EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)
CERN-EP-2021-058 LHCb-PAPER-2020-047 May 4, 2021Measurement of CP asymmetry
in D
0
→ K
S
0
K
S
0
decays
LHCb collaboration† Abstract A measurement of the CP asymmetry in D0 → K0SKS0 decays is reported, based on a data sample of proton-proton collisions collected by the LHCb experiment from 2015 to 2018, corresponding to an integrated luminosity of 6 fb−1. The flavor of the D0 candidate is determined using the charge of the D∗± meson, from which the decay is required to originate. The D0 → K+K− decay is used as a calibration channel. The time-integrated CP asymmetry for the D0 → K0
SKS0 mode is measured to be:
ACP(D0 → K0
SKS0) = (−3.1 ± 1.2 ± 0.4 ± 0.2)%,
where the first uncertainty is statistical, the second is systematic, and the third is due to the uncertainty on the CP asymmetry of the calibration channel. This is the most precise determination of this quantity to date.
Submitted to Phys. Rev. D Lett.
© 2021 CERN for the benefit of the LHCb collaboration. CC BY 4.0 licence.
†Authors are listed at the end of this Letter.
The existence of charge-parity violation (CP V ) effects in charm hadrons has recently been established [1], which constitutes the only evidence of CP V in the up-quark (u, c or t) sector. However, current experimental evidence is limited to a single observable, ∆ACP, the difference between the CP asymmetry in D0→ K+K− and D0→ π+π− decays.
Given the uncertainties in the theoretical predictions on CP V in the charm-quark sector within the Standard Model (SM), it is currently not possible to test these [2, 3]. Further measurements in charm-hadron decays are crucial to shed light on CP V phenomenology. This could involve dynamics beyond the SM, which is not constrained to be the same as in the down-quark (d, s or b) sector and could enter the amplitudes via loop contributions, affecting observables in a detectable way.
Amongst many charm-hadron decay modes in which CP V could manifest, the D0→ K0
SK
0
S mode is a promising target because of the expected size of the effect. Its CP
asymmetry is defined by ACP(K0 SK 0 S) = Γ(D0→ K0 SKS0) − Γ(D0→ KS0KS0) Γ(D0→ K0 SKS0) + Γ(D0→ KS0KS0) , (1)
where Γ is the decay width of the D0 (D0) meson, and it can be larger than in other
channels, up to the percent level in the SM [4–8]. In fact, only amplitudes proceeding via loop-suppressed and tree-level exchange diagrams, which vanish in the flavor–SU(3) limit, contribute to this decay, and they are similar in size. Their interference could therefore result in a detectable CP asymmetry. In addition, the CP asymmetry in the D0→ K0
SKS0
decay is sensitive to a different mix of amplitudes compared to D0 → K+K− and
D0→ π+π− decays. Therefore, measuring ACP (K0
SKS0) provides independent information
which can help to elucidate the mechanisms of CP V in charm hadron decays.
The current world average for the time-integrated CP asymmetry is ACP(K0
SKS0) = (0.4 ± 1.4)% [9], the precision of which is still insufficient for
de-tecting an effect. In this work, a new measurement of this quantity, performed with proton-proton (pp) collisions collected from 2015 to 2018 (Run 2) by the LHCb experiment at the LHC at CERN, is reported. Data collected at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1, are used. The subsample of data collected during 2015 and 2016 has been analyzed previously [10]. In the present work a number of improvements in the analysis leads to a more efficient selection and a sizeable improvement in sensitivity.
The measurement of ACP(KS0KS0) requires knowledge of the D0 flavor at production. A sample of flavor-tagged D0→ K0
SKS0 decays is obtained by selecting only D0 mesons
that originate from D∗+ → D0π+ decays.1 The charge of the pion (tagging pion) in this
decay identifies the flavor of the accompanying D0 meson. While D0 oscillations may cause some of them to change flavor before decaying, this is a small effect in comparison to the resolution of the current measurement and is not considered further.
The decay widths Γ in Eq. 1 are related to the number of observed candidates N by
N ((D)0 → K0 SK 0 S) ∝ σ(D ∗±)ε±Γ(( ) D0 → K0 SK 0 S), (2)
where σ(D∗±) are the production cross sections and ε± the detection probabilities for D∗± decays. Both factors are charge-asymmetric, due to the D∗± production asymmetry
arising from the hadronization of charm quarks in pp collisions, and to asymmetries in the geometry and response of the detector. Because of the charge-symmetric final state of the D0 decay, the only source of detection asymmetry comes from the tagging pion. All these quantities are calibrated using a large sample of D0→ K+K− decays, for which
ACP is known with much greater precision than in the D0→ K0
SKS0 decay mode [11].
The LHCb detector is a single-arm forward spectrometer designed for the study of particles containing b or c quarks, as described in detail in Refs. [12, 13]. The LHCb tracking system exploits a dipole magnet to measure the momentum of charged particles, and it consists of a silicon-strip vertex detector surrounding the pp interaction region [14] and tracking stations placed upstream and downstream of the magnet. The magnetic-field polarity is reversed periodically during data taking, alternating between pointing upwards (MagUp) and downwards (MagDown), to mitigate the differences of reconstruction efficiencies of particles with opposite charges. The online event selection is performed by a trigger [15], 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 and selection in two steps. The simulated data used in this analysis are produced using the software described in Refs. [16–20].
For an event to be considered in this analysis, the hardware-trigger decision is required to have been based either on the transverse energy deposited in the hadronic calorimeter by a particle associated with the D0 candidate, or on signatures not associated with the D∗+
candidate, such as a muon with high transverse momentum, or a large transverse-energy deposit in the electromagnetic or hadronic calorimeter from the rest of the event. Similarly, the first software stage decision is required to have been based either on the presence of a single track associated with the D0 decay, with sufficient transverse momentum and
impact parameter relative to the primary pp collision vertex (PV), or on track-related signatures independent of the D∗+ candidate. This ensures that the trigger decision is independent of the tagging pion, preventing a possible charge-dependent bias which would be difficult to measure and correct accurately.
At the second software stage, a complete reconstruction of the decay chain is performed, requiring a pair of K0
S mesons compatible with the decay of a D0 particle, and the presence
of an additional pion, compatible with originating from a D∗+→ D0π+ decay. Candidate
K0
S→ π+π
− decays are classified in two categories: those in which the decay occurred
early enough for the pions to be reconstructed in the vertex detector (“long”, indicated in the following by an “L” label); and those decaying later, such that segments of pion tracks can only be formed in the silicon-strip tracker upstream of the magnet, and the tracking stations after the magnet (“downstream”, indicated in the following by a “D” label). The geometric acceptance of the LHCb detector for typical KS0 momenta is about a factor of two larger for D-type versus L-type decays, but the mass, momentum and vertex resolution of the latter category are better than those of the former.
Candidates are separated into three categories: LL, LD, or DD, according to the types of the two K0
S mesons associated to the D0 meson. These are analyzed separately, and
the results are combined only at the end. To prevent any experimenters’ bias, the flavor of D0 candidates was not examined until the analysis was finalized.
Some of the D∗+ mesons are not promptly produced in the primary pp interaction, but rather come from the decay of a beauty-flavored hadron. These secondary decays are affected by different production asymmetries with respect to prompt decays, which is estimated at the 1% level. No attempt is made in this analysis to reject secondary
decays, as selection requirements based on pointing observables are less effective in D0 mesons reconstructed with displaced vertices, such as D0 → K0
SKS0, compared to
other charm hadron decays. The spurious asymmetry introduced by this contribution is instead canceled by use of a dedicated calibration sample. For this purpose, a sample of D0→ K+K− decays produced in D∗+ decays is selected in a way to ensure it contains
prompt and secondary decays in the same proportions as the D0→ K0
SK
0
S sample. Its
selection, starting from the first trigger level, refrains from any requirements for which the effect on the secondary-to-prompt ratio cannot reliably reproduce that in the signal sample. This requires, amongst other things, to avoid selections based on observables sensitive to the location of the D∗ or D0 vertices, which have different resolutions in the two samples [21].
The D0→ K0
SK
0
S signal peaks in the difference of invariant masses ∆m = m(D
∗+) −
m(D0), where m(D0) is the invariant mass of the D0→ K0
SKS0 candidate and m(D ∗+
) is the invariant mass of the D∗+→ D0π+ candidate. This sample may be contaminated by
other physics processes. Amongst them, partially reconstructed D0 decays coming from D∗+ mesons, such as D0→ K0
SKS0π0, can also peak in ∆m. Some non-D0 decays can also
contaminate the sample, the main contributor being D+
s → KS0KS0π+ decays, where the
KS0KS0 pair is incorrectly associated with a D0 decay. These background components are effectively suppressed by selecting only candidates with m(D0) within ±20(30) MeV/c2 of the known D0 mass [9] in LL/LD (DD) samples.
A background source which is difficult to eliminate completely is the abundant D0 →K0
Sπ+π− decay, with the π+π− pair mimicking a KS0. After a loose selection
based on the flight distance of the K0
S, it is statistically separated from the signal through
a simultaneous fit of three observables: the ∆m and the invariant masses, m(K0
S), of the
two KS0 candidates.
To maximize the sensitivity of the measurement, the LL and LD subsamples are further split according to whether the D∗+ candidate is compatible or incompatible with having originated from the PV. Compatibility is defined by a fixed threshold on the goodness of fit of the complete decay chain [22], when constrained to be originating from the PV. For PV-compatible candidates, independent of their true nature, a factor of two better mass resolution is obtained by constraining the origin vertex to coincide with the PV. Therefore, separate analyses of the two subsamples, followed by the combination of the results provides optimal exploitation of the available data. This is not done for the DD sample due to its limited signal yield. While this requirement might in principle have slightly different effects on the secondary fraction of signal and calibration sample, differences are negligible, as it has been explicitly verified on data.
The data are further split according to a classifier sensitive to the signal-to-background ratio. The classifier combines a number of track-related observables, including track and vertex quality, transverse momenta of K0
S and D0 candidates, helicity angles of the KS0
and D0 decays, and particle identification parameters of the D0 final state particles. The kinematics of the tagging pion is excluded to avoid introducing possible charge asymmetry biases. All these observables are combined in a k-nearest-neighbors (kNN) classifier [23], trained using a simulated signal sample, and data from the D0 mass sidebands for background. The resulting discriminant is used to split each sample in three categories (low-, medium- and high-purity); the low-purity class contains very little signal and is removed. The thresholds separating the three categories are numerically optimized in a way to achieve the best combined resolution on ACP [21].
140 142 144 146 148 150 152 154 ] 2 c [MeV/ m ∆ 0 200 400 600 800 1000 1200 ) 2 c Candidates / ( 0.2 MeV/ LHCb -1 4 fb S 0 K S 0 K → 0 D / 0 D Data Total Background LL PV-compatible medium-purity 140 142 144 146 148 150 152 154 ] 2 c [MeV/ m ∆ 0 20 40 60 80 100 120 140 160 180 200 220 ) 2 c Candidates / ( 0.3 MeV/ LHCb -1 4 fb S 0 K S 0 K → 0 D / 0 D Data Total Background LL PV-incompatible medium-purity 140 142 144 146 148 150 152 154 ] 2 c [MeV/ m ∆ 0 50 100 150 200 250 300 350 400 ) 2 c Candidates / ( 0.2 MeV/ LHCb -1 4 fb S 0 K S 0 K → 0 D / 0 D Data Total Background LD PV-compatible medium-purity 140 142 144 146 148 150 152 154 ] 2 c [MeV/ m ∆ 0 20 40 60 80 100 120 140 160 180 ) 2 c Candidates / ( 0.3 MeV/ LHCb -1 4 fb S 0 K S 0 K → 0 D / 0 D Data Total Background DD high-purity
Figure 1: Distributions and fit projections of the ∆m observable for representative candidate categories (2017–2018 data). See text for the definition of purities.
Finally, 2015–2016 data are analyzed separately from 2017–2018 data, due to different trigger conditions. In addition, DD candidates were not collected in 2015–2016 data taking. In about 10% of cases, multiple D∗+ candidates are found in the same event. This is mainly due to D0 candidates that are associated with multiple tagging pions. In these cases, one D∗+ candidate is randomly selected for the analysis.
Distributions of the ∆m variable for some representative subsamples are shown in Fig. 1. An unbinned maximum-likelihood fit is performed to the joint distribution of ∆m and the two m(KS0) observables, simultaneously to candidates of both flavors to obtain the value of ACP. The total probability density function is parameterized by the sum of eight
components: the signal component, peaking in the three observables, and seven additional components, each describing a specific background source. This includes D0 → K0
Sπ+π
−
decays, which peak in ∆m and in one m(K0
S) distribution but not in the other, and
all possible combinations of unrelated particles. The peaking component in the ∆m distribution is described by a Gaussian function in PV-incompatible samples, or a Johnson SU distribution [24] in PV-compatible samples. The peaking component in the m(KS0)
distribution is described by the sum of two Gaussian functions with different widths and a common mean, for both L- and D-category KS0 candidates. The non-peaking component in the ∆m distribution is described by an empirical threshold function, while in the m(K0
S)
distribution it is described by a first- and second-order Chebyshev polynomial for L- and D-category KS0 candidates, respectively. In each subsample, the parameters defining the signal and background probability density functions are shared between flavors, while the normalization of each component is allowed to differ.
Each candidate participating in the fit is appropriately weighted with the aim of correcting for all spurious asymmetries, with the help of the calibration D0→ K+K−
sample, selected in a way to contain the same proportions of primary and secondary decays. The calibration sample is similarly split between PV-compatible and PV-incompatible categories, and is required to have m(K+K−) within ±20 MeV/c2 around the known D0
0.5 1 1.5 2 weight 0 100 200 300 400 500 600 700 800 Candidates/0.016 LHCb -1 4 fb LL PV-compatible MagUp S 0 K S 0 K → 0 D S 0 K S 0 K → 0 D 0.5 1 1.5 2 weight 0 100 200 300 400 500 600 700 Candidates/0.016 LHCb -1 4 fb LL PV-compatible MagDown S 0 K S 0 K → 0 D S 0 K S 0 K → 0 D
Figure 2: Distributions of weights (2017–2018 data) applied to signal candidates in the global fit to correct for detector, production, and physics of the calibration channel. Differences between MagUp (left) and MagDown (right) are a consequence of different D0 and D0 acceptances, and of detector asymmetries. A small fraction of entries with large weights fall outside the range of the plot.
mass. In addition, only candidates in a ±1.5 MeV/c2 range around the ∆m peak are used.
To compute weights, each D0→ K+K−subsample is classified in categories of observed
charge asymmetry, by a kNN classifier based on the space of kinematic parameters of the D0 candidate. The detector and production asymmetries observed in the calibration
sample are independent of the D0 decay mode, being charge-symmetric, and can be used
to correct the signal sample for the same effects. This is achieved by weighting each signal candidate in the global fit by a charge-dependent factor
w±(~p0) =
n+C(~p0) + n−C(~p0)
2n±C(~p0)
1 ± ACP(K+K−) ,
(3)
where ~p0 is the D0 three-momentum, and n±C(~p0) is the density of calibration D∗± decays
in the ~p0 space [21].
To account for a possible dependence of the detection asymmetry on magnet polarity, weights are separately calculated for MagUp and MagDown configurations. Their distri-butions are shown in Fig. 2, where their difference is clearly visible. To avoid weights affected by large uncertainties, a negligible fraction of candidates having very large weights (> 10) are dropped at this stage. The weighting procedure described above is a better alternative to the procedure of binning the D0 kinematic space and weighting the two
samples to have the same distribution. The advantage is a reduction of dimensionality to the single variable of actual relevance, that is the charge asymmetry to be corrected. This reduces the loss in statistical power that occurs when weighting bins of very different populations in the two samples under comparison. In addition, it holds exactly even when the involved asymmetries are not small. This is helpful in the case of the LHCb detector, where some kinematic regions are characterized by sizeable detection asymmetries for charged pions [10]. This affects the tagging pion in 30% of our events.
This weighting method has been extensively checked with both data and simulation. One of the checks is to apply the weighting procedure to half of the D0→ K+K− sample,
using the second half to calculate weights. This has the expected effect of canceling the asymmetry of the sample, that was initially highly significant, (1.3 ± 0.1)%, due to a combination of physics and detector effects.
The systematic uncertainty associated to the limited size of the calibration mode is determined by a bootstrap sampling of the data, and is found to be negligible. The
Table 1: Measurements of yields and ACP(D0 → K0
SKS0) in individual subsamples. For asymme-tries, the first uncertainty is statistical and the second is systematic.
Sample 2015 + 2016 (2 fb−1) 2017 + 2018 (4 fb−1) Yield ACP [%] Yield ACP [%] LL PV-comp. 1388 ± 41 0.3 ± 2.5 ± 0.6 4056 ± 77 − 4.3 ± 1.6 ± 0.4 LL PV-incomp. 178 ± 31 − 11 ± 17 ± 2 430 ± 41 − 3.0 ± 7.9 ± 1.1 LD PV-comp. 411 ± 25 − 7.2 ± 5.8 ± 1.1 1145 ± 49 − 2.9 ± 3.8 ± 0.7 LD PV-incomp. 58 ± 18 − 10 ± 31 ± 4 349 ± 64 − 5 ± 17 ± 2 DD − − 87 ± 28 − 35 ± 47 ± 6
uncertainty due to the presence of residual background in the D0→ K+K− sample has
also been evaluated and found to be a minor effect.
Another important source of systematic uncertainty is due to the limited knowledge of the shape of the mass distributions, as the fit function used is purely empirical. Any potential bias in the procedure is evaluated by fitting the model to simulated samples of pseudo-experiments from alternative models. The number and type of peaking components and the behavior of the background at the kinematic threshold are varied, and the largest observed variations are taken as the systematic uncertainty, ranging between 0.4% and 5.6%, depending on the subsample.
A systematic uncertainty is also assessed for possible residual differences in secondary decay fractions between signal and calibration samples. The largest discrepancy between the two samples is the presence of slightly different trigger requirements on the proper decay time of the D0 candidate. This has been corrected for by increasing the weight of
candidates close to the threshold, to emulate the effect of those that have been lost. An uncertainty of this correction is conservatively assessed, that is between 0.1% and 0.2%. Finally, an uncertainty of 0.15% in the input value of ACP(K+K−) is separately taken into
account, measured by the LHCb experiment as ACP(K+K−) = (0.04 ± 0.12 ± 0.10)% [11]. The results obtained in each subsample are summarized in Table 1. The subsamples corresponding to different kNN classifier ranges are fitted simultaneously with common parameters, so they do not produce separate results. As a check of goodness of fit, a χ2 has been calculated for each one-dimensional projection of the fit (Fig. 1). All p-values are found to be greater than 0.2.
All partial results in Table 1 are statistically compatible with each other. The weighted average of all measurements using 2015–2016 data, is
ACP(K0
SK
0
S) = (−1.1 ± 2.3 ± 0.5 ± 0.2)%,
where the first uncertainty is statistical, the second is systematic, obtained by taking the individual contributions as uncorrelated, and the third is from the uncertainty on ACP(K+K−). This result is compatible with the previously published value based on
the same data sample [10], but has a better precision by about 30%, corresponding to an effective doubling of the yields. The sensitivity increase is due to the combined effect of several improvements in the analysis, most notably the new weighting technique, the inclusion of secondary decays, an appropriate categorization of the sample, and the multidimensional likelihood fit.
The asymmetry for the 2017–2018 data is measured to be
ACP(K0
SK
0
S) = (−4.0 ± 1.5 ± 0.3 ± 0.2)%.
Treating the systematic uncertainties as uncorrelated between the data taking periods, except for the shape of the fit functions that is considered to be fully correlated, the asymmetry combining the results from the full Run 2 data sample is obtained as
ACP(K0
SK
0
S) = (−3.1 ± 1.2 ± 0.4 ± 0.2)%.
This measurement supersedes the previous LHCb result [10] and is in agreement with all previous determinations [25–27]. It is the most precise measurement of this quantity to date, and it is compatible with no CP asymmetry at the level of 2.4 standard deviations.
Acknowledgements
We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from CERN and from the national agencies: CAPES, CNPq, FAPERJ and FINEP (Brazil); MOST and NSFC (China); CNRS/IN2P3 (France); BMBF, DFG and MPG (Germany); INFN (Italy); NWO (Netherlands); MNiSW and NCN (Poland); MEN/IFA (Romania); MSHE (Russia); MICINN (Spain); SNSF and SER (Switzerland); NASU (Ukraine); STFC (United Kingdom); DOE NP and NSF (USA). We acknowledge the computing resources that are provided by CERN, IN2P3 (France), KIT and DESY (Germany), INFN (Italy), SURF (Netherlands), PIC (Spain), GridPP (United Kingdom), RRCKI and Yandex LLC (Russia), CSCS (Switzerland), IFIN-HH (Romania), CBPF (Brazil), PL-GRID (Poland) and NERSC (USA). We are indebted to the communities behind the multiple open-source software packages on which we depend. Individual groups or members have received support from ARC and ARDC (Australia); AvH Foundation (Germany); EPLANET, Marie Sk lodowska-Curie Actions and ERC (European Union); A*MIDEX, ANR, IPhU and Labex P2IO, and R´egion Auvergne-Rhˆone-Alpes (France); Key Research Program of Frontier Sciences of CAS, CAS PIFI, CAS CCEPP, Fundamental Research Funds for the Central Universities, and Sci. & Tech. Program of Guangzhou (China); RFBR, RSF and Yandex LLC (Russia); GVA, XuntaGal and GENCAT (Spain); the Leverhulme Trust, the Royal Society and UKRI (United Kingdom).
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M. Chefdeville8, C. Chen3, S. Chen27, A. Chernov35, V. Chobanova46, S. Cholak49,
M. Chrzaszcz35, A. Chubykin38, V. Chulikov38, P. Ciambrone23, M.F. Cicala56, X. Cid Vidal46, G. Ciezarek48, P.E.L. Clarke58, M. Clemencic48, H.V. Cliff55, J. Closier48, J.L. Cobbledick62, V. Coco48, J.A.B. Coelho11, J. Cogan10, E. Cogneras9, L. Cojocariu37, P. Collins48,
T. Colombo48, L. Congedo19,c, A. Contu27, N. Cooke53, G. Coombs59, G. Corti48,
C.M. Costa Sobral56, B. Couturier48, D.C. Craik64, J. Crkovsk´a67, M. Cruz Torres1, R. Currie58, C.L. Da Silva67, E. Dall’Occo15, J. Dalseno46, C. D’Ambrosio48, A. Danilina41, P. d’Argent48, A. Davis62, O. De Aguiar Francisco62, K. De Bruyn78, S. De Capua62, M. De Cian49,
J.M. De Miranda1, L. De Paula2, M. De Serio19,c, D. De Simone50, P. De Simone23,
J.A. de Vries79, C.T. Dean67, D. Decamp8, L. Del Buono13, B. Delaney55, H.-P. Dembinski15, A. Dendek34, V. Denysenko50, D. Derkach81, O. Deschamps9, F. Desse11, F. Dettori27,e, B. Dey73, P. Di Nezza23, S. Didenko82, L. Dieste Maronas46, H. Dijkstra48, V. Dobishuk52, A.M. Donohoe18, F. Dordei27, A.C. dos Reis1, L. Douglas59, A. Dovbnya51, A.G. Downes8, K. Dreimanis60, M.W. Dudek35, L. Dufour48, V. Duk77, P. Durante48, J.M. Durham67,
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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
4Institute Of High Energy Physics (IHEP), Beijing, China
5School of Physics State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing,
China
6University of Chinese Academy of Sciences, Beijing, China
7Institute of Particle Physics, Central China Normal University, Wuhan, Hubei, China
8Univ. Savoie Mont Blanc, CNRS, IN2P3-LAPP, Annecy, France
9Universit´e Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
10Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France
11Universit´e Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France
12Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris,
Palaiseau, France
13LPNHE, Sorbonne Universit´e, Paris Diderot Sorbonne Paris Cit´e, CNRS/IN2P3, Paris, France
14I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany
15Fakult¨at Physik, Technische Universit¨at Dortmund, Dortmund, Germany
16Max-Planck-Institut f¨ur Kernphysik (MPIK), Heidelberg, Germany
17Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany
18School of Physics, University College Dublin, Dublin, Ireland
19INFN Sezione di Bari, Bari, Italy
20INFN Sezione di Bologna, Bologna, Italy
21INFN Sezione di Ferrara, Ferrara, Italy
22INFN Sezione di Firenze, Firenze, Italy
23INFN Laboratori Nazionali di Frascati, Frascati, Italy
24INFN Sezione di Genova, Genova, Italy
25INFN Sezione di Milano, Milano, Italy
26INFN Sezione di Milano-Bicocca, Milano, Italy
27INFN Sezione di Cagliari, Monserrato, Italy
28Universita degli Studi di Padova, Universita e INFN, Padova, Padova, Italy
29INFN Sezione di Pisa, Pisa, Italy
30INFN Sezione di Roma La Sapienza, Roma, Italy
31INFN Sezione di Roma Tor Vergata, Roma, Italy
32Nikhef National Institute for Subatomic Physics, Amsterdam, Netherlands
33Nikhef National Institute for Subatomic Physics and VU University Amsterdam, Amsterdam,
Netherlands
34AGH - University of Science and Technology, Faculty of Physics and Applied Computer Science,
Krak´ow, Poland
35Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences, Krak´ow, Poland
36National Center for Nuclear Research (NCBJ), Warsaw, Poland
37Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania
39Institute for Nuclear Research of the Russian Academy of Sciences (INR RAS), Moscow, Russia
40Institute of Nuclear Physics, Moscow State University (SINP MSU), Moscow, Russia
41Institute of Theoretical and Experimental Physics NRC Kurchatov Institute (ITEP NRC KI), Moscow,
Russia
42Yandex School of Data Analysis, Moscow, Russia
43Budker Institute of Nuclear Physics (SB RAS), Novosibirsk, Russia
44Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI), Protvino, Russia,
Protvino, Russia
45ICCUB, Universitat de Barcelona, Barcelona, Spain
46Instituto Galego de F´ısica de Altas Enerx´ıas (IGFAE), Universidade de Santiago de Compostela,
Santiago de Compostela, Spain
47Instituto de Fisica Corpuscular, Centro Mixto Universidad de Valencia - CSIC, Valencia, Spain
48European Organization for Nuclear Research (CERN), Geneva, Switzerland
49Institute of Physics, Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Lausanne, Switzerland
50Physik-Institut, Universit¨at Z¨urich, Z¨urich, Switzerland
51NSC Kharkiv Institute of Physics and Technology (NSC KIPT), Kharkiv, Ukraine
52Institute for Nuclear Research of the National Academy of Sciences (KINR), Kyiv, Ukraine
53University of Birmingham, Birmingham, United Kingdom
54H.H. Wills Physics Laboratory, University of Bristol, Bristol, United Kingdom
55Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
56Department of Physics, University of Warwick, Coventry, United Kingdom
57STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
58School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom
59School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
60Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom
61Imperial College London, London, United Kingdom
62Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
63Department of Physics, University of Oxford, Oxford, United Kingdom
64Massachusetts Institute of Technology, Cambridge, MA, United States
65University of Cincinnati, Cincinnati, OH, United States
66University of Maryland, College Park, MD, United States
67Los Alamos National Laboratory (LANL), Los Alamos, United States
68Syracuse University, Syracuse, NY, United States
69School of Physics and Astronomy, Monash University, Melbourne, Australia, associated to56
70Pontif´ıcia Universidade Cat´olica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil, associated to2
71Physics and Micro Electronic College, Hunan University, Changsha City, China, associated to 7
72Guangdong Provencial Key Laboratory of Nuclear Science, Institute of Quantum Matter, South China
Normal University, Guangzhou, China, associated to 3
73School of Physics and Technology, Wuhan University, Wuhan, China, associated to 3
74Departamento de Fisica , Universidad Nacional de Colombia, Bogota, Colombia, associated to 13
75Universit¨at Bonn - Helmholtz-Institut f¨ur Strahlen und Kernphysik, Bonn, Germany, associated to 17
76Institut f¨ur Physik, Universit¨at Rostock, Rostock, Germany, associated to 17
77INFN Sezione di Perugia, Perugia, Italy, associated to 21
78Van Swinderen Institute, University of Groningen, Groningen, Netherlands, associated to 32
79Universiteit Maastricht, Maastricht, Netherlands, associated to 32
80National Research Centre Kurchatov Institute, Moscow, Russia, associated to41
81National Research University Higher School of Economics, Moscow, Russia, associated to42
82National University of Science and Technology “MISIS”, Moscow, Russia, associated to41
83National Research Tomsk Polytechnic University, Tomsk, Russia, associated to41
84DS4DS, La Salle, Universitat Ramon Llull, Barcelona, Spain, associated to45
85University of Michigan, Ann Arbor, United States, associated to68
aUniversidade Federal do Triˆangulo Mineiro (UFTM), Uberaba-MG, Brazil
bHangzhou Institute for Advanced Study, UCAS, Hangzhou, China
cUniversit`a di Bari, Bari, Italy
dUniversit`a di Bologna, Bologna, Italy
fUniversit`a di Ferrara, Ferrara, Italy
gUniversit`a di Firenze, Firenze, Italy
hUniversit`a di Genova, Genova, Italy
iUniversit`a degli Studi di Milano, Milano, Italy
jUniversit`a di Milano Bicocca, Milano, Italy
kUniversit`a di Modena e Reggio Emilia, Modena, Italy
lUniversit`a di Padova, Padova, Italy
mScuola Normale Superiore, Pisa, Italy
nUniversit`a di Pisa, Pisa, Italy
oUniversit`a della Basilicata, Potenza, Italy
pUniversit`a di Roma Tor Vergata, Roma, Italy
qUniversit`a di Siena, Siena, Italy
rUniversit`a di Urbino, Urbino, Italy
sMSU - Iligan Institute of Technology (MSU-IIT), Iligan, Philippines
tAGH - University of Science and Technology, Faculty of Computer Science, Electronics and
Telecommunications, Krak´ow, Poland
uP.N. Lebedev Physical Institute, Russian Academy of Science (LPI RAS), Moscow, Russia
vNovosibirsk State University, Novosibirsk, Russia
wDepartment of Physics and Astronomy, Uppsala University, Uppsala, Sweden
