Measurement of the time-integrated CP asymmetry in D0 → K0SK0S decays

JHEP11(2018)048 Published for SISSA by Springer Received:June 6, 2018 Revised:September 21, 2018 Accepted:October 20, 2018 Published:November 8, 2018 Measurement of the time-integrated CP asymmetry in D0→K0 SK0 Sdecays The LHCb collaboration E-mail: [email protected] Abstract: A measurement of the time-integrated CP asymmetry in D0→K0 SK0 Sdecays is reported. The data correspond to an integrated luminosity of about 2 fb−1collected in 2015–2016 by the LHCb collaboration in pp collisions at a centre-of-mass energy of 13 TeV. The D0candidate is required to originate from a D∗+→D0π+decay, allowing the determination of the flavour of the D0meson using the pion charge. The D0→K+K− decay, which has a well measured CP asymmetry, is used as a calibration channel. The CP asymmetry for D0→K0 SK0 Sis measured to be ACP (D0→K0 SK0 S) = (4.3±3.4±1.0)%, where the first uncertainty is statistical and the second is systematic. This result is combined with the previous LHCb measurement at lower centre-of-mass energies to obtain ACP (D0→K0 SK0 S) = (2.3±2.8±0.9)%. Keywords: Charm physics, CP violation, Flavor physics, Hadron-Hadron scattering (experiments) ArXiv ePrint: 1806.01642 Open Access, Copyright CERN, for the benefit of the LHCb Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP11(2018)048 JHEP11(2018)048 Contents 1 Introduction 1 2 LHCb detector 3 3 Event selection 3 4 Asymmetry measurement 6 5 Systematic uncertainties 8 6 Results 10 The LHCb collaboration 14 1 Introduction In the Standard Model, violation of charge-parity (CP) symmetry originates from the presence of a single phase in the Cabibbo-Kobayashi-Maskawa (CKM) matrix [1]. Experimental results support the CKM mechanism for CP violation, but additional sources of CP violation are needed to explain cosmological observations of the relative abundance of matter and antimatter in the universe [2]. In the charm sector, CP violation has not yet been observed, but measurements of CP asymmetries in Cabibbo-suppressed D0→h+h−decays (h=π, K) have reached 0.2% and 0.03% precision for time-integrated [3] and indirect CP asymmetries [4], respectively. The D0→K0 SK0 Sdecay is a promising discovery channel for CP violation in charm decays [5]. Only loop-suppressed amplitudes and exchange diagrams that vanish in the SU(3) flavour limit contribute to this decay. These amplitudes can have different strong and weak phases and are of similar size. The time-integrated CP asymmetry, ACP , in D0→K0 SK0 Sdecays may therefore be enhanced to an observable level [6], and could be as large as 1.1% [5]. Examples of such diagrams are shown in figure 1. The most precise measurement of this asymmetry to date, ACP (K0 SK0 S)=(−0.02 ±1.53 ±0.17)%, has been performed by the Belle collaboration [7]. Earlier measurements were also performed by the LHCb [8] and CLEO [9] collaborations. This article reports a new measurement of ACP in the decay D0→K0 SK0 Susing LHCb data collected in 2015 and 2016. The measurement of the CP asymmetry, defined as ACP (K0 SK0 S)≡Γ(D0→K0 SK0 S)−Γ(D0→K0 SK0 S) Γ(D0→K0 SK0 S) + Γ(D0→K0 SK0 S),(1.1) – 1 – JHEP11(2018)048 ¯u c s ¯ d d ¯s ¯u c s ¯ d d ¯s Figure 1. Exchange (left) and penguin annihilation (right) diagrams contributing to the D0→K0 SK0 Samplitude. Based on ref. [5]. requires knowledge of the flavour of the D0meson at production. A sample of flavour-tagged D0→K0 SK0 Sdecays is obtained by selecting D∗+mesons that are produced in the primary interaction (hereafter referred to as prompt), with the subsequent decay D∗+→D0π+.1 The charge of the pion in this decay identifies the flavour of the accompanying D0meson. The effect of D0−D0mixing [10] is negligible compared to the precision of this analysis and is not considered further. The experimentally measured quantity is the raw asymmetry, defined as Araw ≡ND0−ND0 ND0+ND0 ,(1.2) where ND0is the measured yield of D∗+→D0π+,D0→K0 SK0 Sdecays and ND0is the measured yield of D∗− →D0π−,D0→K0 SK0 Sdecays. This observable is related to the CP asymmetry by the expression, valid for small asymmetries, Araw ≈ ACP +Aprod +Adet,(1.3) where Aprod is the D∗± production asymmetry, defined as Aprod ≡σ(D∗+)−σ(D∗−) σ(D∗+)+σ(D∗−), and Adet is the π± tag detection asymmetry, defined as Adet ≡(π+ tag)−(π− tag) (π+ tag)+(π− tag). The symbol π± tag refers to the pion in the D∗± decay. To a very good approximation, knowledge of Adet and Aprod is unnecessary when using a calibration channel with the same production and tagging mechanism. The decay channel D0→K+K−is used for this purpose. The production and detection asymmetries cancel when taking the difference of the raw asymmetries: ∆ACP ≡ Araw(K0 SK0 S)−Araw(K+K−) (1.4) =ACP (K0 SK0 S)−ACP (K+K−).(1.5) The quantity ACP (K+K−) has been measured with a precision of 0.2% [3], thus allowing the determination of ACP (K0 SK0 S). 1The inclusion of charge-conjugate processes is implied throughout this document, unless explicitly specified. – 2 – JHEP11(2018)048 2 LHCb detector The LHCb detector [11,12] is a single-arm forward spectrometer covering the pseudorapidity range 2 < η < 5, designed for the study of particles containing bor c quarks. 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 (TT) 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 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 (PV), the impact parameter (IP), is measured with a resolution of (15 + 29/pT)µm, where pTis the component of the momentum transverse to the beam, in GeV/c. Different types of charged hadrons are distinguished using information from two ring-imaging Cherenkov (RICH) detectors. Photons, electrons and hadrons 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. The magnetic field deflects oppositely-charged particles in opposite directions and this can lead to detection asymmetries. Periodically reversing the magnetic field polarity throughout the data taking almost cancels the effect. The configuration with the magnetic field pointing upwards (downwards), MagUp (MagDown), bends positively (negatively) charged particles in the horizontal plane towards the centre of the LHC ring. 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 applies a full event reconstruction. At the hardware trigger stage, events are required to have a muon with high pTor a hadron, photon or electron with high transverse-energy deposit in the calorimeters. Simulated events are used at various phases of the analysis. In the simulation, pp collisions are generated using Pythia [13,14] with a specific LHCb configuration [15]. Decays of hadronic particles are described by EvtGen [16], in which final-state radiation is generated using Photos [17]. The interaction of the generated particles with the detector, and its response, are implemented using the Geant4 toolkit [18,19] as described in ref. [20]. 3 Event selection The 2015 and 2016 data samples collected in pp collisions at 13 TeV, which correspond to about 2 fb−1of integrated luminosity, are used in this analysis. Candidates are reconstructed in the decay D∗+→D0π+, followed by D0→K0 SK0 Sand then K0 S→π+π−. The hardware trigger decision is required to be based either on the transverse energy deposited in the hadronic calorimeter by a charged particle from the decay of the D0meson, or on signatures not associated with the D∗+decay, such as a high-pTmuon, or a high transverse-energy deposit in the electromagnetic or hadronic calorimeters. The first stage of the software trigger selects a sample with enhanced heavy-flavour content by requiring – 3 – JHEP11(2018)048 the presence of a large IP, high-pTcharged particle. In the second stage of the software trigger, each selected event is required to contain at least one fully-reconstructed candidate for the D∗+→D0π+,D0→K0 SK0 Sdecay. The decays K0 S→π+π−are reconstructed in two different categories: the first involving K0 Smesons that decay early enough for the decay products to be reconstructed in the vertex detector; and the second containing K0 Scandidates that decay outside the acceptance of the vertex detector, but within the TT acceptance. These categories are referred to as long and downstream, respectively. The long category has better mass, momentum and decay-vertex resolution than the downstream category. In this analysis at least one K0 Sin each D0decay is required to be of the long type. There are therefore two subsamples used: one where both K0 Scandidates are long and the other where one is long and the other is downstream. These are referred to as the LL and LD subsamples, and are analysed separately, since they exhibit different resolutions. One or more of the charged decay products from a long K0 S meson is required to activate the first stage of the software trigger. The pion candidates used in the K0 Sreconstruction are required to be high-quality tracks, using the χ2/ndf of the track fit and the output Pfake of a multivariate classifier, trained to identify fake tracks, that combines information from the particle identification and tracking systems. To ensure that pion candidates do not originate from the PV, they are required to satisfy χ2 IP >36. The quantity χ2 IP for a given particle is defined as the difference in the vertex fit χ2of the PV associated to the particle, reconstructed with and without the particle being considered. For downstream K0 Scandidates, the pions are required to satisfy p > 3 GeV/c and pT>175 MeV/c. Two oppositely charged pions are used to form K0 Scandidates. The vertex fit is required to satisfy χ2<30 and the χ2 IP is required to be greater than 9 (4) for long (downstream) K0 Scandidates. Furthermore, long (downstream) K0 Scandidates are required to satisfy pT>500 (750) MeV/c. Two reconstructed K0 Scandidates are paired to form D0candidates, requiring χ2<10 for the vertex fit. The sum of the pTof the K0 Scandidates is required to exceed 1500 (2000) MeV/c for LL (LD) candidates. The angle between the D0momentum and the vector connecting the PV to the D0decay vertex is required to be less than 34.6 mrad. The measured decay time of the D0meson is required to be greater than 0.2 ps. Finally, the D0mass is required to be within 20 MeV/c2of the known value [10]. A pion candidate (π+ tag) is added to a reconstructed D0meson to form a D∗+candidate, with a D∗+vertex fit which is required to have χ2<25. The π+ tag candidate is required to have pT>100 MeV/c, and to pass through regions of the detector that are known to have a small detector asymmetry [8]. A small fraction of π± tag candidates are reconstructed with the wrong charge assignment, and are removed by a selection on track quality. An important source of background is due to the presence of D0→K0 Sπ+π−decays, where the π+π−pair satisfies the K0 Sselection. In principle, the contribution of this channel can be substantial, due to its large branching fraction, but it is effectively reduced by placing a requirement on the K0 Sflight distance (FD) and on the mass of the K0 S candidates. The quantity χ2 FD is the square of the measured K0 Sflight distance divided by the square of its uncertainty. Figure 2shows a two-dimensional plot of the value of – 4 – JHEP11(2018)048 Figure 2. Two-dimensional distribution of the logarithm of the K0 Sflight distance significance (log χ2 FD) for the two K0 Scandidates in the LL subsample of D0→K0 SK0 Sdecays. The D0→K0 SK0 S signal can be observed in the upper right region of the plot. The contour corresponds to eq. (3.1). the quantity log χ2 FD for K0 Spairs in the LL sample. In the figure, four separate regions are visible. The upper right part of the plot, where both K0 Scandidates have significant flight distances, is the D0→K0 SK0 Ssignal, while the upper left and lower right regions correspond to D0→K0 Sπ+π−decays. The lower left is populated by D0→π+π−π+π− decays and combinatorial background. A requirement on χ2 FD is only necessary for long K0 Scandidates, since downstream K0 Scandidates decay far from the PV by construction. For the LL subsample the requirement on the two K0 Scandidates (K0 S1and K0 S2) is [log χ2 FD(K0 S1)−10]2+ [log χ2 FD(K0 S2)−10]2<16,(3.1) while for the LD sample log χ2 FD(K0 SL)>2.5 is imposed on the long K0 Scandidate. The K0 Smass requirements are q[m(K0 S1)−mK0]2+ [m(K0 S2)−mK0]2<10.5 MeV/c2,(3.2) for LL candidates, with mK0= 497.6 MeV/c2[10], and sm(K0 SL)−mK0 10.5 MeV/c22 +m(K0 SD)−mK0 15 MeV/c22 <1,(3.3) for LD candidates. This selection takes into account the difference in resolution between m(K0 SL) and m(K0 SD). The log χ2 FD(K0 S) and m(K0 S) regions corresponding to signal and peaking-background candidates are identified using simulations. They are further optimised on charge-integrated data by minimising the expected statistical uncertainty on Araw. Events in which the D∗+meson is not produced in the primary interaction, but instead is the product of a b-hadron decay, are characterised by a different production asymmetry and are treated as background. These so-called secondary D∗+candidates tend to have – 5 – JHEP11(2018)048 larger values of χ2 IP(D0) than prompt D∗+candidates and are suppressed by requiring log χ2 IP(D0)<3.0 (3.5) for the LL (LD) subsample. The requirement log χ2 IP(π+ tag)<2.5 is imposed on both subsamples. Simulated events are used to estimate the residual secondary fraction in the LL and LD subsamples to be 9% and 13%, respectively. A multivariate classifier, based on the k-nearest neighbours (kNN) algorithm [21], is used to further suppress combinatorial background. The kNN algorithm classifies events according to the fraction of signal events among its knearest neighbours (taken from the training sample of signal and background events), where the distance is calculated in the n-dimensional space of the input variables and kis a positive integer. The training sample uses simulated events for the signal and data events from the D0mass sidebands for the background. A wide range of input variables based on track and vertex quality, the transverse momenta of K0 Sand D0candidates, helicity angles of the K0 Sand D0decays and particle identification information on the pions in the D0decays was initially considered. Variables depending on the π± tag track are not included in the classifier to avoid introducing possible bias on the asymmetry measurement. The actual variables used, the value of k, and the selection on the classifier output are optimised separately for the LL and LD subsamples, using the expected statistical uncertainty on the raw asymmetry as a figure of merit. For the D0→K+K−control channel, an attempt is made to keep the selection similar to the D0→K0 SK0 Schannel, although some selections made at the software trigger level are different for the two channels. Charged tracks positively identified as kaons in the RICH detectors are selected to reconstruct D0candidates. The kaons are required to satisfy χ2 IP >4. For the D0candidates, at least one of the kaons is required to have pT>1 GeV/c. The sum of the kaon momenta is required to exceed 5 GeV/c and the D0 pTis required to be at least 1 GeV/c. Furthermore, the angle between the D0momentum vector and the vector connecting the primary and decay vertices is required to be less than 17.3 mrad. The following selections are the same as for the D0→K0 SK0 Schannel: π± tag fiducial cuts, fake-track probability and χ2 IP selection; and requirements on D0χ2 IP and invariant mass. 4 Asymmetry measurement The raw asymmetry for D0→K0 SK0 Sis determined by separating the selected candidates into subsets tagged by positively and negatively charged pions. A simultaneous unbinned maximum likelihood fit to their ∆mdistributions is performed, where ∆mis the difference of the reconstructed invariant mass of the D∗+and the D0candidates. The calculation of ∆mis made after the full decay chain has been reconstructed using a mass constraint on the K0 Scandidates and constraining the D∗+candidate to originate from the PV. The signal shape is modelled using the Johnson SUdistribution [22], which consists of a core Gaussian-like shape but allows for an asymmetric tail S(x;µ, σ, δ, γ)∝"1 + x−µ σ2#−1 2 ×exp (−1 2γ+δsinh−1x−µ σ2).(4.1) – 6 – JHEP11(2018)048 Araw sig nsig Araw bkg Purity Pfit(%) Nobs LL MagUp 0.008 ±0.057 346 ±21 −0.097 ±0.069 0.92 48 589 LL MagDown 0.103 ±0.052 413 ±24 −0.098 ±0.068 0.92 43 675 LD MagUp −0.046 ±0.102 156 ±18 −0.021 ±0.044 0.67 93 758 LD MagDown −0.078 ±0.107 152 ±19 −0.040 ±0.038 0.60 14 950 Table 1. Fit results on the D0→K0 SK0 SLL and LD samples for each magnet polarity, where Nobs represents the number of candidates fitted. The purity is determined in the range 144.5<∆m < 146.5 MeV/c2. For each sample, a χ2test statistic for the fitted model and binned data for positively and negatively charged candidates is constructed. The quantity Pfit is the probability of observing a χ2value greater than that observed in the fit to real data, determined using simulated pseudoexperiments sampled from the fitted model. The background shape is described with an exponential function multiplied by a threshold factor and is zero below a fixed endpoint, which is set to the pion mass mπ B(x;mπ, χ)∝√x−mπ×exp χx mπ.(4.2) The likelihood function is parametrised in terms of ACP and the expected total number of events Nexp =nsig +nbkg L=e−Nexp Nobs!Y insig 1 + qiAraw sig 2S(∆m) + nbkg 1 + qiAraw bkg 2Bqi(∆m),(4.3) where nsig and nbkg are the signal and background yields, respectively, and the parameter qi=±1 is the charge of the D∗± candidate and Nobs is the total number of candidates. The signal raw asymmetry Araw sig is a free parameter in the fit. The free parameter Araw bkg allows for a possible asymmetry in the combinatorial background. The four parameters in eq. (4.1) defining the signal probability distribution function (PDF) are common to the D∗+and D∗− samples, while the parameter describing the background shape is allowed to differ between the two subsamples. For the LL sample, there are ten free parameters. To achieve convergence of the fit in the smaller LD sample, it is necessary to fix the two parameters that describe the asymmetric tail in the signal PDF to the values obtained from the charge-integrated LL subsample. Based on studies of simulated events, the tail parameters of the LL and LD subsamples are expected to be compatible. Separate fits are performed for the two magnet polarities. Table 1shows the results of the simultaneous fits to the D0→K0 SK0 Scandidates. The results on each subset of the data are compatible with each other. The fit is shown in figure 3for the samples collected with the MagUp magnetic field configuration. For the D0→K+K−channel, binned χ2fits are performed to the ∆mdistributions of the positively and negatively tagged D0decays. The sample consists of 8.25 ×105selected candidates for the MagDown magnet polarity and 5.61 ×105candidates for the MagUp magnet polarity. The signal is modelled with a Johnson SUdistribution plus a Gaussian distribution, while the background shape is described by a fourth-degree polynomial multiplied by a √∆m−mπthreshold factor. There are 12 free parameters, and 150 bins, – 7 – JHEP11(2018)048 ] 2 c/V [Mem∆ 140 142 144 146 148 150 152 154 ) 2 c/VCandidates / ( 0.3 Me 10 20 30 40 50 60 70 80 90 LHCb S 0 K S 0 K→ 0 D LL Data Total Bkg (a) ] 2 c/V [Mem∆ 140 142 144 146 148 150 152 154 ) 2 c/VCandidates / ( 0.3 Me 10 20 30 40 50 60 70 80 90 LHCb S 0 K S 0 K→ 0 D LL Data Total Bkg (b) ] 2 c/V [Mem∆ 140 142 144 146 148 150 152 154 ) 2 c/VCandidates / ( 0.3 Me 5 10 15 20 25 30 35 40 LHCb S 0 K S 0 K→ 0 D LD Data Total Bkg (c) ] 2 c/V [Mem∆ 140 142 144 146 148 150 152 154 ) 2 c/VCandidates / ( 0.3 Me 5 10 15 20 25 30 35 40 LHCb S 0 K S 0 K→ 0 D LD Data Total Bkg (d) Figure 3. Results of fits to ∆mdistributions of D0→K0 SK0 Scandidates for MagUp magnet polarity. The fit to (a) D∗+→D0π+and (b) D∗− →D0π−candidates for the LL sample and the fit to (c) D∗+→D0π+and (d) D∗− →D0π−candidates for the LD sample are shown. The black crosses represent the data points, the solid blue curve is the total fit function, and the dashed blue curve is the background component of the fit. in each ∆mfit. The χ2probabilities associated to the fits are 28% (20%) for the negatively (positively) tagged D0decays, and 23% (3%) for the negatively (positively) tagged D0decays, in the MagUp and MagDown magnet polarities, respectively. Figure 4shows the results for the MagUp magnet polarity fit. The results obtained for the two magnet polarities are Araw(K+K−)MagUp =−0.0188 ±0.0020,(4.4) Araw(K+K−)MagDown = 0.0030 ±0.0017, where the uncertainties are statistical. The difference in the MagUp and MagDown values of Araw(K+K−) is an indication of a significant π± tag detection asymmetry, which depends on the magnetic field orientation. 5 Systematic uncertainties The main source of systematic uncertainty arises from the determination of Araw on the D0→K0 SK0 Ssample. Possible bias in the fitting procedure is evaluated using simulated pseudoexperiments. In particular, the uncertainty related to the choice of the signal model is evaluated by using the nominal model to fit samples generated with two alternative – 8 – JHEP11(2018)048 C. Gotti20,i, E. Govorkova27, J.P. Grabowski12, R. Graciani Diaz40, L.A. Granado Cardoso42, E. Graug´es40, E. Graverini44, G. Graziani17, A. Grecu32, R. Greim27, P. Griffith22, L. Grillo56, L. Gruber42, B.R. Gruberg Cazon57, O. Gr¨unberg67, C. Gu3, E. Gushchin36, Yu. Guz39,42, T. Gys42, C. G¨obel62, T. Hadavizadeh57, C. Hadjivasiliou5, G. Haefeli43, C. Haen42, S.C. Haines49, B. Hamilton60, X. Han12, T.H. Hancock57, S. Hansmann-Menzemer12, N. Harnew57, S.T. Harnew48, C. Hasse42, M. Hatch42, J. He63, M. Hecker55, K. Heinicke10, A. Heister9, K. Hennessy54, L. Henry72, E. van Herwijnen42, M. Heß67, A. Hicheur2, D. Hill57, M. Hilton56, P.H. Hopchev43, W. Hu65, W. Huang63, Z.C. Huard59, W. Hulsbergen27, T. Humair55, M. 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Milanes66, E. Millard50, M.-N. Minard4, L. Minzoni16,g, D.S. Mitzel12, A. Mogini8, J. Molina Rodriguez1,z, T. Momb¨acher10, I.A. Monroy66, S. Monteil5, M. Morandin23, G. Morello18, M.J. Morello24,t, O. Morgunova69, J. Moron30, A.B. Morris6, R. Mountain61, F. Muheim52, M. Mulder27, D. M¨uller42, J. M¨uller10, K. M¨uller44, V. M¨uller10, P. Naik48, T. Nakada43, R. Nandakumar51, A. Nandi57, T. Nanut43, I. Nasteva2, M. Needham52, N. Neri21, S. Neubert12, N. Neufeld42, M. Neuner12, T.D. Nguyen43, C. Nguyen-Mau43,n, S. Nieswand9, R. Niet10, N. Nikitin35, A. Nogay69, D.P. O’Hanlon15, A. Oblakowska-Mucha30, V. Obraztsov39, S. Ogilvy18, R. Oldeman22,f , C.J.G. Onderwater68, A. Ossowska29, J.M. Otalora Goicochea2, P. Owen44, A. Oyanguren72, P.R. Pais43, A. Palano14, M. Palutan18,42, G. Panshin71, A. Papanestis51, M. Pappagallo52, L.L. Pappalardo16,g, W. Parker60, C. Parkes56, G. Passaleva17,42, A. Pastore14, M. Patel55, C. Patrignani15,e, A. Pearce42, A. Pellegrino27, G. Penso26, M. Pepe Altarelli42, S. Perazzini42, D. Pereima34, P. Perret5, L. Pescatore43, K. Petridis48, A. Petrolini19,h, A. Petrov69, M. Petruzzo21,q, B. Pietrzyk4, G. Pietrzyk43, M. Pikies29, D. Pinci26, J. Pinzino42, F. Pisani42, A. Pistone19,h, A. Piucci12, V. Placinta32, S. Playfer52, J. Plews47, M. Plo Casasus41, F. Polci8, M. Poli Lener18, A. Poluektov50, N. Polukhina70,c, I. Polyakov61, E. Polycarpo2, G.J. Pomery48, S. Ponce42, A. Popov39, D. Popov47,11, S. Poslavskii39, C. Potterat2, E. Price48, J. Prisciandaro41, C. Prouve48, V. Pugatch46, A. Puig Navarro44, H. Pullen57, G. Punzi24,p, W. Qian63, J. Qin63, R. Quagliani8, B. Quintana5, B. Rachwal30, J.H. Rademacker48, M. Rama24, – 15 – JHEP11(2018)048 M. Ramos Pernas41, M.S. Rangel2, F. Ratnikov37,x, G. Raven28, M. Ravonel Salzgeber42, M. Reboud4, F. Redi43, S. Reichert10, A.C. dos Reis1, F. Reiss8, C. Remon Alepuz72, Z. Ren3, V. Renaudin7, S. Ricciardi51, S. Richards48, K. Rinnert54, P. Robbe7, A. Robert8, A.B. Rodrigues43, E. Rodrigues59, J.A. Rodriguez Lopez66, A. Rogozhnikov37, S. Roiser42, A. Rollings57, V. Romanovskiy39, A. Romero Vidal41, M. Rotondo18, M.S. Rudolph61, T. Ruf42, J. Ruiz Vidal72, J.J. Saborido Silva41, N. Sagidova33, B. Saitta22,f , V. Salustino Guimaraes62, C. Sanchez Gras27, C. Sanchez Mayordomo72, B. Sanmartin Sedes41, R. Santacesaria26, C. Santamarina Rios41, M. Santimaria18, E. Santovetti25,j, G. Sarpis56, A. Sarti18,k, C. Satriano26,s, A. Satta25, M. Saur63, D. Savrina34,35, S. Schael9, M. Schellenberg10, M. Schiller53, H. Schindler42, M. Schmelling11, T. Schmelzer10, B. Schmidt42, O. Schneider43, A. Schopper42, H.F. Schreiner59, M. Schubiger43, M.H. Schune7, R. Schwemmer42, B. Sciascia18, A. Sciubba26,k, A. Semennikov34, E.S. Sepulveda8, A. Sergi47,42, N. Serra44, J. Serrano6, L. Sestini23, P. Seyfert42, M. Shapkin39, Y. Shcheglov33,†, T. Shears54, L. Shekhtman38,w, V. Shevchenko69, E. Shmanin70, B.G. Siddi16, R. Silva Coutinho44, L. Silva de Oliveira2, G. Simi23,o, S. Simone14,d, N. Skidmore12, T. Skwarnicki61, E. Smith9, I.T. Smith52, M. Smith55, M. Soares15, l. Soares Lavra1, M.D. Sokoloff59, F.J.P. Soler53, B. Souza De Paula2, B. Spaan10, P. Spradlin53, F. Stagni42, M. Stahl12, S. Stahl42, P. Stefko43, S. Stefkova55, O. Steinkamp44, S. Stemmle12, O. Stenyakin39, M. Stepanova33, H. Stevens10, S. Stone61, B. Storaci44, S. Stracka24, M.E. Stramaglia43, M. Straticiuc32, U. Straumann44, S. Strokov71, J. Sun3, L. Sun64, K. Swientek30, V. Syropoulos28, T. Szumlak30, M. Szymanski63, S. T’Jampens4, Z. Tang3, A. Tayduganov6, T. Tekampe10, G. Tellarini16, F. Teubert42, E. Thomas42, J. van Tilburg27, M.J. Tilley55, V. Tisserand5, M. Tobin43, S. Tolk42, L. Tomassetti16,g, D. Tonelli24, D.Y. Tou8, R. Tourinho Jadallah Aoude1, E. Tournefier4, M. Traill53, M.T. Tran43, A. Trisovic49, A. Tsaregorodtsev6, G. Tuci24,p, A. Tully49, N. Tuning27,42, A. Ukleja31, A. Usachov7, A. Ustyuzhanin37, U. Uwer12, C. Vacca22,f , A. Vagner71, V. Vagnoni15, A. Valassi42, S. Valat42, G. Valenti15, R. Vazquez Gomez42, P. Vazquez Regueiro41, S. Vecchi16, M. van Veghel27, J.J. Velthuis48, M. Veltri17,r, G. Veneziano57, A. Venkateswaran61, T.A. Verlage9, M. Vernet5, M. Vesterinen57, J.V. Viana Barbosa42, D. Vieira63, M. Vieites Diaz41, H. Viemann67, X. Vilasis-Cardona40,m, A. Vitkovskiy27, M. Vitti49, V. Volkov35, A. Vollhardt44, B. Voneki42, A. Vorobyev33, V. Vorobyev38,w, C. Voß9, J.A. de Vries27, C. V´azquez Sierra27, R. Waldi67, J. Walsh24, J. Wang61, M. Wang3, Y. Wang65, Z. Wang44, D.R. Ward49, H.M. Wark54, N.K. Watson47, D. Websdale55, A. Weiden44, C. Weisser58, M. Whitehead9, J. Wicht50, G. Wilkinson57, M. Wilkinson61, M.R.J. Williams56, M. Williams58, T. Williams47, F.F. Wilson51,42, J. Wimberley60, M. Winn7, J. Wishahi10, W. Wislicki31, M. Witek29, G. Wormser7, S.A. Wotton49, K. Wyllie42, D. Xiao65, Y. Xie65, A. Xu3, M. Xu65, Q. Xu63, Z. Xu3, Z. Xu4, Z. Yang3, Z. Yang60, Y. Yao61, H. Yin65, J. Yu65,ab, X. Yuan61, O. Yushchenko39, K.A. Zarebski47, M. Zavertyaev11,c, D. Zhang65, L. Zhang3, W.C. Zhang3,aa, Y. Zhang7, A. Zhelezov12, Y. Zheng63, X. Zhu3, V. Zhukov9,35, J.B. Zonneveld52, S. Zucchelli15 1Centro Brasileiro de Pesquisas F´ısicas (CBPF), Rio de Janeiro, Brazil 2Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil 3Center for High Energy Physics, Tsinghua University, Beijing, China 4Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IN2P3-LAPP, Annecy, France 5Clermont Universit´e, Universit´e Blaise Pascal, CNRS/IN2P3, LPC, Clermont-Ferrand, France 6Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France 7LAL, Univ. Paris-Sud, CNRS/IN2P3, Universit´e Paris-Saclay, Orsay, France 8LPNHE, Sorbonne Universit´e, Paris Diderot Sorbonne Paris Cit´e, CNRS/IN2P3, Paris, France 9I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany 10 Fakult¨at Physik, Technische Universit¨at Dortmund, Dortmund, Germany – 16 – JHEP11(2018)048 11 Max-Planck-Institut f¨ur Kernphysik (MPIK), Heidelberg, Germany 12 Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany 13 School of Physics, University College Dublin, Dublin, Ireland 14 INFN Sezione di Bari, Bari, Italy 15 INFN Sezione di Bologna, Bologna, Italy 16 INFN Sezione di Ferrara, Ferrara, Italy 17 INFN Sezione di Firenze, Firenze, Italy 18 INFN Laboratori Nazionali di Frascati, Frascati, Italy 19 INFN Sezione di Genova, Genova, Italy 20 INFN Sezione di Milano-Bicocca, Milano, Italy 21 INFN Sezione di Milano, Milano, Italy 22 INFN Sezione di Cagliari, Monserrato, Italy 23 INFN Sezione di Padova, Padova, Italy 24 INFN Sezione di Pisa, Pisa, Italy 25 INFN Sezione di Roma Tor Vergata, Roma, Italy 26 INFN Sezione di Roma La Sapienza, Roma, Italy 27 Nikhef National Institute for Subatomic Physics, Amsterdam, Netherlands 28 Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam, Netherlands 29 Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Krak´ow, Poland 30 AGH – University of Science and Technology, Faculty of Physics and Applied Computer Science, Krak´ow, Poland 31 National Center for Nuclear Research (NCBJ), Warsaw, Poland 32 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania 33 Petersburg Nuclear Physics Institute (PNPI), Gatchina, Russia 34 Institute of Theoretical and Experimental Physics (ITEP), Moscow, Russia 35 Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia 36 Institute for Nuclear Research of the Russian Academy of Sciences (INR RAS), Moscow, Russia 37 Yandex School of Data Analysis, Moscow, Russia 38 Budker Institute of Nuclear Physics (SB RAS), Novosibirsk, Russia 39 Institute for High Energy Physics (IHEP), Protvino, Russia 40 ICCUB, Universitat de Barcelona, Barcelona, Spain 41 Instituto Galego de F´ısica de Altas Enerx´ıas (IGFAE), Universidade de Santiago de Compostela, Santiago de Compostela, Spain 42 European Organization for Nuclear Research (CERN), Geneva, Switzerland 43 Institute of Physics, Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland 44 Physik-Institut, Universit¨at Z¨urich, Z¨urich, Switzerland 45 NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine 46 Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine 47 University of Birmingham, Birmingham, U.K. 48 H.H. Wills Physics Laboratory, University of Bristol, Bristol, U.K. 49 Cavendish Laboratory, University of Cambridge, Cambridge, U.K. 50 Department of Physics, University of Warwick, Coventry, U.K. 51 STFC Rutherford Appleton Laboratory, Didcot, U.K. 52 School of Physics and Astronomy, University of Edinburgh, Edinburgh, U.K. 53 School of Physics and Astronomy, University of Glasgow, Glasgow, U.K. 54 Oliver Lodge Laboratory, University of Liverpool, Liverpool, U.K. 55 Imperial College London, London, U.K. 56 School of Physics and Astronomy, University of Manchester, Manchester, U.K. 57 Department of Physics, University of Oxford, Oxford, U.K. 58 Massachusetts Institute of Technology, Cambridge, MA, U.S.A. – 17 – JHEP11(2018)048 59 University of Cincinnati, Cincinnati, OH, U.S.A. 60 University of Maryland, College Park, MD, U.S.A. 61 Syracuse University, Syracuse, NY, U.S.A. 62 Pontif´ıcia Universidade Cat´olica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to 2 63 University of Chinese Academy of Sciences, Beijing, China, associated to 3 64 School of Physics and Technology, Wuhan University, Wuhan, China, associated to 3 65 Institute of Particle Physics, Central China Normal University, Wuhan, Hubei, China, associated to 3 66 Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia, associated to 8 67 Institut f¨ur Physik, Universit¨at Rostock, Rostock, Germany, associated to 12 68 Van Swinderen Institute, University of Groningen, Groningen, Netherlands, associated to 27 69 National Research Centre Kurchatov Institute, Moscow, Russia, associated to 34 70 National University of Science and Technology ”MISIS”, Moscow, Russia, associated to 34 71 National Research Tomsk Polytechnic University, Tomsk, Russia, associated to 34 72 Instituto de Fisica Corpuscular, Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain, associated to 40 73 University of Michigan, Ann Arbor, U.S.A., associated to 61 74 Los Alamos National Laboratory (LANL), Los Alamos, U.S.A., associated to 61 aUniversidade Federal do Triˆangulo Mineiro (UFTM), Uberaba-MG, Brazil bLaboratoire Leprince-Ringuet, Palaiseau, France cP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, Russia dUniversit`a di Bari, Bari, Italy eUniversit`a di Bologna, Bologna, Italy fUniversit`a di Cagliari, Cagliari, Italy gUniversit`a di Ferrara, Ferrara, Italy hUniversit`a di Genova, Genova, Italy iUniversit`a di Milano Bicocca, Milano, Italy jUniversit`a di Roma Tor Vergata, Roma, Italy kUniversit`a di Roma La Sapienza, Roma, Italy lAGH – University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krak´ow, Poland mLIFAELS, La Salle, Universitat Ramon Llull, Barcelona, Spain nHanoi University of Science, Hanoi, Vietnam oUniversit`a di Padova, Padova, Italy pUniversit`a di Pisa, Pisa, Italy qUniversit`a degli Studi di Milano, Milano, Italy rUniversit`a di Urbino, Urbino, Italy sUniversit`a della Basilicata, Potenza, Italy tScuola Normale Superiore, Pisa, Italy uUniversit`a di Modena e Reggio Emilia, Modena, Italy vMSU – Iligan Institute of Technology (MSU-IIT), Iligan, Philippines wNovosibirsk State University, Novosibirsk, Russia xNational Research University Higher School of Economics, Moscow, Russia ySezione INFN di Trieste, Trieste, Italy zEscuela Agr´ıcola Panamericana, San Antonio de Oriente, Honduras aa School of Physics and Information Technology, Shaanxi Normal University (SNNU), Xi’an, China ab Physics and Micro Electronic College, Hunan University, Changsha City, China †Deceased – 18 –