function, with yield and slope parameter allowed to vary freely. Several peaking backgrounds due to decays of b hadrons to J/ψ mesons and two charged hadrons, where one or both hadrons are misidentified, survive the selection. In this fit they are not vetoed, unlike in the training of the NN, except for candidates consistent with the B0 s→J/ψφ hypothesis. Instead, their contribution is modelled by smoothed non-parametric functions determined from simulated data. The respective yields are determined by swapping the mass assignments of the p , π and K in turn and searching for peaks at the B0 , B0 s or Λ0 b masses. In the Λ0 b→J/ψpπ− fit, significant backgrounds are found from the decays Λ0 b→J/ψpK− (with K− identified as π− ), B0→J/ψK+π− (with K+ identified as p ), and B0 s→J/ψK+K− (with one K identified as p and the other as π ). In the Λ0 b→J/ψpK− fit, the main contributions are from the decays B0→J/ψπ+K− (with π+ identified as p ), – 4 – JHEP07(2014)103 ] 2 [MeV/c - πpψJ/ m 5500 5600 5700 2 Candidates per 5 MeV/c 0 200 400 600 800 1000 1200 1400 LHCb Data - πpψJ/→ b Λ - pKψJ/→ b Λ B reflections Combinatorial Total ] 2 [MeV/c - pKψJ/ m 5500 5600 5700 2 Candidates per 5 MeV/c 10 2 10 3 10 Data - pKψJ/→ b Λ B reflections Combinatorial Total LHCb Figure 1 . Distribution of (left) J/ψ pπ− and (right) J/ψ pK− masses with fit projections overlaid. For Λ0 b→J/ψ pK−candidates, only the normalisation sample is shown. B0 s→J/ψK+K− (with K+ identified as p ), and Λ0 b→J/ψpK+ (with K− and p swapped). These yields are then used as Gaussian constraints on the normalisation of the reflection background shapes. The results of the fits are shown in figure 1. The contributions of the reflections are summed, except for the large Λ0 b→J/ψpK− reflection in the Λ0 b→J/ψpπ− fit, which is shown separately. Low-mass contributions of partially reconstructed Λ0 b→J/ψpπ−π0 and Λ0 b→J/ψpK−π0 decays, where the π0 is not considered in the combination, are investigated. Adding such a component to the fit, with a mass shape taken from simulation, results in yields compatible with zero and does not change the signal yields. In total 11 179 ± 109 Λ0 b→J/ψpK− and 2102 ± 61 Λ0 b→J/ψpπ− decays are obtained. The Λ0 b→J/ψpK− yield, having been determined on the half of the data not used in the training, is multiplied by two, resulting in a ratio of Λ0 b→J/ψpπ− to Λ0 b→J/ψpK− yields of 0.0940 ±0.0029. The shapes used in the mass fit are varied to determine a systematic uncertainty related to the mass model. No significant differences are found when trying alternate signal parameterisation that still result in a good fit. Changing the peaking backgrounds PDF, or letting their yield free in the fit, change their relative fit fractions, as well as that of the combinatorial background, but does not affect the signal yields. The combinatorial background model is changed from an exponential to a second-order polynomial, which results in a Λ0 b→J/ψpπ− ( Λ0 b→J/ψpK− ) yield reduced by 2.1% (0.3%). These variations are added in quadrature and used to estimate a systematic uncertainty on the ratio of branching fractions. – 5 – JHEP07(2014)103 5CP asymmetry The same fit procedure is repeated separately for baryon (tagged by a positively charged proton) and antibaryon candidates. All parameters of the fits are determined again separately, except for the signal shape and the combinatorial background slope, which are taken from the fit to all candidates. A total of 1131 ± 40 Λ0 b→J/ψpπ− , 964 ± 38 Λ0 b→J/ψpπ+ , 5655 ± 77 Λ0 b→J/ψpK− and 5529 ± 76 Λ0 b→J/ψpK+ decays are found, corresponding to the raw asymmetries Araw(Λ0 b→J/ψpπ−)≡N(Λ0 b→J/ψpπ−)−N(Λ0 b→J/ψpπ+) N(Λ0 b→J/ψpπ−) + N(Λ0 b→J/ψpπ+)(5.1) = (+7.9±2.2)%, Araw(Λ0 b→J/ψpK−) = (+1.1±0.9)%. The procedure to assess the systematic uncertainties related to the shape of the mass distribution, described in section 4, is repeated to determine the sensitivity of the raw asymmetries. A total variation of 0.7% is obtained, which is dominated by a change in Araw(Λ0 b→J/ψpπ−) when using a second-order polynomial background model. The raw decay-rate asymmetry can be decomposed as Araw(Λ0 b→J/ψph−) = ACP (Λ0 b→J/ψph−) + Aprod(Λ0 b)−Areco(h+) + Areco(p),(5.2) where the terms on the right hand side of the equation are the CP -violating, Λ0 b production and reconstruction asymmetries of the hadron h± = π±, K± and the proton, respectively. Reconstruction asymmetries are defined following the convention Areco ( h+ ) ≡(h+)−(h−) (h+)+(h−) throughout, where  is the reconstruction efficiency. The production asymmetry Aprod and the proton reconstruction asymmetry cancel in the difference of the two asymmetries ∆ACP ≡ ACP (Λ0 b→J/ψpπ−)−ACP (Λ0 b→J/ψpK−) =Araw(Λ0 b→J/ψpπ−)−Araw(Λ0 b→J/ψpK−) + Areco(π+)−Areco(K+).(5.3) The kaon and pion asymmetries can be determined from the raw asymmetry of the B0→J/ψK∗(892)0decay with K∗(892)0→K−π+. It has been measured [36] as Araw(B0→J/ψ K∗(892)0)≡N(B0)−N(B0) N(B0) + N(B0)= (−1.10 ±0.32 ±0.06)%,(5.4) where the first uncertainty is statistical and the second systematic. It can be decomposed as Araw(B0→J/ψ K∗(892)0) = ACP (B0→J/ψK∗(892)0)−κAprod(B0) (5.5) +Areco(π+)−Areco(K+) ≈Areco(π+)−Areco(K+),(5.6) where κ is a dilution factor due to B0 mixing and Aprod ( B0 ) is the B0 production asymmetry, which is compatible with zero [ 37 ]. Under the assumption of no CP asymmetry in the – 6 – JHEP07(2014)103 B0→J/ψK∗(892)0 decay and negligible production asymmetry, this value can thus be taken as the combined kaon and pion reconstruction asymmetry, and is consistent with measurements in other decay modes to kaon and pions [37,38]. The difference of CP asymmetries in the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays can then be rewritten as ∆ACP =Araw(Λ0 b→J/ψpπ−)−Araw(Λ0 b→J/ψpK−) + Araw(B0→J/ψK∗(892)0) (5.7) = (+5.7±2.4)%, where the uncertainty is statistical only. The kaon and pion momenta in Λ0 b decays are not identical to those in B0→J/ψK∗(892)0 decays, which could induce different detector asymmetries in the Λ0 b and B0 modes. This is investigated by weighting the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− data to match the pion and kaon momentum distributions observed in B0→J/ψK∗(892)0 decays. The value of ∆ ACP changes by 0.8%, which is assigned as the systematic uncertainty related to reconstruction asymmetries. Local CP asymmetries in the Dalitz plane are also searched for using the technique outlined in ref. [39,40]. No significant local asymmetries are found. 6 Efficiency corrections and systematic uncertainties The raw quantities need to be corrected to determine the physics quantities. The efficiency of the selection requirements is studied with simulation. Some quantities are known not to be well reproduced in simulation, namely the Λ0 b transverse momentum and lifetime, the particle multiplicity, and the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decay kinematic properties. For all these quantities the simulated data are weighted to match the observed distributions in data. They are obtained with the sPlot technique using the Λ0 b candidate mass as the control variable. For three-body b -hadron decays, both the signal decays and the dominant combinatorial backgrounds populate regions close to the kinematic boundaries of the J/ψpπ− and J/ψpK− Dalitz plot [ 41 ]. For more accurate modelling of these regions, it is convenient to transform the conventional Dalitz space to a rectangular space (hereafter referred to as the square Dalitz plot [42]). We follow the procedure described in ref. [15]. The Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays have different detector acceptance, reconstruction and selection efficiencies. They are determined from simulated data, which are weighted to match the experimental data. The main differences are induced by i. the detector acceptance, as the efficiency of Λ0 b→J/ψpK− is 6% larger than that for the Λ0 b→J/ψpπ− decays due to the lower kinetic energy release in the former, which causes smaller opening angles; ii. the reconstruction and preselection efficiency, which is 4% larger in Λ0 b→J/ψpπ− decays due to the average total and transverse momentum of the final state particles being larger than in Λ0 b→J/ψpK−decays; – 7 – JHEP07(2014)103 Source BF ∆ACP Simulation-based corrections 0.913 ±0.040 - PID 0.960 ±0.010 - Trigger 1.000 ±0.010 - Λ0 blifetime 1.000 ±0.001 - Mass distribution model 1.000 ±0.021 0.0±0.7% B0→J/ψK∗(892)0-−1.1±0.3% Detection asymmetries - 0.0±0.8% Total 0.876 ±0.045 −1.1±1.2 % Table 1 . Corrections and related systematic uncertainties on the ratio of Λ0 b→J/ψpπ− to Λ0 b→J/ψpK− branching fractions (BF) and on the difference between the CP asymmetries ∆ ACP . The corrections are multiplicative on the branching fraction and additive for the asymmetry. iii. the particle identification requirements on the π− or K− , which are more efficient on Λ0 b→J/ψpπ−decays by 7%; iv. the φveto, which removes 7% (3%) of the Λ0 b→J/ψpK−(J/ψpπ−) signal. Overall, these effects result in a further correction on the ratio of branching fractions of Λ0 b→J/ψpπ−to Λ0 b→J/ψpK−decays of 0.913 ±0.040. The efficiency of particle identification is not perfectly modelled in simulation. The kaon and pion identification efficiencies are further weighted after the kinematic weighting described above, using a large sample of D∗ -tagged D0→K−π+ decays. The uncertainties are determined by varying the weights of the simulated data within their uncertainties, yielding a correction of 0 . 960 ± 0 . 010. The kinematic properties of the proton in the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays are found to be the same. The same applies to the muons. The efficiencies of proton and muon identification therefore cancel in the ratio of branching fractions, as well as in the CP asymmetries. The trigger efficiency is determined using simulation, which is validated using Λ0 b→ J/ψpK− decays from data. Differences between the Λ0 b→J/ψpπ− and Λ0 b→J/ψpK− decays efficiencies are at the percent level and are assigned as systematic uncertainties. The value of the Λ0 b lifetime used in simulation is taken from ref. [ 43 ], and is 3% lower than the current most precise measurement [ 5 ]. The simulated data is weighted to account for this and the difference is assigned as a systematic uncertainty. The estimates of the systematic uncertainties described above are summarised in table 1, along with the total obtained by summing them in quadrature. The uncertainty on the ratio of branching fractions is dominated by the uncertainty on corrections obtained from simulation, mostly due to the unknown decay kinematic properties of the Λ0 b→J/ψpπ− decay. For ∆ ACP , the mass model distribution and the detection asymmetries contribute about equally. – 8 – JHEP07(2014)103 D. Hynds 51 , M. Idzik 27 , P. Ilten 56 , R. Jacobsson 38 , A. Jaeger 11 , J. Jalocha 55 , E. Jans 41 , P. Jaton 39 , A. Jawahery 58 , F. Jing 3 , M. John 55 , D. Johnson 55 , C.R. Jones 47 , C. Joram 38 , B. Jost 38 , N. Jurik 59 , M. Kaballo9, S. Kandybei43, W. Kanso6, M. Karacson38, T.M. Karbach38, S. Karodia51, M. Kelsey59, I.R. Kenyon45, T. Ketel42, B. Khanji20, C. Khurewathanakul39, S. Klaver54, O. Kochebina7, M. Kolpin11, I. Komarov39, R.F. Koopman42, P. Koppenburg41,38, M. Korolev32, A. Kozlinskiy 41 , L. Kravchuk 33 , K. Kreplin 11 , M. Kreps 48 , G. Krocker 11 , P. Krokovny 34 , F. Kruse 9 , W. Kucewicz26,o, M. Kucharczyk20,26,38,k, V. Kudryavtsev34, K. Kurek28, T. Kvaratskheliya31, V.N. La Thi39, D. Lacarrere38, G. Lafferty54, A. Lai15, D. Lambert50, R.W. Lambert42, E. Lanciotti38, G. Lanfranchi18, C. Langenbruch38, B. Langhans38, T. Latham48, C. 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Perrin-Terrin 6 , L. Pescatore 45 , E. Pesen 66 , K. Petridis 53 , A. Petrolini 19,j , E. Picatoste Olloqui 36 , B. Pietrzyk4, T. Pilaˇr48, D. Pinci25, A. Pistone19, S. Playfer50, M. Plo Casasus37, F. Polci8, A. Poluektov 48,34 , E. Polycarpo 2 , A. Popov 35 , D. Popov 10 , B. Popovici 29 , C. Potterat 2 , E. Price 46 , J. Prisciandaro39, A. Pritchard52, C. Prouve46, V. Pugatch44, A. Puig Navarro39, G. Punzi23,t, W. Qian 4 , B. Rachwal 26 , J.H. Rademacker 46 , B. Rakotomiaramanana 39 , M. Rama 18 , M.S. Rangel 2 , I. Raniuk43, N. Rauschmayr38, G. Raven42, S. Reichert54, M.M. Reid48, A.C. dos Reis1, S. Ricciardi49, S. Richards46, M. Rihl38, K. Rinnert52, V. Rives Molina36, D.A. Roa Romero5, P. Robbe 7 , A.B. Rodrigues 1 , E. Rodrigues 54 , P. Rodriguez Perez 54 , S. Roiser 38 , V. Romanovsky 35 , A. Romero Vidal 37 , M. Rotondo 22 , J. Rouvinet 39 , T. Ruf 38 , F. Ruffini 23 , H. Ruiz 36 , P. Ruiz Valls 64 , G. Sabatino25,l, J.J. Saborido Silva37, N. Sagidova30, P. Sail51, B. Saitta15,e, V. Salustino Guimaraes2, C. Sanchez Mayordomo64, B. Sanmartin Sedes37, R. Santacesaria25, C. Santamarina Rios37, E. Santovetti24,l, M. Sapunov6, A. Sarti18,m, C. Satriano25,n, A. Satta24, D.M. Saunders46, M. Savrie16,f , D. Savrina31,32, M. Schiller42, H. Schindler38, M. Schlupp9, M. Schmelling10, B. Schmidt38, O. Schneider39, A. Schopper38, M.-H. Schune7, R. Schwemmer38, B. Sciascia18, A. Sciubba25, M. Seco37, A. Semennikov31, I. Sepp53, N. Serra40, J. Serrano6, L. Sestini22, P. Seyfert11, M. Shapkin35, I. Shapoval16,43,f , Y. Shcheglov30, T. Shears52, L. Shekhtman34, V. Shevchenko63, A. Shires9, R. Silva Coutinho48, G. Simi22, M. Sirendi47, N. Skidmore46, T. Skwarnicki59, N.A. Smith52, E. Smith55,49, E. Smith53, J. Smith47, M. Smith54, – 15 – JHEP07(2014)103 H. Snoek41, M.D. Sokoloff57, F.J.P. Soler51, F. Soomro39, D. Souza46, B. Souza De Paula2, B. Spaan9, A. Sparkes50, P. Spradlin51, F. Stagni38, M. Stahl11, S. Stahl11, O. Steinkamp40, O. Stenyakin 35 , S. 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Zvyagin38 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 de Savoie, 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 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 – 16 – JHEP07(2014)103 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 Institut f¨ur Physik, Universit¨at Rostock, Rostock, Germany, associated to 11 63 National Research Centre Kurchatov Institute, Moscow, Russia, associated to 31 64 Instituto de Fisica Corpuscular (IFIC), Universitat de Valencia-CSIC, Valencia, Spain, associated to 36 65 KVI - University of Groningen, Groningen, The Netherlands, associated to 41 66 Celal Bayar University, Manisa, Turkey, associated to 38 aUniversidade Federal do Triˆangulo Mineiro (UFTM), Uberaba-MG, Brazil 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 Firenze, Firenze, Italy hUniversit`a di Urbino, Urbino, Italy iUniversit`a di Modena e Reggio Emilia, Modena, Italy jUniversit`a di Genova, Genova, Italy kUniversit`a di Milano Bicocca, Milano, Italy lUniversit`a di Roma Tor Vergata, Roma, Italy mUniversit`a di Roma La Sapienza, Roma, Italy – 17 – JHEP07(2014)103 nUniversit`a della Basilicata, Potenza, Italy oAGH - University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krak´ow, Poland pLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain qUniversity of Utrecht, Utrecht, The Netherlands rHanoi University of Science, Hanoi, Viet Nam sUniversit`a di Padova, Padova, Italy tUniversit`a di Pisa, Pisa, Italy uScuola Normale Superiore, Pisa, Italy vUniversit`a degli Studi di Milano, Milano, Italy – 18 –