LHCb-CONF-2015-003July 27, 2015

A precise measurement of the B0

meson oscillation frequency

The LHCb collaboration †

Abstract

The oscillation frequency of B0 mesons is measured using semileptonic decays witha charged D or D∗ meson in the final state, on a data sample collected by the LHCbdetector corresponding to an integrated luminosity of 3 fb−1 of pp collisions. Acombination of the two decay modes gives ∆md = (503.6± 2.0± 1.3) ns−1, wherethe first uncertainty is statistical and the second systematic. This is the most precisesingle measurement of this parameter. It is compatible with the current worldaverage and has comparable precision.

c© CERN on behalf of the LHCb collaboration, licence CC-BY-4.0.

†Conference report prepared for the 2015 European Physical Society Conference on High Energy Physics(EPS-HEP), Vienna, Austria, 22–29 July 2015. Contact author: Basem Khanji basem.khanji@cern.ch

1 Introduction

Flavour oscillation, or mixing, of neutral meson systems is due to mass eigenstates beingdifferent from flavour eigenstates. In B0 mesons, the mass difference between masseigenstates, ∆md, is directly related to the square of the product of the CKM matrixelements Vtb and V ∗td, and therefore probes the CKM mechanism of CP violation in theStandard Model.

Several measurements of ∆md have been performed by experiments at LEP, Tevatron,B Factories and, most recently, at LHCb [1–3], resulting in a world average value witha relative precision of 0.6% [4]. This letter reports a measurement of ∆md based onB0→ D−µ+νµX and B0→ D∗−µ+νµX decays 1 in a data sample of pp collisions collectedat LHCb during Run1 in 2011 at

√s =7 and in 2012 at 8 TeV, corresponding to an

integrated luminosity of about 1 and 2 fb−1, respectively.The relatively high branching fraction for semileptonic decays of B0 mesons, when

paired with the highly efficient lepton identification and flavour tagging capabilities atLHCb, result in abundant samples of B0→ D(∗)−µ+νµX decays where the flavour of theB0 meson at the time of production and decay is known. In addition, the decay time,t, of B0 mesons can be determined with good resolution though the decay is not fullyreconstructed due to the missing neutrino. It is therefore possible to precisely measure theoscillation frequency ∆md from a time-dependent analysis of the decay rates of unmixedand mixed events, Nunmix(t) and Nmix(t):

Nunmix(t) ≡ N(B0→ D(∗)−µ+νµX)(t) ∝ e−Γdt[1 + cos(∆mdt)] ,

Nmix(t) ≡ N(B0 → B0→ D(∗)+µ−νµX)(t) ∝ e−Γdt[1− cos(∆mdt)] , (1)

where the mixing state assignement is based on the flavour of the B0 meson at productionand decay being the same (unmixed) or the opposite (mixed). In Eqn. 1, Γd = 1/τd isthe decay width of the B0 meson, while the difference in the decay widths of the masseigenstates, ∆Γd, is assumed to vanish, and CP violation in mixing is neglected. Theflavour asymmetry between unmixed and mixed events is

A(t) =Nunmix(t)−Nmix(t)

Nunmix(t) +Nmix(t)= cos(∆mdt) . (2)

A concise description of the LHCb detector and the collision and simulated datasetsused in this measurement is given in Section 2. Section 3 presents the selection criteria,the flavour tagging algorithms, and the method chosen to reconstruct the B decay time.The fitting strategy and results are shown in Section 4. A summary of the systematicuncertainties is given in Section 5. Conclusions are reported in Section 6.

1charge-conjugation is always implied throughout this letter.

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2 Detector and simulation

The LHCb detector [5,6] is a single-arm forward spectrometer covering the pseudorapidityrange 2 < η < 5, designed for the study of particles containing b or c quarks. Thedetector includes a high-precision tracking system consisting of a silicon-strip vertexdetector surrounding the pp interaction region [7], a large-area silicon-strip detectorlocated upstream of a dipole magnet with a bending power of about 4 Tm, and threestations of silicon-strip detectors and straw drift tubes [8] placed downstream of the magnet.The tracking system provides a measurement of momentum, p, of charged particles with arelative uncertainty that varies from 0.5% at low momentum to 1.0% at 200 GeV/c. Theminimum distance of a track to a primary vertex, the impact parameter, is measured witha resolution of (15+29/pT) µm, where pT is the component of the momentum transverse tothe beam, in GeV/c. Different types of charged hadrons are distinguished using informationfrom two ring-imaging Cherenkov (RICH) detectors [9]. Photons, electrons and hadrons areidentified by a calorimeter system consisting of scintillating-pad and preshower detectors,an electromagnetic calorimeter and a hadronic calorimeter. Muons are identified by asystem composed of alternating layers of iron and multiwire proportional chambers [10].

The online event selection is performed by a trigger [11,12], which consists of a hardwarestage, based on information from the calorimeter and muon systems, followed by a softwarestage, which applies a full event reconstruction. Candidate events are first required to passthe hardware trigger, which selects muons with a transverse momentum pT > 1.48 GeV/cin the 7 TeV data or pT > 1.76 GeV/c in the 8 TeV data. The software trigger requiresa two-, three- or four-track secondary vertex, where one of the tracks is identified as amuon, with a significant displacement from the primary pp interaction vertices (PVs).At least one charged particle must have a transverse momentum pT > 1.7 GeV/c and beinconsistent with originating from a PV. A multivariate algorithm [13] is used for theidentification of secondary vertices consistent with the decay of a b hadron.

The method chosen to reconstruct the B decay time relies on Monte Carlo simulation.Simulated data are also used to estimate the main background sources and to verify thefit model. In the simulation, pp collisions are generated using Pythia [14] with a specificLHCb configuration [15]. Decays of hadronic particles are described by EvtGen [16],in which final-state radiation is generated using Photos [17]. The interaction of thegenerated particles with the detector, and its response, are implemented using the Geant4toolkit [18] as described in Ref. [19]. Large samples of mixtures of semileptonic decaysresulting in a D− or a D∗− in the final state were generated and the various assumptionsused to build these samples are assessed in the evaluation of systematic uncertainties.

3 Event selection criteria

For charged particles used to reconstruct signal candidates, requirements are imposed ontrack quality, impact parameter (IP) with respect to any primary vertex, momentum, andtransverse momentum.

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Tracks are required to be identified as muons, kaons or pions. The charm mesonsare reconstructed through the D− → K+π−π− decay, or through the D∗− → D0π−,D0→ K+π− decay chain. Their reconstructed masses should be in a range containing theirknown masses values [4]. For D− and D0 candidates, the sum of the pT of the daughtersshould be above 1800 MeV/c. A good quality vertex fit is required for the D−, D0, andD∗− candidates, and for the D(∗)−µ+ combination (referred to as the B candidate fromnow onwards). The reconstructed vertices of D−, D0, and B candidates are required tobe significantly detached from the reconstructed primary vertex (PV). For D− and D0

candidates, a large IP with respect to the PV is required. The B momentum and its flightdirection, measured using the PV and the B vertex positions, are required to be aligned.The selection criteria mentioned above reduce the contribution of D(∗)− decays, where thecharmed meson originates from the primary vertex, to the per-mille level or less. Moreover,the invariant mass of the B candidate is required to be in the range [3.0, 5.2] GeV/c2.

Vetoes based on invariant mass are applied firstly to suppress B → J/ψX decays, whereone of the muons from the J/ψ decay is mis-identified as a pion and is mis-reconstructedas a D(∗)−, and secondly to suppress semileptonic decays of the Λ0

b baryon, where theproton of the subsequent Λ+

c decay into pK−π+ mimics the signature of a D− meson.The dominant background is due to B+→ D−µ+νµX and B+→ D∗−µ+νµX decays

where additional particles coming from the decay of higher charm resonances, or frommulti-body decays of B mesons, are not considered. This background is reduced by usinga multivariate discriminant based on a boosted decision tree (BDT) algorithm [20, 21],which exploits information on the B candidate, kinematics of the higher charm resonanceand isolation criteria for tracks and composite candidates in the B decay chain. Trainingof the BDT classifier is carried out using simulation samples of B0→ D∗−µ+νµX signaland B+→ D∗−µ+νµX backgorund. The variables used as input for the BDT classifier aredescribed in the Appendix.

Combinatorial background is evaluated by using reconstructed events in the D(∗)−

signal mass sidebands. Backgrounds due to decays of B0s and Λ0

b into similar final statesas those of the signal are studied through simulations.

The decay time of the B0 meson is calculated as t = (MB0 · L)/(prec · c/k), whereMB0 is the mass of the B0, taken from Ref. [4], L is the measured decay length andprec is its visible momentum, measured from the D− or D∗− meson and the muon. Insemileptonic decays the momentum of the B0 meson cannot be measured precisely dueto unreconstructed particles. Therefore the B0 momentum is inferred by dividing itsvisible momentum by the factor k = 〈prec/ptrue〉 determined from simulation, where ptrue

is the true B momentum. This correction depends on the decay time and represents thedominant source of uncertainty in the determination of the decay time of the B0 meson fort > 1.5 ps. Since the k-factor strongly depends on the decay kinematics, it is parametrisedby a second-order (fourth-order) polynomial that depends on the visible mass of the Bcandidate in the B0→ D−µ+νµX (B0→ D∗−µ+νµX) modes.

The B0 flavour at production time is determined by using information from the otherb hadron present in an event. The decision of flavour tagging algorithms [22] based on thecharge of leptons, kaons, and of an inclusively reconstructed detached vertex, is used for the

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B0→ D∗−µ+νµX channel. In the B0→ D−µ+νµX channel, which is subject to a larger B+

background contamination, the decision of the tagging algorithm based on the detachedvertex is excluded in order to avoid spurious background asymmetries. The statisticaluncertainty on ∆md decreases as a function of the tagging power P = εtag(1 − 2ω)2 asP−1/2, where εtag is the tagging effiency and ω is the mistag rate. To increase the statisticalprecision, the events are grouped into four categories of increasing predicted mistag η,defined by η ∈ [0, 0.25], [0.25, 0.33], [0.33, 0.41], [0.41, 0.47]. The average mistag rates forsignal and background are taken as free parameters when fitting for ∆md. The combinedtagging power for the B0→ D−µ+νµX mode is (2.38± 0.05)% and (2.46± 0.04)% in 2011and 2012 data, respectively. For the B0→ D∗−µ+νµX mode, the tagging power in 2011and 2012 are (2.55± 0.07)% and (2.32± 0.04)%, respectively.

4 Fit strategy and results

The fit strategy proceeds in three stages. Firstly, D(∗)− mesons originating from semilep-tonic B0 or B+ decays are separated from the background coming from combinations oftracks not associated to a charm meson decay by a fit to the invariant mass distributionsof the selected candidates. This fit assigns to each event an sWeight [23], corresponding tothe probability of having a charmed meson from a semileptonic B0 or B+ decay. This isused in the subsequent fits to cancel the contribution of the background by means of thesPlot [23] procedure. Secondly, the contribution of D(∗)− from B+ decays is determinedin a subsequent fit to the distributions of the BDT classifier reweighted for the signalsWeights. The BDT distributions corresponding to the B0 and B+ decays are extractedfrom simulated events. Finally, the oscillation frequency ∆md is determined by a fit to thetime distribution of unmixed and mixed candidates reweighted for the signal sWeights.

An extended, binned maximum likelihood fit to the data distributions is performed foreach stage, simultaneously for the four tagging categories defined above. Events collectedin 2011 and 2012 are treated separately.

Figure 1 shows the results of the fits to the D− mass distributions of B0→ D−µ+νµX.In these fits, the distributions of D− from B0 and B+ decays are summed as they aredescribed by the same probability density function (PDF): the sum of two Gaussians and aCrystal Ball function [24]. The yields corresponding to the D− peak are (5.73± 0.02)× 105

and (1.598± 0.003)× 106 in 2011 and 2012 data, respectively. The combinatorial back-ground, which contributes about 6% under the D− peak, is modelled with an exponentialdistribution.

For the B0→ D∗−µ+νµX samples, a simultaneous fit to the distributions of the Kπinvariant mass, m = mKπ, and the invariant mass difference of Kππ and Kπ combinations,δm = mKππ −mKπ, is performed. Three different components are considered: the signalD∗ from B decays and two background sources. The PDF for the mass distributions ofD∗ from B decays is defined by the sum of two Gaussians and a Crystal Ball functionin the m mass projection and by two Gaussians and a Johnson function [25] in the δmmass projection. A combinatorial background of the order of 4% under the D∗ peak is

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modelled with an exponential distribution for m and a phase space distribution withthreshold for δm. Background candidates containing a D0 originating from a b hadrondecay without an intermediate D∗ resonance, which contribute about 15% in the full δmmass range, are described by the same distribution as that of the signal for m, and by thesame function used for the combinatorial background component for δm. All parameterswhich describe signal and background shapes vary freely in the invariant mass fits. Theresults of the 2011 and 2012 fits for the nuisance parameters are compatible within thestatistical uncertainties. Figure 2 shows the results of the fit to the B0→ D∗−µ+νµXsamples, projected on the two mass observables. The yields corresponding to the D∗ peakin the (m, δm) distributions are (2.447± 0.007)× 105 and (5.758± 0.010)× 105 in 2011and 2012 data, respectively.

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Figure 1: D− invariant mass distributions for the B0→ D−µ+νµX candidates in (left) 2011and (right) 2012 data. Projections of the fit function are superimposed for (blue line) the fullPDF and its components: (red line) signal D− from B decays and (green line) combinatorialbackground. The corresponding distributions of the normalised residuals of data with respect tothe fit (pulls) are shown below each plot.

The fraction of B+ background in data, fB+ , is determined with good precision byfitting the distribution of the BDT classifier, where templates for signal and B+ backgroundare obtained from simulation. Fits are performed separately in tagging categories for 2011and 2012 data, giving fractions of B+ of 6% and 3% on average for the B0→ D−µ+νµXand the B0→ D∗−µ+νµX mode, respectively, with variation of the order of 10% betweensamples. The result of the fits on 2012 data for both modes is given in Figure 8 in theAppendix. Systematic uncertainties of 0.5% and 0.4% are assigned on the B+ fractionsfor B0→ D−µ+νµX and B0→ D∗−µ+νµX, respectively, which are due to the knowledgeof the exclusive decays used to build the simulation templates. In the decay time fit, the

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Figure 2: Distributions of (top) mKπ and (bottom) δm for B0→ D∗−µ+νµX candidates in (left)2011 and (right) 2012 data. Projections of the fit function are superimposed for (blue line) thefull PDF and its components: (red line) signal D∗− from B decays, (black dashed line) D0 fromB and (green line) combinatorial backgrounds. The corresponding distributions of the normalisedresiduals of data with respect to the fit (pulls) are shown below each plot.

B+ fractions are kept fixed. The statistical and systematical uncertainties on fB+ lead toa systematic uncertainty on ∆md, which will be reported in Sect. 5.

The oscillation frequency ∆md is determined from a binned maximum likelihood fitto the distribution of the B0 decay time t of candidates classified as mixed (q = −1) orunmixed (q = 1) according to the flavour of the B meson at production and decay time.

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The total probability distribution function for the fit is given by:

P(t, q) = S(t, q) + fB+B+(t, q) , (3)

where the time distribution for signal and background are given by

S(t, q) = N e−Γdt(1 + q (1− 2ωsig) cos ∆mdt) , (4)

B+(t, q) = NB+e−Γut

(1 + q

2− qωB+

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where N and NB+ are normalisation factors, Γd and Γu = 1/τB+ are kept fixed in thefit, with τB+ being the lifetime of the B+ meson. The mistag fractions for signal and B+

components, ωsig and ωB+ , vary freely in the fit. To account for the time resolution, bothdistributions in Eq. 4 are convolved with an appropriate resolution model that takes intoaccount uncertainties on both the decay length and the momentum. The distributionsused in the fit are therefore obtained by a double convolution. The contribution accountingfor the decay length resolution is described by a triple Gaussian function with an effectivewidth corresponding to a time resolution of 75 fs, as determined from simulated events.The contribution accounting for the uncertainty on the momentum is described by thedistribution of the corrected k-factor prec/(k · ptrue), obtained from the simulation. Thissecond convolution is dominant above 1.5 ps. Finally, the PDF P is multiplied by anacceptance function a(t) to account for the effect of the trigger and offline selections andreconstruction. In the B0→ D−µ+νµX mode, the acceptance function is obtained bydividing the proper time distribution, obtained on data after applying the signal sWeights,with the distribution expected for B0 decays. The latter is given by convoluting theexponential decay distribution, generated with the known B0 lifetime, with the resolutionmodel defined above. For the B0→ D∗−µ+νµX mode the acceptance is described by asum of cubic spline polynomials [26]. Spline coefficients are determined directly from thetagged time-dependent fits on data, where the B0 and B+ lifetimes are fixed to their worldaverages [4].

The fitting strategy has been validated on simulated data. In particular, a bias isobserved on the ∆md value, due to a correlation between the decay time and its resolution,which is not taken into account when parameterizing the signal shape. Simulation showsthat this dependence is introduced by the requirements of the software trigger and offlineselection on the impact parameters of D− and D0 with respect to the primary vertex.Values for this bias, of up to 4 ns−1 with a 10% uncertainty, are determined per modeand per year by fitting the true and corrected time distributions and taking the differencebetween the resulting values of ∆md. The uncertainty on the bias results in a systematicuncertainty on ∆md.

The values of ∆md, obtained from the time-dependent fit and corrected for the fitbias, are reported in Table 1. Systematical uncertainties are discussed below. Thefour independent ∆md determinations are compatible within statistical uncertainties.Figure 3 shows the fit projections for the decay time distributions for the candidatesin the category with lowest mistag in 2012 data. The time-dependent asymmetry for

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Figure 3: Decay time distributions for (left) B0→ D−µ+νµX and (right) B0→ D∗−µ+νµX inthe category with lowest mistag in 2012 data. The corresponding distributions of the normalisedresiduals of data with respect to the fit (pulls) are shown below each plot.

both B0→ D−µ+νµX and B0→ D∗−µ+νµX modes in 2011 and 2012 data are shownin Figures 4 and 5, respectively. Fits are performed in subsamples of different trackmultiplicity, number of primary vertices, magnet polarity, run periods, and muon charges.Statistically compatible results are obtained in all cases. A combination of the two ∆md

determinations, including systematic uncertainties, is given in Section 6.

Table 1: Results of ∆md measured in each mode for 2011 and 2012 data separately, for the totalsample, and for the combination of the two modes. The quoted uncertainties are statistical (stat)and total systematic (syst) uncertainties, respectively.

Mode 2011 sample 2012 sample Total sample∆md [ ns−1 ] ∆md [ ns−1 ] ∆md [ ns−1 ]

B0→ D−µ+νµX 504.7± 4.9stat 503.2± 2.9stat 503.6± 2.5stat ± 1.4syst

B0→ D∗−µ+νµX 496.2± 5.9stat 506.9± 3.9stat 503.6± 3.2stat ± 1.4syst

combination 503.6± 2.0stat ± 1.3syst

5 Systematic uncertainties

Several sources of systematic uncertainties have been considered. The contribution of eachsource has been evaluated by using a large number of parameterized simulations, andestimating the deviation between the default and the results obtained when repeating thefits after having adjusted the inputs to those corresponding to the systematic variation

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under test. Systematic uncertainties, grouped by type and by their possible correlationacross the two channels, are summarized in Table 2.

5.1 B+ background

The fraction of B+ background is estimated from data with a very small statisticaluncertainty. A variation of the branching fractions of semileptonic B0 decays resulting in aD∗− or D− in the final state within their uncertainties gives systematic uncertainties on theB+ fractions of 0.5% and 0.4% for the B0→ D−µ+νµX and B0→ D∗−µ+νµX, respectively.The resulting uncertainty on ∆md is 0.1 ns−1 in B0 → D−µ+νµX and negligible forB0→ D∗−µ+νµX. In the default fit, assumptions are made for the time acceptance of theB0 and the B+ components. For the B0→ D−µ+νµX mode, an uncertainty of 0.4 ns−1 on∆md is obtained when reweighting the default time acceptance by the ratio of the B+ andB0 signal acceptances determined on simulation. For the B0→ D∗−µ+νµX channel, a shiftof 0.8 ns−1 on ∆md is observed when the B+ and B0 samples, generated with differentacceptances, are fitted with the same time acceptance. The above systematic uncertaintiesare considered as uncorrelated between the two channels.

The resolution on the B+ decay length contributes 0.1 ns−1 to ∆md in the B0 →D−µ+νµX channel and negligibly to the B0→ D∗−µ+νµX channel.

5.2 Other backgrounds

The impact of the knowledge of backgrounds due to semileptonic B0s decays with D(∗)− in

the final state has been estimated by varying their contributions within the uncertaintieson their branching fractions. This results in a variation of 0.2 ns−1 on ∆md for theB0→ D∗−µ+νµX. For the B0→ D−µ+νµX, there is an additonal contribution due toB0s → D+

s µν decays, where a kaon in the D+s → K+K−π+ decay is mis-identified as a

pion, which gives an 8% contribution due to D+s peaking under the D+ mass. A difference

in ∆md of 0.5 ns−1 is observed.The Λ0

b → nD∗−µ+ decays has never been seen before. However, due to the similarfinal state, it can be mistaken for B+ background as both backgrounds do not oscillate.Dedicated simulated samples were used to estimate a signal contamination of 0.2% due toΛ0b decays, with a 100% uncertainty. A negligible effect on ∆md from this source is found.

Small contributions from B → D(∗)−D+s X decays, with the D+

s decaying semileptoni-cally give an uncertainty of 0.2 ns−1 on ∆md in the B0→ D−µ+νµX mode, and a negligibleeffect for B0→ D∗−µ+νµX mode.

5.3 k-factor

Two main sources of systematic uncertainties are related to the k-factor. The former, dueto possible differences in the B momentum spectrum between simulation and data, isstudied by comparing the B momentum in B+→ J/ψK+ decays in data and simulation,and subsequently reweighting signal simulation to estimate the effect on the k-factor

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distribution and therefore on ∆md. The systematic uncertainties on ∆md due to thiseffect for B0→ D−µ+νµX and B0→ D∗−µ+νµX are 0.3 ns−1 and 0.5 ns−1, respectively.The latter, related to the uncertainties on the measurements of the branching fractionfor the exclusive modes which are used to build the simulated samples, is evaluated byvarying by one standard deviation the branching fractions of exclusive decays, one ata time, and re-weighting the corresponding k-factor distribution. Uncertainties of 0.4ns−1 and 0.2 ns−1 are assigned for B0→ D−µ+νµX and B0→ D∗−µ+νµX, respectively.The systematic uncertainties due to knowledge of the k-factor correction are consideredcorrelated between the two channels.

The systematic uncertainties on ∆md, due to the finite number of events in thesimulation sample used to compute the k-factor corrections, are 0.3 and 0.4 ns−1 (B0→D−µ+νµX), and 0.3 and 0.2 ns−1 (B0→ D∗−µ+νµX) for the 2011 and 2012 samples,respectively.

5.4 Other systematic sources

In B0→ D−µ+νµX the default fit uses an acceptance histogram obtained from sWeighteddata. Parameterized simulations are generated with the default acceptance histogram fromdata, but fit with an acceptance histogram obtained from simulation, giving a negligibleeffect on ∆md. No systematic uncertainty is assigned to B0→ D∗−µ+νµX decays, sincethe time acceptance is described by spline polynomials, with free parameters in the fit.

Discrepancies between data and simulation on the resolution on the B flight distance,have been evaluated by conservatively scaling the widths of the triple Gaussian functionby a factor 1.5 with respect to the default. Uncertainties of 0.3 ns−1 and 0.5 ns−1 on ∆md

are assigned for the B0→ D−µ+νµX and B0→ D∗−µ+νµX, respectively. Both channelsare affected by the same discrepancy between data and simulation, thus this systematicsource is counted as correlated.

Since all parameters vary freely in the invariant mass fits, the uncertainties due tothe invariant mass model are small. As a cross-check, the fits were repeated by usingthe sWeights determined without splitting the mass fits in tagging categories, giving anegligible variation on ∆md.

Signal and background mistags are free parameters in the fit, therefore no systematicuncertainty associated to them is assigned.

Asymmetries in the production of neutral and charged B mesons, in tagging efficiencyand mistag probabilities, and in the reconstruction of the final state are neglected inthe ∆md fits. Also, the B0 semileptonic CP asymmetry adsl is assumed to be zero. Thesystematic uncertainty on ∆md due to these assumptions were studied by means ofparametrized simulations and found to be negligible.

The bias on ∆md mentioned in Sec. 4 is determined using the simulation. Thedependence of ∆md on possible differences between data and simulation was alreadyconsidered above by varying the composition of the simulation sample used to constructthe k-factor distribution. Since the bias is related to impact parameter cut of the Dmeson with respect to the primary vertex, the fits were repeated with a k-factor histogram

12

Table 2: Sources of systematic uncertainties on ∆md, separated into those that are correlatedand uncorrelated between the two decay channels B0→ D−µ+νµX and B0→ D∗−µ+νµX.

Source of uncertainty B0→ D−µ+νµX [ ns−1 ] B0→ D∗−µ+νµX [ ns−1 ]Uncorrelated Correlated Uncorrelated Correlated

B+ background: 0.4 0.1 0.8 –Other backgrounds: – 0.5 – –k-factor distribution: 0.4 0.5 0.3 0.6Other fit-related: 0.6 0.9 0.2 0.9Total 0.9 1.1 0.9 1.1

obtained with a tighter cut on the impact parameter, and the difference with respectto the default is taken as systematic uncertainty. The systematic uncertainties (0.4 and0.1 ns−1 for B0→ D−µ+νµX and B0→ D∗−µ+νµX, respectively) related to the bias areconsidered as uncorrelated between the channels, as they are determined from differentsimulation samples and the time biasing cuts, responsible for the systematic uncertaintyon the bias, are different between the two channels. Additionaly for the B0→ D∗−µ+νµX,an uncertainty of 0.1 ns−1 is assigned, due to possible differences in the time acceptancebetween data and MC. The uncertainty on B0→ D∗−µ+νµX is therefore 0.2 ns−1.

The knowledge of the length scale of the LHCb experiment is limited by the uncertaintiescoming from the metrology measurements of the silicon-strip vertex detector. It wasevaluated in the context of the ∆ms measurement and found to be 0.022% [27]. Thistranslates in an uncertainty on ∆md of ±0.1 ns−1. The uncertainty on the knowledgeof the momentum scale has been determined studying the masses of various well knownresonances and found to be 0.15% [28]. This uncertainty results in a 0.8 ns−1 uncertaintyon ∆md in both modes.

Effects due to the choice of the binning scheme and fitting ranges are found to benegligible.

6 Conclusion

A combined value of ∆md is obtained as a weighted average of the four measurementsperformed in B0→ D−µ+νµX and B0→ D∗−µ+νµX in the two years. First, the 2011 and2012 results of each decay mode are averaged according to their statistical uncertainties.The combined results are shown in the last column of table 1, where the first andsecond uncertainties are statistical and total systematic, respectively. Then, the resulting∆md values of each mode are averaged according to the combination of the correspondingstatistical and uncorrelated systematic uncertainties. The correlated systematic uncertaintyis added in quadrature to the resulting uncertainty. The combined result is shown inthe last row of table 1, where the first and second uncertainties are statistical and totalsystematic, respectively. A comparison of the present ∆md measurement with previous

13

]-1 [nsdm∆450 500 550

ALEPH (3 analyses) 19± 6 ±446

DELPHI (5 analyses) 11± 18 ±519

L3 (3 analyses) 28± 28 ±444

OPAL (5 analyses) 15± 18 ±479

CDF1 (4 analyses) 27± 33 ±495

D0 (1 analysis) 16± 20 ±506

BABAR (4 analyses) 4± 6 ±506

BELLE (3 analyses) 5± 4 ±509

LHCb (3 analyses) 3± 5 ±514

<0.66) +BABAR (P 0.25 + 0.26 - 0.25±4.15

This measurement 1.3± 2.0 ±503.6

BABAR (p*>1.3GeV) 0.27 + 0.19 - 0.21±4.32

Average (w/o this meas.) 3±510

HFAGSummer 2014

Bosch, Lange, Neubert and Paz (BLNP)Phys.Rev.D72:073006,2005

/dof = 9.2/11 (CL = 61.00 %)2χ

Figure 6: Comparison of the measurement presented in this paper with previous determinationsof the B0 oscillation frequency.

measurements, as well as with the current world average, is shown in Fig. 6.In conclusion, the oscillation frequency in B0–B0 system (∆md) is measured in semilep-

tonic B decays using data collected in 2011 and 2012 at LHCb. The B0→ D−µ+νµXand B0→ D∗−µ+νµX decays are used, where the D mesons are reconstructed in Cabibbo-favoured decays: D−→ K+π−π− and D∗−→ D0π−, with D0→ K+π−. A combined ∆md

measurement is obtained:

∆md = (503.6± 2.0 (stat)± 1.3 (syst)) ns−1 ,

which is compatible with previous LHCb measurements and the world average. This is themost precise single determination of this quantity, with a total uncertainty comparable to

14

the current world average.

Acknowledgements

We express our gratitude to our colleagues in the CERN accelerator departments forthe excellent performance of the LHC. We thank the technical and administrative staffat the LHCb institutes. We acknowledge support from CERN and from the nationalagencies: CAPES, CNPq, FAPERJ and FINEP (Brazil); NSFC (China); CNRS/IN2P3(France); BMBF, DFG, HGF and MPG (Germany); INFN (Italy); FOM and NWO (TheNetherlands); MNiSW and NCN (Poland); MEN/IFA (Romania); MinES and FANO(Russia); MinECo (Spain); SNSF and SER (Switzerland); NASU (Ukraine); STFC (UnitedKingdom); NSF (USA). The Tier1 computing centres are supported by IN2P3 (France),KIT and BMBF (Germany), INFN (Italy), NWO and SURF (The Netherlands), PIC(Spain), GridPP (United Kingdom). We are indebted to the communities behind themultiple open source software packages on which we depend. We are also thankful forthe computing resources and the access to software R&D tools provided by Yandex LLC(Russia). Individual groups or members have received support from EPLANET, MarieSk lodowska-Curie Actions and ERC (European Union), Conseil general de Haute-Savoie,Labex ENIGMASS and OCEVU, Region Auvergne (France), RFBR (Russia), XuntaGaland GENCAT (Spain), Royal Society and Royal Commission for the Exhibition of 1851(United Kingdom).

15

7 Appendix

This appendix contains supplementary material regarding the input variables to theBDT classifier, the fits to the distributions of the BDT classifier on data, the k-factordistributions on simulated data.

7.1 BDT classifier

The variables used as input for the BDT classifier are the following:

• Corrected mass [29], defined as mcorr =√m2B + pT (B)2 + pT (B), where mB is the

visible mass of the B candidate and pT (B) its visible momentum transverse to itsflight direction. The B flight direction is measured using the primary vertex and Bvertex positions.

• Pointing angle between the B momentum and its flight direction.

• Visible mass of the B candidate.

• Impact parameter, IP (π,D), with respect to the decay vertex of the D− (D0), ofthe track with the smallest impact parameter with respect to the B candidate.

• Invariant mass and vertex χ2 of the combination of the D− (D∗−) and the trackwith the smallest χ2-distance with respect to the B candidate.

• Cone isolation I = pT (B)pT (B)+

Pi pT,i

, where the sum is computed on tracks which satisfy√δη2

i + δφ2i < 1, δηi and δφi being the difference in pseudo-rapidity and in polar

angle φ between the track and the B candidate, respectively.

• Track isolation variables, used to discriminate tracks originating from the B vertexfrom those originating from elsewhere:

– Track isolation counters [30], computed for each track in the B decay chain

– an isolation BDT [30], iso(sum), estimated on the B candidate.

– a second isolation BDT, similar to the previous, which exploits a differenttraining strategy and additional variables, computed on tracks originating fromD− (D0) decays, iso(D), those coming from the B decay, iso(B), and all tracksin the decay chain, iso(all).

The TMVA package [31], used to train and test the classifier, ranks the input variablesaccording to their discriminating power between signal and background. Figure 7 showsthe distribution of six most discriminating variables on simulated signal and backgroundsamples.

The fits to the BDT classifier on the 2012 data sample for both modes, performedon the four tagging categories, are shown in Fig. 8. To suppress the background due to

16

iso(D)-0.5 0 0.5 1

Ent

ries

(ar

b. u

nits

)Signal

Background

iso(all)-0.5 0 0.5 1

LHCb preliminary

iso(B)-0.5 0 0.5 1

iso(sum)-3 -2 -1 0

Ent

ries

(ar

b. u

nits

)

]2c [MeV/corrm4000 6000 8000 10000

) [mm]D, πIP(5 10

Figure 7: Distributions of the six most discriminating variables used as inputs for training the BDTclassifier. Blue and red histograms represent B0→ D∗−µ+νµX signal and B+→ D∗−µ+νµXbackground, respectively, as obtained on a sample of simulated events.

B+→ D−µ+νµX and B+→ D∗−µ+νµX decays, only the events with the value of the BDTclassifies larger than −0.12 (−0.16) and −0.3 (−0.3) are selected for B0→ D−µ+νµX andB0→ D∗−µ+νµX in 2011 (2012) samples, respectively.

7.2 Distributions of k-factor on signal events

Figure 9 shows distributions of the k-factor as a function of the invariant mass of theD(∗)−µ+ system, as obtained on samples of signal events. In each plot, the average k-factorand the result of a polynomial fit are also shown.

17

-1 -0.5 0 0.5 10

5

10

15

20

310×LHCb preliminary

(a)

-1 -0.5 0 0.5 10

50

100310×

(c)DataTotal fitSignalBackground

-1 -0.5 0 0.5 10

5

10

15

20

310×

(b)

-1 -0.5 0 0.5 10

50

100310×

(d)

/ 0.0

333

10

×E

vent

s

BDT output

-1 -0.5 0 0.5 10

5

10

310×LHCb preliminary

(a)

-1 -0.5 0 0.5 10

5

10

15

20

310×

(c)

-1 -0.5 0 0.5 10

5

10

310×

(b)

-1 -0.5 0 0.5 10

5

10

15

20

310×

(d)

/ 0.0

53

10

×E

vent

s

BDT output

Figure 8: Fits to the output of the B+ veto BDT for (top four plots) B0→ D−µ+νµX and(bottom four plots) B0→ D∗−µ+νµX in 2012 data, for each tagging category. The filled redhistogram, the dashed green line, and the continuous blue line correspond to background, signal,and total templates, respectively. 18

]2c mass [MeV/dB3500 4000 4500 5000

-fac

tor

k

0.30.40.50.60.70.80.9

11.11.2 )2 c

Eve

nts/

(0.0

16)/

(23

MeV

/

0102030405060708090

LHCb preliminary

]2c mass [MeV/dB3500 4000 4500 5000

-fac

tor

k

0.30.40.50.60.70.80.9

11.11.2 )2 c

Eve

nts/

(0.0

04)/

(11

MeV

/

0

5

10

15

20

25

30

35LHCb preliminary

Figure 9: The k-factor distribution and the average k-factor (black points) as function ofthe D(∗)−µ+ invariant mass, on samples of simulated (top) B0 → D−µ+νµX and (bottom)B0→ D∗−µ+νµX decays. Polynomial fits to the average k-factor as function of the B mass arealso shown in red.

19

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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,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. Contu15,38, 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. Deleage4, 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 Suarez37,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. Farber38, 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. Gallorini22,38, S. Gambetta50,M. Gandelman2, P. Gandini55, Y. Gao3, J. Garcıa Pardinas37, J. Garra Tico47, L. Garrido36,D. Gascon36, C. Gaspar38, R. Gauld55, L. Gavardi9, G. Gazzoni5, A. Geraci21,u, D. Gerick11,E. Gersabeck11, M. Gersabeck54, T. Gershon48, Ph. Ghez4, A. Gianelle22, S. Gianı39,V. Gibson47, O. G. Girard39, L. Giubega29, V.V. Gligorov38, C. Gobel60, D. Golubkov31,A. Golutvin53,31,38, A. Gomes1,a, C. Gotti20,j , M. Grabalosa Gandara5, R. Graciani Diaz36,L.A. Granado Cardoso38, E. Grauges36, E. Graverini40, G. Graziani17, A. Grecu29,E. Greening55, S. Gregson47, P. Griffith45, L. Grillo11, O. Grunberg63, B. Gui59, E. Gushchin33,Yu. Guz35,38, T. Gys38, T. Hadavizadeh55, C. Hadjivasiliou59, G. Haefeli39, C. Haen38,

23

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, J.A. Hernando Morata37, E. van Herwijnen38, M. Heß63, A. Hicheur2, 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. 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. Lefevre5,A. Leflat32,38, J. Lefrancois7, 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, N. Lusardi21, 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,K. Matthieu11, A. Mauri40, B. Maurin39, A. Mazurov45, M. McCann53, J. McCarthy45,A. McNab54, R. McNulty12, B. Meadows57, F. Meier9, M. Meissner11, D. Melnychuk28,M. Merk41, D.A. Milanes62, M.-N. Minard4, D.S. Mitzel11, J. Molina Rodriguez60,I.A. Monroy62, S. Monteil5, M. Morandin22, P. Morawski27, A. Morda6, M.J. Morello23,s,J. Moron27, A.B. Morris50, R. Mountain59, F. Muheim50, J. Muller9, K. Muller40, V. Muller9,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. Pilar48, 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,

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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, 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,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. Vazquez Sierra37, S. Vecchi16,J.J. Velthuis46, M. Veltri17,g, G. Veneziano39, M. Vesterinen11, B. Viaud7, D. Vieira2,M. Vieites Diaz37, X. Vilasis-Cardona36,o, 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. Zhong3, S. Zucchelli14.

1Centro Brasileiro de Pesquisas Fısicas (CBPF), Rio de Janeiro, Brazil2Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil3Center for High Energy Physics, Tsinghua University, Beijing, China4LAPP, Universite Savoie Mont-Blanc, CNRS/IN2P3, Annecy-Le-Vieux, France5Clermont Universite, Universite Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand, France6CPPM, Aix-Marseille Universite, CNRS/IN2P3, Marseille, France7LAL, Universite Paris-Sud, CNRS/IN2P3, Orsay, France8LPNHE, Universite Pierre et Marie Curie, Universite Paris Diderot, CNRS/IN2P3, Paris, France9Fakultat Physik, Technische Universitat Dortmund, Dortmund, Germany10Max-Planck-Institut fur Kernphysik (MPIK), Heidelberg, Germany11Physikalisches Institut, Ruprecht-Karls-Universitat Heidelberg, Heidelberg, Germany12School of Physics, University College Dublin, Dublin, Ireland13Sezione INFN di Bari, Bari, Italy14Sezione INFN di Bologna, Bologna, Italy15Sezione INFN di Cagliari, Cagliari, Italy16Sezione INFN di Ferrara, Ferrara, Italy17Sezione INFN di Firenze, Firenze, Italy

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18Laboratori Nazionali dell’INFN di Frascati, Frascati, Italy19Sezione INFN di Genova, Genova, Italy20Sezione INFN di Milano Bicocca, Milano, Italy21Sezione INFN di Milano, Milano, Italy22Sezione INFN di Padova, Padova, Italy23Sezione INFN di Pisa, Pisa, Italy24Sezione INFN di Roma Tor Vergata, Roma, Italy25Sezione INFN di Roma La Sapienza, Roma, Italy26Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland27AGH - University of Science and Technology, Faculty of Physics and Applied Computer Science,Krakow, Poland28National Center for Nuclear Research (NCBJ), Warsaw, Poland29Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania30Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia31Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia32Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia33Institute for Nuclear Research of the Russian Academy of Sciences (INR RAN), Moscow, Russia34Budker Institute of Nuclear Physics (SB RAS) and Novosibirsk State University, Novosibirsk, Russia35Institute for High Energy Physics (IHEP), Protvino, Russia36Universitat de Barcelona, Barcelona, Spain37Universidad de Santiago de Compostela, Santiago de Compostela, Spain38European Organization for Nuclear Research (CERN), Geneva, Switzerland39Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland40Physik-Institut, Universitat Zurich, Zurich, Switzerland41Nikhef National Institute for Subatomic Physics, Amsterdam, The Netherlands42Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam, TheNetherlands43NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine44Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine45University of Birmingham, Birmingham, United Kingdom46H.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom47Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom48Department of Physics, University of Warwick, Coventry, United Kingdom49STFC Rutherford Appleton Laboratory, Didcot, United Kingdom50School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom51School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom52Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom53Imperial College London, London, United Kingdom54School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom55Department of Physics, University of Oxford, Oxford, United Kingdom56Massachusetts Institute of Technology, Cambridge, MA, United States57University of Cincinnati, Cincinnati, OH, United States58University of Maryland, College Park, MD, United States59Syracuse University, Syracuse, NY, United States60Pontifıcia Universidade Catolica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to 2

61Institute of Particle Physics, Central China Normal University, Wuhan, Hubei, China, associated to 3

62Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia, associated to 8

63Institut fur Physik, Universitat Rostock, Rostock, Germany, associated to 11

64National Research Centre Kurchatov Institute, Moscow, Russia, associated to 31

65Yandex School of Data Analysis, Moscow, Russia, associated to 31

66Instituto de Fisica Corpuscular (IFIC), Universitat de Valencia-CSIC, Valencia, Spain, associated to 36

67Van Swinderen Institute, University of Groningen, Groningen, The Netherlands, associated to 41

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aUniversidade Federal do Triangulo Mineiro (UFTM), Uberaba-MG, BrazilbP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, RussiacUniversita di Bari, Bari, ItalydUniversita di Bologna, Bologna, ItalyeUniversita di Cagliari, Cagliari, Italyf Universita di Ferrara, Ferrara, ItalygUniversita di Urbino, Urbino, ItalyhUniversita di Modena e Reggio Emilia, Modena, ItalyiUniversita di Genova, Genova, ItalyjUniversita di Milano Bicocca, Milano, ItalykUniversita di Roma Tor Vergata, Roma, ItalylUniversita di Roma La Sapienza, Roma, ItalymUniversita della Basilicata, Potenza, ItalynAGH - University of Science and Technology, Faculty of Computer Science, Electronics andTelecommunications, Krakow, PolandoLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, SpainpHanoi University of Science, Hanoi, Viet NamqUniversita di Padova, Padova, ItalyrUniversita di Pisa, Pisa, ItalysScuola Normale Superiore, Pisa, ItalytUniversita degli Studi di Milano, Milano, ItalyuPolitecnico di Milano, Milano, Italy

†Deceased

27