Observation of prompt \mathrm{J}\hskip-0.8pt/\hskip-1.4pt\psi meson elliptic flow in high-multiplicity \mathrm{p}\text{Pb} collisions at \sqrt{\smash[b]{s_{{}_{\mathrm{NN}}}}}=8.16\,\text{TeV}
Abstract

A measurement of the elliptic flow () of prompt  mesons in high-multiplicity  collisions is reported using data collected by the CMS experiment at a nucleon-nucleon center-of-mass energy . Prompt  mesons decaying into two muons are reconstructed in the rapidity region in the nucleon-nucleon center-of-mass frame (), corresponding to either or . The average result from the two rapidity ranges is reported over the transverse momentum () range from 0.2 to 10. Positive values are observed for the prompt  meson, as extracted from long-range two-particle correlations with charged hadrons, for . The prompt  results are compared with previous CMS measurements of elliptic flow for open charm mesons () and strange hadrons. From these measurements, constraints can be obtained on the collective dynamics of charm quarks produced in high-multiplicity events arising from small systems.

EUROPEAN ORGANIZATION FOR NUCLEAR RESEARCH (CERN)


CERN-EP-2018-256 2019/\two@digits7/\two@digits19

CMS-HIN-18-010                                         


Observation of prompt  meson elliptic flow in high-multiplicity collisions at


The CMS Collaboration111See Appendix A for the list of collaboration members



Abstract

Please replace the default abstract using the abstract command.


Submitted to Physics Letters B

© 2019 CERN for the benefit of the CMS Collaboration. CC-BY-4.0 license

1 Introduction

Strong collective behavior is found in the azimuthal correlations of particles emitted in relativistic nucleus-nucleus (AA) collisions at the BNL RHIC [1, 2, 3, 1, 4] and at the CERN LHC [5, 6, 7, 8, 9, 10]. These correlations, which are long-range in pseudorapidity (), suggest the formation of a strongly interacting quark-gluon plasma (QGP) that exhibits nearly ideal hydrodynamic behavior [11, 12, 13]. The azimuthal correlation structure of emitted particles is typically characterized by its Fourier components [14]. In particular, within a hydrodynamic picture, the second and third Fourier anisotropy components are known as elliptic () and triangular () flow, respectively, and reflect the QGP medium response to the initial collision geometry and its fluctuations [15, 16, 17]. In recent years, similar long-range collective azimuthal correlations have also been observed in events with high final-state particle multiplicity in proton-proton ([18, 19, 20, 21], proton-nucleus ([22, 23, 24, 25, 26, 27, 28, 29, 30], and lighter AA collisions [31, 32, 33], raising the question of whether a fluid-like QGP is created in these much smaller systems. While experimental measurements in these small systems are consistent with the hydrodynamic expansion of a tiny QGP droplet, alternative scenarios based on gluon saturation in the initial state also claim to capture the main features of the correlation data (recent reviews are provided in Refs. [34, 35]).

Heavy-flavor quarks (charm and bottom) are primarily produced at a very early stage via initial hard scattering because of their large masses. As such, they are largely decoupled from the bulk production of soft gluons and light-flavor quarks at a later stage in AA collisions, and thereby probe the properties and dynamics of the QGP through its entire evolution [36]. A strong elliptic flow () signal has been observed for open heavy-flavor  mesons in both AuAu collisions at RHIC [37] and PbPb collisions at the LHC [38, 39, 40], suggesting that charm quarks may develop strong collective flow behavior. Furthermore, a recent measurement of the elliptic flow of  mesons in PbPb collisions at [41] has provided additional evidence for the collective behavior of charm quarks in the QGP.

In the study of collectivity in small systems, such as that occurring in  or  collisions, a key open question is whether the strong collective behavior observed for bulk constituents in high-multiplicity events also extends to charm and bottom quarks. Long-range correlations involving inclusive muons at high transverse momentum () reveal a hint of heavy-flavor quark collectivity in  collisions [42]. Furthermore, the recent observation of a significant elliptic flow signal for prompt  mesons in  collisions has provided evidence for charm quark collectivity in a small system [43]. The signal for  mesons is found to be smaller than that of light-flavor hadrons at a given , indicating that in these small systems there is a weaker collective motion for charm quarks, as compared to that of the bulk medium, than found in large AA systems. However, as the  meson carries both a light and a charm quark, the relative contribution of these different flavor quarks to the observed signal is not fully constrained. Without detailed theoretical modeling, a scenario is not excluded where the  meson signal is entirely carried by the light-flavor quark. The observation of an elliptic flow signal for  mesons in a small system could provide more direct evidence of charm quark collectivity and could impose new constraints on the collective dynamics of heavy-quark production in such collisions. Furthermore, heavy-quark collectivity may also provide a hint of how, in small systems, hard probes interact with the QGP [36], assuming this is formed. A measurement of inclusive  (combined charmonia and  mesons from decay of open beauty hadrons) in  collisions was reported in Ref. [44], where positive coefficients were found in the range of with center-of-mass rapidities or . A recent model calculation of   in  collisions suggests little signal arising from final-state interactions between charm quarks and the QGP medium [45].

This Letter presents the first measurement of prompt  meson elliptic flow (excluding contributions from  hadron decays) from long-range two-particle correlations in very high multiplicity  collisions at . The harmonics for prompt  mesons in the ranges and are determined over a wide  range from 0.2 to 10. To estimate the possible residual contribution from back-to-back jet-like correlations, the values are also presented after subtracting correlations obtained from low-multiplicity  events (denoted as ), where jet-like correlations are assumed to dominate. The results are compared to those of the light strange-flavor  and  hadrons, and the open heavy-flavor prompt  meson, which were previously reported by CMS [43] in the same  range but in a different rapidity range of . In order to explore possible collectivity at the partonic level, a comparison is also presented in terms of the transverse kinetic energy per constituent quark (/, where , and is the number of constituent quarks).

2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume, there are four primary subdetectors including a silicon pixel and strip tracker detector, a lead tungstate crystal electromagnetic calorimeter, and a brass and scintillator hadron calorimeter, each composed of a barrel and two endcap sections. Iron and quartz-fiber Cherenkov hadron forward (HF) calorimeters cover the range . Muons are measured in the range in gas-ionization detectors embedded in the steel flux-return yoke outside the solenoid, with detection planes made using three technologies: drift tubes, cathode strip chambers, and resistive-plate chambers. The silicon tracker measures charged particles within the range . For charged particles with and , the track resolutions are typically 1.5% in and 25–90 (45–150) in the transverse (longitudinal) impact parameter [46]. A detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [47].

3 Data selection and meson reconstruction

The  data at used in this analysis were collected in 2016, and correspond to an integrated luminosity of 186. The beam energies are 6.5 for the protons and 2.56 per nucleon for the lead nuclei. Because of the asymmetric beam conditions, particles selected in the laboratory rapidity range of () have a corresponding nucleon-nucleon center-of-mass frame rapidity range of (), with positive rapidity defined in the proton beam direction. To minimize statistical uncertainties, the quoted  meson results combine the individual values obtained for the proton and lead beam directions.

The  data are analyzed in different ranges of , where  is the number of primary charged particle tracks [46] with and . The main results are obtained with events in the high-multiplicity range . To select these events, dedicated triggers were developed, as discussed in Refs. [48, 49]. Events with are also used to estimate the possible contribution of residual back-to-back jet-like correlations. These lower-multiplicity events are selected online with a hardware-based trigger requiring two muon candidates in the muon detectors with no explicit momentum or rapidity threshold [50]. In the offline analysis, hadronic collisions are selected by requiring at least one HF calorimeter tower with more than 3 of total energy in each of the two HF detectors. Events must contain a primary vertex close to the nominal interaction point of the beams, within 15 cm along the beam direction, and 0.2 cm in the plane transverse to beam direction. The  range limits correspond to fractional inelastic cross sections from 100 to 57% for , and from 0.33 to 0.01% for , respectively.

The offline muon reconstruction algorithm starts either by finding tracks in the muon detectors, which are then fitted together with tracks reconstructed in the silicon tracker (global muons), or by extrapolating tracks from the silicon tracker to match a hit on at least one segment of the muon detectors (tracker muons). The muon candidates are required to pass the identification criteria of the particle-flow algorithm [51], which suppresses contamination of “punch-through” hadrons misidentified as muons, based on energy deposition in the calorimeters. The soft muon selection criteria are also imposed, as defined in Ref. [52], to further improve the purity of muons.

The  meson candidates are formed from pairs of oppositely charged muons, originating from a common vertex. Based on the vertex probability distributions for signal and background candidates, the probability that the dimuon pair shares a common vertex is required to be larger than 1%, lowering the background from random combinations as well as from semileptonic decays of bottom and charm hadrons. Because of the long lifetime of hadrons compared to that of  mesons, the nonprompt  meson component can be reduced by placing constraints on the pseudo-proper decay length [53]. This is defined by , where is the distance between the primary and dimuon vertices, is the Particle Data Group [54] world average value of the  meson mass (assumed for all dimuon candidates), and is the dimuon momentum. The upper limit (decreasing as a function of ) imposed on the value is based on Monte Carlo (MC) studies with simulated event samples of pythia 8.209 [55, 56], and found to reject 75–90% (from low to high ) of nonprompt  mesons, largely independent of multiplicity. The residual nonprompt  meson fraction in the data is estimated to be approximately 5% across the full  range, and its effect on the measurement is propagated as a systematic uncertainty, as described in Section 5.

4 Analysis technique

The azimuthal anisotropy of  mesons is extracted from the long-range () two-particle azimuthal correlations, following an identical procedure to that described in Refs. [21, 27, 43]. A two-dimensional (2D) correlation function is constructed by pairing each  candidate with reference primary charged-particle tracks with and (denoted “ref” particles), and calculating

{linenomath}
(1)

where and are the differences in and in the azimuthal angle () of the pair. The same-event pair distribution, , represents the yield of particle pairs normalized by the number of  candidates from the same event. The mixed-event pair yield distribution, , is constructed by pairing  candidates in each event with the reference primary charged-particle tracks from 20 different randomly selected events, from the same  range and having a primary vertex falling in the same 2 cm wide range of reconstructed coordinate. The analysis procedure is performed in each  and invariant mass () range of  candidates. A correction for the acceptance and efficiency of the  meson yields is applied, but found to have a negligible effect on the measurements. The  correlation functions averaged over (to remove short-range correlations, such as jet fragmentation) are then obtained from the 2D distributions and fitted by the first three terms of a Fourier series (including additional terms has a negligible effect on the fit results): {linenomath}

(2)

Here, are the Fourier coefficients and represents the total number of same-event pairs per  candidate for a given invariant mass interval. By assuming that is the product of single-particle anisotropies of  mesons and reference charged particles [57], , the anisotropy harmonics for  candidates can be extracted as a function of invariant mass, . With the current data, only the second order () elliptic anisotropy harmonic can be measured with meaningful statistical precision.

Figure 1: Example of fits to the invariant mass spectrum (left) and the distribution (right) in the interval 6.0–8.0 for events with .

To extract the genuine values of the  meson signal (), the contribution from background candidates () has to be subtracted from the values of all  meson candidates, as obtained in the previous step. The procedure is to first fit the dimuon mass spectrum with a function composed of three components: two Crystal Ball functions [58] with different widths but common mean and tail parameters for the  signal (the tail parameters are fixed to the values obtained from simulation), , and an exponential function to model the combinatorial background, . Then, the signal plus background distribution is fitted with: {linenomath}

(3)

where {linenomath}

(4)

Here, for the background  candidates is modeled as an exponential function of the invariant mass, and is the  signal fraction obtained from the mass spectrum fit. An example of fits to the mass spectrum and in the  interval 6.0–8.0 for the multiplicity range is shown in Fig. 1. The residual contribution of back-to-back dijets to the measured results is estimated from low-multiplicity  events and is removed from the signal after accounting for the jet yield ratio of the selected events, following a jet subtraction procedure similar to that established in Refs. [57, 21, 43]. The Fourier coefficients, , extracted from Eq. (2) for , are subtracted from the coefficients obtained in the high-multiplicity region, with {linenomath}

(5)

Here, represents the jet yield obtained by integrating the difference of the short-range () and long-range event-normalized associated yields for each multiplicity class. The ratio, /, is introduced to account for the enhanced jet correlations resulting from the selection of higher-multiplicity events. For , the jet yield ratio cannot be directly estimated from the two-particle azimuthal correlations, as the  candidates tend to have larger values than the acceptance for charged particles. Therefore, the value is assumed to be the same as that for the high-  region, where no  dependence has been observed. It was also previously observed that the values of jet yield ratio for  and strange particle species show little dependence on  over the full  range [43].

5 Systematic uncertainties

Sources of systematic uncertainties on the prompt  meson measurement include the  meson yield correction (acceptance and efficiency correction derived from pythia simulation), the nonprompt  meson contamination, the background function form, the signal and background invariant mass PDF, the jet subtraction procedure, the contamination of events containing more than one  interaction (pileup), and the trigger bias. In this Letter, the quoted uncertainties in are absolute values, and are found to have no dependence on , except those for the jet subtraction procedure. Systematic uncertainties originating from different sources are added in quadrature to obtain the overall systematic uncertainty shown as boxes in the figures.

To evaluate the uncertainties arising from the efficiency correction to the  meson yield, the values are compared to the uncorrected ones, yielding an uncertainty of 0.008. The effect on the measured due to the residual contribution from nonprompt  mesons is evaluated by varying the requirement such that the nonprompt  meson yield is doubled. The values are found not to change by more than , which is assigned as the systematic uncertainty due to the  meson yield correction. Possible differences in the rejection efficiency of nonprompt  mesons between data and simulation are investigated and found to be negligible. The systematic uncertainties from the background function form are evaluated by comparing values based on first-, second-, and third-order polynomial fits to the background distribution. The resulting  signal values are found to vary by less than 0.009. Systematic effects related to signal invariant mass PDF are found to be negligible by releasing, one at a time, the fixed tail parameters of the Crystal Ball functions. The variation of , while changing the background invariant mass PDF to a second- or third-order polynomial function is also found to be negligible. In the jet subtraction procedure, the statistical precision of the jet yield ratio is limited. The results are found to be consistent within to (increasing with ) when varying the jet yield ratio by its statistical uncertainty. The systematic uncertainties from the potential pileup effect and the trigger bias are taken to be the same as for inclusive charged particles in Ref. [49], where they can be established with good statistical precision. The pileup and trigger bias uncertainties are negligible compared to the other sources of systematic uncertainties, as the fraction of residual pileup events is only a few % and the trigger efficiency is close to 100%.

6 Results

Figure 2 shows the results of prompt  mesons at forward rapidities ( or ) for high-multiplicity ()  collisions, covering a  range from 0.2 to 10. Results obtained separately for  meson rapidity in the Pb- and p-going direction are compared, and found to be consistent within statistical uncertainties. Thus, as mentioned earlier, combined values are presented for the best statistical precision. The results for  and  hadrons (light, strange-flavor), and prompt  mesons (open heavy-flavor), reported in a previous CMS publication [43] for the midrapidity region , are also shown for comparison.

Figure 2: The results of the prompt  mesons at forward rapidities ( or ), as a function of  in the multiplicity range for  collisions at . Data for  and  hadrons, and prompt  mesons at midrapidity () from previous CMS measurements [43] are also shown for comparison. The error bars correspond to statistical uncertainties, while the shaded areas denote the systematic uncertainties.

Positive prompt  meson values are observed over a wide range from about 2 to 8. The prompt  meson results show a trend of first increasing up to and then decreasing toward higher . This observed trend appears to be in common with the other hadron species shown. In the range below 5, the values for  and  mesons are consistent with each other within the uncertainties, while an indication of smaller values for  mesons than that for  mesons is seen for . Over the full range, the signal values for both  and  hadrons are smaller than those for  and  hadrons. This observation is consistent with the earlier conclusion that charm quarks develop a weaker collective dynamics than light quarks in small systems [43], unlike what is seen in AA collisions. Because of experimental limitation, values for the prompt  meson and the other meson species are not compared within the same rapidity range, possibly affecting their comparison. The rapidity dependence of values for charged particles in  collisions has been measured [59, 60], suggesting up to around 15% variation from to .

Figure 3: Upper: the values for prompt  mesons at forward rapidities ( or ), as well as for  and  hadrons, and prompt  mesons at midrapidity (), as a function of  for  collisions at with . Lower: the -normalized results. The ,  and   data are taken from Ref. [43]. The error bars correspond to statistical uncertainties, while the shaded areas denote the systematic uncertainties.

To better study the elliptic flow signal coming purely from long-range collective correlations, the   results are corrected for residual jet correlations. The resulting () values are shown in Fig. 3 (upper) for prompt  mesons as a function of  with , and compared to similarly corrected , , and  hadron results [43]. The effect of the correction for all particle species is most noticeable at very high , while the overall  dependence of the data remains unchanged. The  mesons have a larger correction applied to their values (possibly because  mesons are more correlated with the bulk multiplicity, and thus are biased toward stronger jet correlations due to the selection of high multiplicities) and their values after the correction tend to converge to those of the prompt  and  mesons at high .

A recent model calculation of   in  collisions, based on final-state interactions between produced charm quarks and a QGP medium, suggests a very small signal of less than 0.01 [45]. This calculation indicates that additional contributions, e.g., those from initial-state interactions, may be needed to account for the observed signal of prompt  mesons reported in this Letter.

Motivated by the possible formation of a hydrodynamically expanding QGP medium in small systems, the elliptic flow signals for , ,  and  hadrons are compared as a function of transverse kinetic energy () in Fig. 3 (lower), to account for the mass difference among the four hadron species [61, 62]. Here, the values of and  are both divided by the number of constituent quarks, , to represent the collective flow signal at the partonic level in the context of the quark coalescence model [63, 64, 65], which postulates that the elliptic flow signal of a hadron is a sum of contributions from individual constituent quark flow values. As was previously reported in  collisions [27, 43], a scaling of -normalized values is observed between the  meson and  baryon, shown in Fig. 3 (lower). This scaling between light baryon and meson species systems produced in the collision (known as the number-of-constituent-quark or NCQ scaling) was first discovered in AA colliding systems [66, 61, 62], indicating that collectivity is first developed among the partons, which later recombine into final-state hadrons. The elliptic flow signal per quark () for prompt  mesons at low range is consistent with those of , , and prompt  hadrons within large statistical uncertainties for the current data. There is a hint that the prompt  meson data tend to fall on the same trend as those of  and  baryons, all of which are above the prompt  meson data. A more definitive conclusion could be drawn with future high precision data. For , the for prompt  and  mesons are consistently below that of the  meson. An indication of smaller values for  mesons than for  mesons is seen for . As  mesons contain two charm quarks, while  mesons contain a charm and a light-flavor quark, this observation would be consistent with a weaker collective behavior of heavy-flavor quarks than light quarks, possibly a consequence of the much smaller size of the collision system. Future data with improved precision will provide crucial insights to fully constrain the collective behavior of light- and heavy-flavor quarks in high-multiplicity, small systems.

7 Summary

In summary, the elliptic flow harmonic () for prompt  mesons in high-multiplicity proton-lead () collisions at is presented as a function of transverse momentum (). Positive values are observed for prompt  mesons at forward rapidity ( or ) over a wide range (). This observation provides evidence for charm quark collectivity in high-multiplicity  collisions, similar to that first observed for light-flavor hadrons. The observed ordering of among light-flavor, open and hidden heavy-flavor hadrons at intermediate and high- regions (e.g., above 4) adds support to the earlier conclusion that heavy quarks exhibit weaker collective behavior than light quarks or gluons in small systems, unlike what is found in AA collisions. For particle transverse kinetic energy per constituent quark values less than 1, the of prompt  mesons is consistent with prompt ,  and  hadrons, within current uncertainties. A model calculation based on final-state interactions between charm quarks and a QGP medium in  collisions significantly underestimates the measured prompt   signal. The new prompt  meson results, together with previous results for light-flavor and open heavy-flavor hadrons, provide novel insights into the dynamics of the heavy quarks produced in small systems that lead to high final-state multiplicities.

Acknowledgments

We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA).

Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science - EOS” - be.h project n. 30820817; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület (“Momentum”) Programme and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).

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S. Ahuja, C.A. Bernardes, L. Calligaris, T.R. Fernandez Perez Tomei, E.M. Gregores, P.G. Mercadante, S.F. Novaes, SandraS. Padula Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang\@textsuperscript5, X. Gao\@textsuperscript5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen\@textsuperscript6, A. Spiezia, J. Tao, Z. Wang, E. Yazgan, H. Zhang, S. Zhang\@textsuperscript6, J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang, Z. Xu Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez, C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov\@textsuperscript7, T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic
M. Finger\@textsuperscript8, M. Finger Jr.\@textsuperscript8 Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
Y. Assran\@textsuperscript9\@textsuperscript10, S. Elgammal\@textsuperscript10, S. Khalil\@textsuperscript11 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M. Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki, Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T. Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup, E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
A. Abdulsalam\@textsuperscript12, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C. Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C. Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, J. Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram\@textsuperscript13, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov, C. Collard, E. Conte\@textsuperscript13, J.-C. Fontaine\@textsuperscript13, D. Gelé, U. Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L. Mirabito, S. Perries, A. Popov\@textsuperscript14, V. Sordini, G. Touquet, M. Vander Donckt, S. Viret Georgian Technical University, Tbilisi, Georgia
T. Toriashvili\@textsuperscript15 Tbilisi State University, Tbilisi, Georgia
I. Bagaturia\@textsuperscript16 RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H. Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A. Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl\@textsuperscript17 Deutsches Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K. Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin Anuar, K. Borras\@textsuperscript18, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G. Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo\@textsuperscript19, A. Geiser, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, J. Hauk, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann\@textsuperscript20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V. Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P. Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A. Vagnerini, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A. Ebrahimi, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange, D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D. Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F.M. Stober, M. Stöver, A. Vanhoefer, B. Vormwald, I. Zoi Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M. Giffels, M.A. Harrendorf, F. Hartmann\@textsuperscript17, S.M. Heindl, U. Husemann, F. Kassel\@textsuperscript17, I. Katkov\@textsuperscript14, S. Kudella, S. Mitra, M.U. Mozer, Th. Müller, M. Plagge, G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, S. Kesisoglou, P. Kontaxakis, A. Panagiotou, I. Papavergou, N. Saoulidou, E. Tziaferi, K. Vellidis National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D. Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary
M. Bartók\@textsuperscript21, M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath\@textsuperscript22, Á. Hunyadi, F. Sikler, T.Á. Vámi, V. Veszpremi, G. Vesztergombi Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi\@textsuperscript23, A. Makovec, J. Molnar, Z. Szillasi Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati\@textsuperscript24, C. Kar, P. Mal, K. Mandal, A. Nayak\@textsuperscript25, D.K. Sahoo\@textsuperscript24, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R. Gupta, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A. Mehta, K. Sandeep, S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S. Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj\@textsuperscript26, M. Bharti\@textsuperscript26, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep\@textsuperscript26, D. Bhowmik, S. Dey, S. Dutt\@textsuperscript26, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A. Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, G. Saha, S. Sarkar, M. Sharan, B. Singh\@textsuperscript26, S. Thakur\@textsuperscript26 Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, P.K. Netrakanti, L.M. Pant, P. Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, B. Sutar, RavindraKumar Verma Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S. Karmakar, S. Kumar, M. Maity\@textsuperscript27, G. Majumder, K. Mazumdar, N. Sahoo, T. Sarkar\@textsuperscript27 Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani\@textsuperscript28, E. Eskandari Tadavani, S.M. Etesami\@textsuperscript28, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh\@textsuperscript29, M. Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari , Università di Bari , Politecnico di Bari , Bari, Italy
M. Abbrescia, C. Calabria, A. Colaleo, D. Creanza, L. Cristella, N. De Filippis, M. De Palma, A. Di Florio, F. Errico, L. Fiore, A. Gelmi, G. Iaselli, M. Ince, S. Lezki, G. Maggi, M. Maggi, G. Miniello, S. My, S. Nuzzo, A. Pompili, G. Pugliese, R. Radogna, A. Ranieri, G. Selvaggi, A. Sharma, L. Silvestris, R. Venditti, P. Verwilligen, G. Zito INFN Sezione di Bologna , Università di Bologna , Bologna, Italy
G. Abbiendi, C. Battilana, D. Bonacorsi, L. Borgonovi, S. Braibant-Giacomelli, R. Campanini, P. Capiluppi, A. Castro, F.R. Cavallo, S.S. Chhibra, C. Ciocca, G. Codispoti, M. Cuffiani, G.M. Dallavalle, F. Fabbri, A. Fanfani, E. Fontanesi, P. Giacomelli, C. Grandi, L. Guiducci, F. Iemmi, S. Lo Meo, S. Marcellini, G. Masetti, A. Montanari, F.L. Navarria, A. Perrotta, F. Primavera\@textsuperscript17, T. Rovelli, G.P. Siroli, N. Tosi INFN Sezione di Catania , Università di Catania , Catania, Italy
S. Albergo, A. Di Mattia, R. Potenza, A. Tricomi, C. Tuve INFN Sezione di Firenze , Università di Firenze , Firenze, Italy
G. Barbagli, K. Chatterjee, V. Ciulli, C. Civinini, R. D’Alessandro, E. Focardi, G. Latino, P. Lenzi, M. Meschini, S. Paoletti, L. Russo\@textsuperscript30, G. Sguazzoni, D. Strom, L. Viliani INFN Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genova , Università di Genova , Genova, Italy
F. Ferro, F. Ravera, E. Robutti, S. Tosi INFN Sezione di Milano-Bicocca , Università di Milano-Bicocca , Milano, Italy
A. Benaglia, A. Beschi, F. Brivio, V. Ciriolo\@textsuperscript17, S. Di Guida\@textsuperscript17, M.E. Dinardo, S. Fiorendi, S. Gennai, A. Ghezzi, P. Govoni, M. Malberti, S. Malvezzi, A. Massironi, D. Menasce, F. Monti, L. Moroni, M. Paganoni, D. Pedrini, S. Ragazzi, T. Tabarelli de Fatis, D. Zuolo INFN Sezione di Napoli , Università di Napoli ’Federico II’ , Napoli, Italy, Università della Basilicata , Potenza, Italy, Università G. Marconi , Roma, Italy
S. Buontempo, N. Cavallo, A. De Iorio, A. Di Crescenzo, F. Fabozzi, F. Fienga, G. Galati, A.O.M. Iorio, W.A. Khan, L. Lista, S. Meola\@textsuperscript17, P. Paolucci\@textsuperscript17, C. Sciacca, E. Voevodina INFN Sezione di Padova , Università di Padova , Padova, Italy, Università di Trento , Trento, Italy
P. Azzi, N. Bacchetta, D. Bisello, A. Boletti, A. Bragagnolo, R. Carlin, P. Checchia, M. Dall’Osso, P. De Castro Manzano, T. Dorigo, U. Dosselli, F. Gasparini, U. Gasparini, A. Gozzelino, S.Y. Hoh, S. Lacaprara, P. Lujan, M. Margoni, A.T. Meneguzzo, J. Pazzini, P. Ronchese, R. Rossin, F. Simonetto, A. Tiko, E. Torassa, M. Zanetti, P. Zotto, G. Zumerle INFN Sezione di Pavia , Università di Pavia , Pavia, Italy
A. Braghieri, A. Magnani, P. Montagna, S.P. Ratti, V. Re, M. Ressegotti, C. Riccardi, P. Salvini, I. Vai, P. Vitulo INFN Sezione di Perugia , Università di Perugia , Perugia, Italy
M. Biasini, G.M. Bilei, C. Cecchi, D. Ciangottini, L. Fanò, P. Lariccia, R. Leonardi, E. Manoni, G. Mantovani, V. Mariani, M. Menichelli, A. Rossi, A. Santocchia, D. Spiga INFN Sezione di Pisa , Università di Pisa , Scuola Normale Superiore di Pisa , Pisa, Italy
K. Androsov, P. Azzurri, G. Bagliesi, L. Bianchini, T. Boccali, L. Borrello, R. Castaldi, M.A. Ciocci, R. Dell’Orso, G. Fedi, F. Fiori, L. Giannini, A. Giassi, M.T. Grippo, F. Ligabue, E. Manca, G. Mandorli, A. Messineo, F. Palla, A. Rizzi, P. Spagnolo, R. Tenchini, G. Tonelli, A. Venturi, P.G. Verdini INFN Sezione di Roma , Sapienza Università di Roma , Rome, Italy
L. Barone, F. Cavallari, M. Cipriani, D. Del Re, E. Di Marco, M. Diemoz, S. Gelli, E. Longo, B. Marzocchi, P. Meridiani, G. Organtini, F. Pandolfi, R. Paramatti, F. Preiato, S. Rahatlou, C. Rovelli, F. Santanastasio INFN Sezione di Torino , Università di Torino , Torino, Italy, Università del Piemonte Orientale , Novara, Italy
N. Amapane, R. Arcidiacono, S. Argiro, M. Arneodo, N. Bartosik, R. Bellan, C. Biino, N. Cartiglia, F. Cenna, S. Cometti, M. Costa, R. Covarelli, N. Demaria, B. Kiani, C. Mariotti, S. Maselli, E. Migliore, V. Monaco, E. Monteil, M. Monteno, M.M. Obertino, L. Pacher