PHYSICAL REVIEW D 99, 052005 (2019) pffiffi Search for long-lived particles produced in pp collisions at s = 13 TeV that decay into displaced hadronic jets in the ATLAS muon spectrometer M. Aaboud et al.* (ATLAS Collaboration) (Received 21 November 2018; published 15 March 2019) A search for the decay of neutral, weakly interacting, long-lived particles using data collected by the ATLAS detector at the LHC is presented. The analysis in this paper uses 36.1 fb−1 of proton-proton pffiffiffi collision data at s ¼ 13 TeV recorded in 2015–2016. The search employs techniques for reconstructing vertices of long-lived particles decaying into jets in the muon spectrometer exploiting a two-vertex strategy and a novel technique that requires only one vertex in association with additional activity in the detector that improves the sensitivity for longer lifetimes. The observed numbers of events are consistent with the expected background and limits for several benchmark signals are determined. DOI: 10.1103/PhysRevD.99.052005 I. INTRODUCTION by the ATLAS pffiffiand ffi LHCb Collaborations in proton-proton collisions at s ¼ 7 TeV [27,28], pffiffiffi by the ATLAS, CMS The discovery of the Higgs boson at the LHC completed the Standard Model (SM) of elementary particles and and LHCb Collaborations at s ¼ 8 TeVp[29–34] ffiffiffi and focused attention on the many central features of our more recently by the CMS Collaboration at s ¼ 13 TeV universe that the SM does not address: dark matter, neutrino [35]. To date, no search has observed evidence of BSM, mass, matter-antimatter asymmetry (baryogenesis), and neutral LLPs. the hierarchy problem (naturalness). Many beyond the This paper describes a search for neutral pffiffiffi LLPs produced Standard Model (BSM) theoretical constructs proposed in proton-proton interactions at s ¼ 13 TeV, using −1 in the past few years that address these phenomena predict 36.1 fb of data recorded by the ATLAS detector at the the existence of long-lived particles (LLPs) with macro- LHC during 2015 and 2016. Decays of LLPs can result scopic decay lengths that are limited only by big bang in secondary decay vertices (displaced vertices) that are nucleosynthesis to about cτ ≲ 107 –108 m, where τ is the highly displaced from the IP. The present paper focuses on proper lifetime of the LLP [1]. Examples include super- LLP decays reconstructed in the muon spectrometer. Three symmetric (SUSY) models such as mini-split SUSY [2,3], different analysis strategies are considered, with each gauge-mediated SUSY breaking [4], R-parity-violating strategy targeting a specific event topology. Two single- SUSY [5,6] and stealth SUSY [7,8]; models addressing vertex strategies are based on methodologies presented in the hierarchy problem such as neutral naturalness [9–12] Ref. [36], and the third strategy is an inclusive search for and hidden valleys [13,14]; models addressing dark matter two displaced vertices in the muon spectrometer. [15–19], and the matter-antimatter asymmetry of the This work significantly extends the mean proper lifetime universe [20–22]; and models that generate neutrino masses (cτ) range of the ATLAS search for a light scalar boson [23,24]. Many of these theoretical models result in neutral decaying into long-lived neutral particles beyond that at pffiffiffi LLPs, which may be produced in the proton-proton s ¼ 8 TeV in 20.3 fb−1 of 2012 proton-proton collision collisions of the LHC and decay back into SM particles data [29], which covered the cτ region 1–100 m. far from the interaction point (IP). Additionally, it extends the range of excluded proper life- Searches for LLPs decaying into finalpffiffiffi states containing times beyond that of a recent ATLAS analysis [32] that jets were carried out at the Tevatron ( s ¼ 1.96 TeV) by searches for displaced decays in the hadronic calorimeter both the CDF [25] and D0 [26] Collaborations, at the LHC and uses the same scalar boson model and mass points. The paper first describes the ATLAS detector in Sec. II, * Full author list given at the end of the article. followed by the event selection strategy in Sec. III, the benchmark models in Sec. IV, and the data and simulation Published by the American Physical Society under the terms of samples in Sec. V. The specialized trigger and reconstruction the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to algorithms are discussed in Sec. VI, followed by a descrip- the author(s) and the published article’s title, journal citation, tion of the baseline selection applied to all events in Sec. VII. and DOI. Funded by SCOAP3. Sections VIII and IX outline the three search topologies. 2470-0010=2019=99(5)=052005(36) 052005-1 © 2019 CERN, for the ATLAS Collaboration M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) Systematic uncertainties are summarized in Sec. X and The first two RPC stations, which are radially separated by results for all three topologies are presented in Sec. XI. The 0.5 m, start at a radius of either 7 m (large sectors) or 8 m summary and conclusions are given in Sec. XII. (small sectors). The third station is located at a radius of either 9 m (large sectors) or 10 m (small sectors). In the end caps, the first TGC station is located at jzj ¼ 13 m. The other II. ATLAS DETECTOR two stations start at jzj ¼ 14 m and jzj ¼ 14.5 m, respec- The ATLAS detector [37], which has nearly 4π steradian tively. The muon trigger system covers the range jηj < 2.4. coverage, is a multipurpose detector consisting of an inner The muon tracking chamber system covers the region jηj < tracking detector (ID) surrounded by a superconducting 2.7 with three layers of monitored drift tubes (MDT), solenoid, electromagnetic and hadronic calorimeters, complemented by cathode strip chambers (CSC) in the and a muon spectrometer (MS) based on three large air- forward region. The MDT chambers consist of two multi- core toroidal superconducting magnets, each with eight layers separated by a distance ranging from 6.5 mm to coils. The ID covers the range 0.03 m < r < 1.1 m and 317 mm. Each multilayer consists of three or four layers of jzj < 3.5 m.1 It consists of a silicon pixel detector, a silicon drift tubes. The individual drift tubes are 30 mm in diameter microstrip detector, and a straw-tube transition-radiation and have a length of 2–5 m depending on the location of the tracker. Together, the three systems provide precision chamber in the spectrometer. In each multilayer the charged- tracking of charged particles for jηj < 2.5. particle track segment can be reconstructed by finding the The calorimeter system covers the pseudorapidity range line that is tangent to the drift circles. These segments are jηj < 4.9. It consists of a high-granularity lead/liquid-argon local measurements of the position and direction of the electromagnetic calorimeter (ECal) surrounded by a had- charged particle. Because the tubes are 2–5 m in length with ronic calorimeter (HCal). Within the region jηj < 3.2, the a direction along ϕ, the MDT measurement provides only a ECal comprises liquid-argon (LAr) barrel and end cap very coarse ϕ position of the track hit. In order to reconstruct electromagnetic calorimeters with lead absorbers. An addi- the ϕ position and direction, the MDT measurements are tional thin LAr presampler covering jηj < 1.8 is used to combined with the ϕ coordinate measurements from the correct for energy loss in material upstream of the calo- trigger chambers. rimeters. The ECal extends from 1.5 m to 2.0 m in r in the The ATLAS trigger and data acquisition system [38] barrel and from 3.6 m to 4.25 m in jzj in the end caps. consists of a hardware-based first-level trigger (L1) followed The HCal is a steel/scintillator-tile calorimeter that is by a software-based high-level trigger (HLT) that reduces segmented into three barrel structures within jηj < 1.7, the rate of recorded events for offline storage to 1 kHz. and two copper/LAr hadronic calorimeters in the end cap The implementation of the L1 muon trigger logic is (1.5 < jηj < 3.2). The HCal covers the region from 2.25 m similar for both the RPC and TGC systems. Each of the three to 4.25 m in r in the barrel (although the HCal active planes of the RPC system and the two outermost planes of material extends only up to 3.9 m) and from 4.3 m to the TGC system consist of a doublet of independent detector 6.05 m in jzj in the end caps. The solid angle coverage is layers. The first TGC plane contains three detector layers. completed with forward copper/LAr and tungsten/LAr A low-pT (<10 GeV) muon region-of-interest (RoI) is calorimeter modules optimized for electromagnetic and generated by requiring a coincidence of hits in at least three hadronic measurements, respectively. Together the ECal of the four layers of the two inner RPC planes for the barrel. and HCal have a thickness of 9.7 interaction lengths In the end caps, the trigger requires hits in the two outer TGC at η ¼ 0. planes. A high-pT muon RoI requires additional hits in at The MS comprises three stations of separate trigger and least one of the two layers of the outer RPC plane for the tracking chambers that measure the deflection of muons in barrel, while for the end caps, hits in two of the three layers of a magnetic field generated by the air-core toroid magnets. the innermost TGC layer are required. The muon RoIs have a The barrel chamber system is subdivided into 16 sectors: 8 spatial extent of 0.2 × 0.2 in Δη × Δϕ in the MS barrel and large sectors (between the magnet coils) and 8 small sectors 0.1 × 0.1 in Δη × Δϕ in the MS end caps. Only the two (inside the magnet coils). Three stations of resistive plate highest-pT RoIs per MS sector are used by the HLT. chambers (RPC) and thin gap chambers (TGC) are used The L1 calorimeter trigger is based on information from for triggering in the MS barrel and end caps, respectively. the calorimeter elements within projective regions, called trigger towers. The trigger towers have a size of approx- 1 imately 0.1 in Δη and Δϕ in the central part of the ATLAS uses a right-handed coordinate system with its origin at the nominal IP in the center of the detector and the z axis along calorimeter, jηj < 2.5, and are larger and less uniform in the beam pipe. The x axis points from the IP to the center of the the more forward region. LHC ring, and the y axis points upwards. Cylindrical coordinates ðr; ϕÞ are used in the transverse plane, where ϕ is the azimuthal III. ANALYSIS STRATEGY angle around the z axis. The pseudorapidity is defined in terms of the polar angle θ as η ¼ p − ln tanðθ=2Þ. Angular ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi distance is The analysis presented in this paper searches for events measured in units of ΔR ≡ ðΔηÞ2 þ ðΔϕÞ2 . with two displaced vertices in the MS, or one displaced 052005-2 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) TABLE I. Topologies considered in this paper, corresponding basic event selection and benchmark models. Strategy Basic event selection Benchmarks 2MSVx at least 2 MS vertices scalar portal, Higgs portal baryogenesis, stealth SUSY 1MSVx+Jets exactly 1 MS vertex at least 2 jets stealth SUSY with ET > 150 GeV 1MSVx þ Emiss T exactly 1 MS vertex Emiss T > 30 GeV scalar portal with mΦ ¼ 125 GeV, Higgs portal baryogenesis vertex in the MS in association with additional activity in showers not contained in the calorimeter volume (punch- the detector. Three separate strategies are studied, defined through jets) resulting in tracks reconstructed in the MS. by the number of MS vertices and additional selection Multijet events that contain vertices in the MS would have criteria. The benchmark models that motivate these strat- ID tracks and jets that point towards the displaced MS egies are discussed in detail in Sec. IV. vertex as well as inwards to the IP. To reduce the acceptance Candidate events are selected by the Muon RoI Cluster of fake vertices from multijet events, vertices are required to trigger [39] that requires a cluster of three (four) muon RoIs be isolated from ID tracks and calorimeter jets. Additional in the barrel (end caps). No jet or track isolation require- background, referred to in this paper as noncollision ments are applied at trigger level. Displaced vertices are then background, can be generated by electronic noise in the reconstructed using a dedicated MS vertex reconstruction MDT and RPC/TGC chambers, by cosmic-ray muons, by algorithm [40]. For each strategy considered in this paper multijet events with mismeasured jets and by machine- additional selection criteria, optimized by comparing signal induced background [41]. This last contribution, usually to background events, are used to maximize the analysis referred to as beam-induced background, is composed of sensitivity. particles produced in the hadronic and electromagnetic The simplest strategy requires at least two MS vertices showers caused by beam protons interacting with collima- (2MSVx), and it is inclusive of any other activity in the tors or residual gas molecules inside the vacuum pipe. event. The other two strategies require exactly one MS To avoid unintended biasing of the results, the signal vertex, with additional requirements on associated objects regions of the 2MSVx and 1MSVx+AO strategies were (1MSVx+AO). The first requires exactly one MS vertex blinded during the analysis development. and two prompt jets (1MSVx+Jets), targeting models where prompt jets are produced together with the LLP, IV. DESCRIPTION OF BENCHMARK MODELS as expected in the stealth SUSY scenarios. In these cases, the two prompt jets can also contribute to signal event Although the event selections outlined in Sec. III are selection. The second requires a small amount of missing sensitive to a large variety of models, this paper interprets transverse momentum (denoted by Emiss the results in terms of three different benchmark models. T ) in addition to the single displaced vertex (1MSVx þ Emiss The first, shown in Fig. 1(a), is a scalar portal model [14], T ) and targets mod- els that do not predict significant activity in addition to where a SM-like Higgs or lower/higher-mass boson (Φ) LLPs, such as from decays of “SM-like” Higgs bosons into decays into two long-lived scalars (s). Figure 1(b) shows long-lived neutral scalar particle pairs. In fact, since the the second model, Higgs portal baryogenesis [22], in tracks originating from vertices in the MS are not consid- which a SM-like Higgs boson (h) decays into long-lived Majorana fermions χ that decay into fermions, violating ered in the Emiss T computation, for these models the Emiss T in baryon and/or lepton number conservation. The last model, signal events is sensitive to the Higgs boson pT , which is shown in Fig. 1(c), is a stealth SUSY model [7,8] where typically of the order of tens of GeV. For signal vertices, if the second LLP has decayed in the ID or calorimeter the the long-lived singlino (S̃) is produced by a gluino (g̃) in Emiss vector tends to be aligned with the direction of the association with a prompt gluon-jet (g). The singlino decay T produces two gluons and a light gravitino. displaced vertex, measured from the origin of the detector The decay channels, the relative masses and lifetimes coordinate system. However, if the decay of the second generated for each model, as well as details about the LLP occur beyond the MS there is no missing energy. Monte Carlo (MC) event generation are described in Sec. V. Therefore, the angle in the transverse plane between the vertex and the Emiss T direction can contribute to the signal event selection. The three analysis strategies are summa- A. Scalar portal rized in Table I, together with the theoretical benchmark A theoretically popular way of introducing long-lived, models used in this paper. neutral particles to the SM is through a hidden sector that The main source of background to LLPs decaying into weakly couples to the SM. For example, scalar (Higgs) hadronic jets in the MS is from hadronic or electromagnetic portals [13,14,42], where the Higgs boson weakly mixes 052005-3 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) f p f p f s χ Φ f¯ h f s f χ f p f f¯ p f (a) (b) (c) FIG. 1. Diagrams of the benchmark models studied in this paper: (a) scalar portal model, (b) Higgs portal baryogenesis model, and (c) stealth SUSY model. The LLPs in these processes are represented by double lines and labeled (a) s, (b) χ, and (c) S̃. In the stealth SUSY model, G̃ is the gravitino and S is the singlet. The final-state SM fermions are labeled as f, and the gluons as g. with a hidden-sector scalar, can result in pair production of decays of weak-scale states have been shown to have direct hidden-sector scalars or pseudoscalars that carry no SM testability at colliders [45–47]. quantum numbers. The branching fraction limit for SM In the baryogenesis model considered for this paper [22], Higgs boson decays into undetected particles is currently at the lowest-dimension operator coupling a singlet χ to the the 25% level [43] (assuming SM-like Higgs boson SM is the Higgs portal. The simplest realization of this production and width), potentially allowing sizable branch- interaction is with a scalar, Φ, that mixes with the SM ing fractions for decays into non-SM particles. Higgs boson [48]. If Φ has a Yukawa coupling to a pair Moreover, models of neutral naturalness [44] are generic of χ, this leads to the Higgs portal production of χ via extensions of hidden-valley portal models where the scalar exchange of a single SM-like Higgs boson after mixing, masses can be very low, typically 5–15 GeV. To date, no pp → h → χχ, as shown in Fig. 1(b). Since LHC experi- LHC analysis has explored this model. ments have established the existence of a SM-like Higgs The mechanism for LLP production in scalar decays is boson with a mass of 125 GeV, while the other possibilities shown in Fig. 1(a). Here, a scalar boson Φ decays with are more model-dependent, the model used here assumes some effective coupling into a pair of long-lived scalars, s. the minimal spectrum where the Φ scalar is heavy and The scalars s subsequently decay into SM particles. Since decouples, and focuses on the production channel via the this model assumes that the couplings of the scalar to SM SM Higgs portal. particles are determined by a Yukawa coupling, each long- For the production of the χ through the Higgs portal, two lived scalar decays mainly into heavy fermions, bb̄, cc̄, and different regimes can be identified. (i) mχ < mh =2: in this region the dominant production τþ τ− . The branching fractions of these decays depend on mechanism is through an on-shell Higgs boson. The the mass of the scalar, ms , but for ms ≳ 25 GeV they are χ production at 13 TeV is expected to be copious, almost constant and equal to 85%, 5%, and 8%. Oð10 pbÞ, and the constraints set by the current The branching fraction for Φ decaying into a pair LHC searches are correspondingly strong. There are of hidden-sector particles is not constrained in these also indirect limits on the non-SM decay branching models. It is therefore interesting to focus both on Higgs fraction of the Higgs boson based on global fits boson decays into LLPs, where Φ is a SM-like Higgs [49,50]. Despite all these strong constraints, the on- boson, and on other Φ mass regions previously unexplored shell region is still very interesting due to the sizable for decays into LLPs. branching fractions allowed for the Higgs decays into BSM particles [49,50]. B. Higgs portal baryogenesis (ii) mχ > mh =2: in this region the Higgs boson is off- The origin of the cosmic asymmetric abundance of shell and the signal rate falls rapidly with increasing baryons remains one of the most prominent questions that mχ , even for large mixing. The cross section demand physics beyond the SM. Several baryogenesis expected for a χ mass of 100 GeV is about 7 fb. mechanisms have been proposed, but electroweak baryo- The decay modes of the χ must violate baryon and/or genesis is one of the few with signatures that could be lepton number conservation, which generates the baryonic explored at the LHC energies. In addition to better asymmetry. The lowest-dimensional interactions of this testability, baryogenesis based on new weak-scale particles type allow χ to decay into three SM fermions. The decay is also theoretically appealing since it can naturally connect channels used in this paper, χ → τþ τ− νl , cbs, lþ c̄b, νbb̄, new physics addressing the weak-scale hierarchy problem are examples of three types of couplings inspired by with the dynamics responsible for generating the baryon R-parity-violating SM fermion trilinear operators that asymmetry. A few examples of low-scale (≲ TeV) baryo- can couple to χ [22]. The charge conjugates of these decay genesis models that generate the baryon asymmetry via the channels are also considered. Decays into final states as 052005-4 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) cbb or css are not possible since the R-parity-violating and therefore have a negligible signal contamination. The operator containing two down-type quarks with the same zero-bias trigger runs throughout ATLAS data taking, so flavor is not allowed. Mixed cases such as cbd or cds are these data are acquired with the same beam conditions possible, but they are not considered in this paper since present in normal physics data and can be used to study the their kinematics is similar to the cbs channel and give expected background. Due to the very high output event similar results. rate, the zero-bias trigger is prescaled and only a fraction of the total events are recorded. For this reason, the integrated C. Stealth SUSY luminosity acquired is much lower than the total collected Stealth SUSY models [7,8] are a class of R-parity- during 2015 and 2016 data taking and corresponds to conserving SUSY models that do not have large Emiss 1.1 μb−1 and 12 μb−1 for the two periods, respectively. T signatures. While this can be accomplished in many differ- Monte Carlo simulation samples were produced for all ent ways, this search explores a model that involves adding a models considered in this paper. The masses, summarized hidden-sector (stealth) singlet superfield S at the electro- in Table II, were chosen to span the accessible parameter weak scale, which has a superpartner singlino S̃. By weakly space. For the stealth SUSY model, the singlino and singlet coupling the hidden sector to the minimal supersymmetric masses were set to 100 and 90 GeV, respectively. These Standard Model [51], the mass-splitting between S and S̃ values were recommended by the authors of the model as a (δM) is small, assuming low-scale SUSY breaking. High- good representative choice [7]. The small mass-splitting scale SUSY breaking also can be consistent with small mass between the singlino and singlet ensures that the gravitino splitting and stealth SUSY, although this requires a more carries off very little momentum. The mean proper lifetime complex model and is not considered in this search [8]. of each sample is tuned to obtain a mean lab-frame decay The SUSY decay chain ends with the singlino decaying length of 5 m. This choice maximizes the distribution of into a singlet plus a low-mass gravitino G̃, where the gravitino decays throughout the ATLAS detector volume. The mean carries off very little energy and the singlet promptly decays proper lifetime used for the generation of the samples is into two gluons. The effective decay processes are g̃ → S̃g within a range of 0.17–5.55 m, depending on the sample. For each MC sample, 400 000 events are produced. (prompt), S̃ → SG̃ (not prompt), and S → gg (prompt), Since the analysis is sensitive to a wide range of mean where the gravitino is treated as massless. This scenario proper lifetimes, and the generation of many samples to results in one prompt gluon and two displaced gluons per cover a broad lifetime range would be extremely CPU-time gluino decay. Since R-parity is assumed to be conserved, each consuming, a toy MC strategy was adopted to extrapolate event necessarily produces two gluinos, resulting in two the number of expected events to the range of mean proper displaced vertices. A representative diagram of this process lifetimes between 0 and 1000 m. For each LLP in the is shown in Fig. 1(c). The simplified stealth SUSY model MC sample a random decay position sampled from an considered in this paper assumes that all squarks are decoupled. The decay width (and, consequently, the lifetime) of the TABLE II. Mass parameters for the simulated scalar portal, pffiffiffiffi by both the δM4 and 2the SUSY- singlino is determined Higgs portal baryogenesis, and stealth SUSY models. breaking scale F: pΓffiffiffiffi G̃ ≈ mS̃ ðδMÞ =πF [7]. The S̃→S Model mϕ [GeV] ms [GeV] SUSY-breaking scale F is not a fixed parameter, and thus the singlino has the possibility of traveling an Scalar portal 100 8, 25 125 5, 8, 15, 25, 40 appreciable distance through the detector, leading to a 200 8, 25, 50 significantly displaced vertex. 400 50, 100 600 50, 150 V. DATA AND SIMULATION SAMPLES 1000 50, 150, 400 pffiffiffi The analysis presented in this paper uses s ¼ 13 TeV mχ [GeV] χ decay channel pp collision data recorded by the ATLAS detector with Higgs portal 10 τþ τ− νl , cbs, lþ c̄b, νbb̄ stable LHC beams during the 2015 and 2016 data-taking baryogenesis 30 periods. After data quality requirements, the total integrated 50 luminosity is 3.2 fb−1 and 32.9 fb−1 for 2015 and 2016, 100 respectively. mg̃ [GeV] mS̃ , mS [GeV] Zero-bias data are used to estimate the expected back- Stealth SUSY 250 100, 90 ground for the 2MSVx strategy and potential contamina- 500 tion by noncollision background in the 1MSVx+AO 800 strategies. These data are acquired with a special trigger 1200 1500 which fires on the bunch crossing that occurs one LHC 2000 revolution after a low-threshold calorimeter-based trigger 052005-5 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) exponential distribution was generated. The physical decay clusters of neighboring energy deposits in the calorimeter position in the detector was then calculated for each particle cells containing a significant energy above a noise thresh- using the LLP four-momenta from the simulated MC old [63,64] provide input to the anti-kt algorithm. The samples. The overall probability of the event to satisfy calorimeter cell energies are measured at the EM scale, the selection criteria was then evaluated from efficiencies to corresponding to the energy deposited by electromagneti- satisfy each selection criterion, parametrized as a function cally interacting particles. After reconstruction, jets are of the LLP decay position. calibrated using the procedure outlined in Ref. [65]. In order to validate the extrapolation procedure described The missing transverse momentum, Emiss T , is defined as above, another set of samples for only the scalar boson the magnitude of the negative vector sum of the transverse model with ms ≥ 125 GeV and with fewer (200 000) momenta of preselected electrons, muons, photons and jets, events was generated. The mean proper lifetime in each to which is added an extra term to account for energy of these samples was tuned in order to have a slightly deposits that are not associated with any of these selected longer mean lab-frame decay length, corresponding to 9 m. objects [66]. This extra term was calculated from inner The mean proper lifetimes in these MC samples span a detector tracks matched to the primary vertex (PV) to make range of 0.23–7.20 m, depending on the sample. it more resilient to contamination from pileup interactions. All MC samples described above were generated at For the analysis presented in this paper, electrons, muons leading order using MG5_AMC@NLO 2.2.3 [52] interfaced and photons were used only in the computation of Emiss T , to PYTHIA 8.210 [53] parton shower model. The A14 set and their reconstruction is detailed in Refs. [67,68]. of tuned parameters [54] was used together with the Electrons were required to have a pT > 10 GeV and jηj < NNPDF2.3LO parton distribution function (PDF) set 2.47 and also pass medium identification requirements [55]. The EVTGEN 1.2.0 program [56] was used for the [69]. Muons were required to have a pT > 10 GeV and properties of b- and c-hadron decays. The generated events jηj < 2.7 with a matching track in the ID and pass a were processed through a full simulation of the ATLAS medium quality requirement [68]. Photons were selected detector geometry and response [57] using the GEANT4 [58] using a tight identification requirement [70]. Since tracklets toolkit. The simulation includes multiple pp interactions (defined in Sec. VI C) are not used for the Emiss T calculation, per bunch crossing (pileup), as well as the effect on the a displaced vertex from a signal event in the MS will detector response due to interactions from bunch crossings contribute to the Emiss T . before or after the one containing the hard interaction. Pileup was simulated with the soft strong-interaction B. Muon RoI cluster trigger processes of PYTHIA 8.210 using the A2 set of tuned The muon RoI cluster trigger is a signature-driven trigger parameters [59] and the MSTW2008LO [60] PDF set. that selects candidate events for decays of LLPs particles in Per-event weights were applied to the simulated events the MS: events must contain a cluster of muon RoIs within to correct for inaccuracies in the pileup simulation. a ΔR ¼ 0.4 cone. The details of the performance and implementation of this trigger can be found in Ref. [39]. The VI. TRIGGER AND EVENT RECONSTRUCTION isolation criteria for jets and tracks, discussed in Ref. [39] Hadronic LLP decays in the MS typically produce and used to reduce background punch-through jets, were not narrow, high-multiplicity hadronic showers. Variations in applied in the analysis presented in this paper. The trigger track multiplicity and shower width depend on the mass selects isolated, signallike events and nonisolated, back- and boost of the decaying LLP and the final states to which groundlike events. The backgroundlike events were then the LLP decays. Dedicated trigger [39] and vertex [40] available to be used in control regions and for data-driven algorithms were developed to select and reconstruct dis- background estimations in signal regions. placed decays in the MS. Due to the amount of material in The trigger efficiency, defined as the fraction of LLPs the calorimeter, only decays occurring in or after the last selected by the trigger as a function of the LLP decay sampling layer of the hadronic calorimeter will generally position, is shown in Figs. 2(a) and 2(b) for four MC produce a significant number of hits in the MS and simulated benchmark samples with LLP decays in the MS therefore were reconstructed. barrel and end cap regions, respectively. The efficiency was parametrized as a function of the transverse decay position (Lxy ) in the barrel and the longitudinal decay position (jLz j) A. Reconstruction of prompt hadronic jets in the end caps. The trigger is efficient for hadronic decays and missing transverse momentum of LLPs that occur anywhere from the outer regions of the Calorimeter jets with a ET threshold greater than 10 GeV HCal to the middle stations of the MS. These efficiencies and jηj < 4.9 are constructed at the electromagnetic (EM) were obtained from the subset of events with only a single energy scale using the anti-kt jet algorithm [61] with a LLP decay in the muon spectrometer in order to ensure radius parameter R ¼ 0.4 using the FASTJET 2.4.3 software that the result of the trigger is due to a single burst of package [62]. A collection of three-dimensional topological MS activity. The uncertainties shown are statistical only. 052005-6 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 1 1 ATLAS Simulation ATLAS Simulation Muon RoI Cluster trigger efficiency Muon RoI Cluster trigger efficiency 0.9 0.9 HCal end RPC1 S RPC2 S RPC1 L RPC2 L m~g = 500 GeV m~g = 500 GeV TGC1 0.8 mg~ = 1500 GeV 0.8 mg~ = 1500 GeV HCal end χ→cbs, mχ = 10 GeV χ→cbs, mχ = 10 GeV 0.7 0.7 χ→cbs, mχ = 100 GeV χ→cbs, mχ = 100 GeV 0.6 0.6 Barrel vertices End cap vertices 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0 1 2 3 4 5 6 7 8 0 2 4 6 8 10 12 14 Long-lived particle Lxy [m] Long-lived particle |Lz| [m] (a) (b) FIG. 2. Efficiency for the muon RoI cluster trigger as a function of the decay position of the LLP for four simulated benchmark samples in the (a) MS barrel and (b) MS end caps. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, RPC 1=2 represent the first/second layer of RPC chambers, TGC 1 represents the first layer of TGC chambers and L/S indicates whether they are in large or small sectors. The relative differences between the efficiencies of the segments and corresponding track parameters is called a benchmark samples are a result of the different masses of tracklet. These tracklets are used to reconstruct the positions the LLPs, which in turn affect their momenta and con- of MS vertices. This algorithm was previously used for both sequently the opening angles of the decay products. The the 7 TeV [27] and 8 TeV [71] searches for displaced decays. trigger efficiency is higher when the LLP decays close to Detectable decay vertices were located in the region between the end of the hadronic calorimeter (barrel: r ∼ 4 m; end the outer edge of the HCal and the middle station of muon caps: z ∼ 6 m) and it decreases substantially as the decay chambers. Due to the different detector technology (no occurs closer to the middle station of the muon spectrom- spatially separated multilayers), the CSC chambers were not eter (barrel: r ∼ 7 m; end caps: z ∼ 13 m). For decays used for the MS vertex reconstruction. occurring close to the middle station, the charged hadrons and photons (and their EM showers) are not spatially separated and they are overlapping when they traverse the 1. Reconstructed objects for vertex isolation middle stations. In order to ensure sufficient signal acceptance and Scale factors were used in order to correct for mismod- background rejection, a set of vertex isolation criteria eling of the L1 muon trigger response in MC simulation for ID tracks and calorimeter jets was established in order and they were calculated by comparing the distributions to assist in determining whether or not a vertex is consistent of the average number of muon RoI clusters within a ΔR with a displaced hadronic decay. cone of 0.4 around the axis of a punch-through jet in For track isolation, two separate criteria were used: one for multijet MC and data events. In fact, a high-energy jet has a high-pT tracks which considers tracks with pT > 5 GeV, high probability of punching through into the MS and and one for large multiplicities of low-pT tracks which used creating a cluster of muon RoIs that can mimic the behavior the pT vector sum of all tracks associated with the PV with of signal events. High-energy jets were selected using a jet pT > 400 MeV in a ΔR cone of 0.2 around the MS vertex trigger with a ET threshold of 400 GeV. The scale factor is axis.2 The two different isolations stem from the fact that 1.13  0.01 for the barrel and 1.04  0.02 for the end caps, some jets have most of their energy in a single hadron, while and it does not depend on the η or the pT of the jet. others can consist of multiple low-pT tracks. For the 2MSVx and 1MSVx+Jets strategies, all the jets C. Reconstruction of MS vertices considered for isolation must meet jet quality criteria. Jets A dedicated algorithm [40], capable of reconstructing must satisfy ET > 30 GeV and log10 ðEHAD =EEM Þ < 0.5. low-momentum tracks in a busy environment, was used to The value log10 ðEHAD =EEM Þ quantifies the fraction of reconstruct the displaced MS vertices used in this search. energy of the jet that is deposited in the HCal (EHAD ) with The algorithm takes advantage of the spatial separation respect to the energy deposited in the ECal (EEM ). This between the two multilayers inside a single MDT chamber. requirement ensures that vertices originating from LLPs that Single-multilayer straight-line segments that contain three decay near the outer edge of the hadronic calorimeter and or more MDT hits were reconstructed using a minimum χ 2 fit. Segments from multilayer-1 were then matched with 2 The MS vertex axis is defined with respect to the detector those from multilayer-2. The paired set of single-multilayer coordinate system. 052005-7 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) also have significant MS activity were not rejected. In consequently a minimum number of MDT (nMDT ) and addition, in order to reduce the probability that a signal RPC/TGC (nRPC =nTGC ) hits was required. The number of vertex fails to meet the isolation criteria due to pileup jets MDT hits was counted in the MDT chambers that have that do not have sufficient energy to create an MS vertex, their center within Δϕ ¼ 0.6 and Δη ¼ 0.6 of the vertex jets with 20 < ET < 60 GeV were required to be matched ðη; ϕÞ position. The number of RPC or TGC hits is the sum to the PV using a jet vertex tagger (JVT) discriminant [72]. of hits that are within ΔR ¼ 0.6 of the vertex position. Standard jet quality criteria [73] were not enforced because A requirement on the maximum number of MDT hits was jets that do not fulfill these requirements can also produce a also applied to remove background events caused by background MS vertex. coherent noise bursts in the MDT chambers. In addition For the 1MSVx þ Emiss T strategy a looser selection on the to reducing the background, the minimum required number jets used for isolation was applied. The reason for this is of RPC/TGC hits helps to further reject these noisy events, that most of the background that enters the signal region of because a noise burst in the MDT system is not expected to this strategy is generated by events where a jet satisfying be coherent with one in the muon trigger system. the jet quality criteria is almost back-to-back with an MS A displaced decay that occurs in the transition region vertex created by another jet that does not fulfill the jet between MS barrel and end caps results in hits in both quality criteria, but has enough energy to punch through regions. Vertex reconstruction was performed separately in into the muon spectrometer. Studies performed in data the barrel and end caps, and only the barrel (end cap) hits showed that there could be standard or pileup jets with a were used in the barrel (end cap) vertex reconstruction measured energy down to 15 GeV that can create a vertex in algorithm. Therefore, any vertices reconstructed from the MS. These jets would not be used to compute the either of the two algorithms have fewer hits, as they were isolation since they do not pass the ET selection require- reconstructed from a subset of the total hits. The result is a ment present in jet quality criteria and the associated vertex decrease in the reconstruction efficiency, and this also would be incorrectly considered as a signal candidate. occasionally results in two vertices being reconstructed For these reasons, all jets above 15 GeV were considered in from a single LLP decay. Therefore, the MS vertices with the isolation computation for the 1MSVx þ Emiss T strategy. pseudorapidity, jηvx j, between 0.8 and 1.3 were not The looser selection on the jets used for isolation has considered in the analysis. This has a negligible impact negligible impact on the signal efficiency, according to on the signal efficiency, since the average MS vertex simulation; in all the samples considered for the results efficiency in this region is less than 2%. presented in this paper there are no events rejected because Background studies performed for the 1MSVx+AO of a jet below 20 GeV entering the isolation. strategies using data showed that in the transition region The same type of jet events could also affect the 2MSVx between the barrel and the end cap hadronic calorimeters, and 1MSVx+Jets strategies. For the former the jet quality 0.7 < jηvx j < 1.2, the probability of having a jet that does criteria have no impact on the background estimation, not fulfill the minimal selection criteria for being consid- while for the latter the effect is negligible because the ered for isolation and that punches through into the MS is additional selection on the energy of the two prompt jets much higher than in other regions of the detector. This strongly reduces this background contribution. region overlaps the already excluded MS transition region, Vertex isolation criteria were optimized separately for except for 0.7 < jηvx j < 0.8. The fraction of signal events each analysis strategy described in Sec. III, and they are removed was very small compared to the gain obtained by described in detail in Secs. VIII and IX. removing punch-through jet background that could affect the single-vertex analysis; therefore, vertices reconstructed VII. BASELINE EVENT SELECTION in the MS region 0.7 < jηvx j < 0.8 were not considered either. A common baseline selection was applied to the events Table III summarizes the baseline criteria used to select considered in the three strategies described in Table I. “good” MS vertices. After this selection, the main back- Events were required to pass the muon RoI cluster trigger ground contribution is from punch-through jets. This and contain a PV with at least two tracks with remains true after further selections are applied in both pT > 400 MeV. The vertex with the largest sum of the the 1MSVx+AO and 2MSVx strategies. The number of squares of the transverse momenta of all tracks associated events passing the baseline selection reported in Table III with the vertex was chosen as the PV. This PV selection has is 389 743 and 1 209 324 in the barrel and end caps, no impact on the signal efficiency. In simulation, the respectively. selected PV corresponds to the signal interaction in about 95%–99% of the cases, depending on the sample; even VIII. TWO-MS-VERTEX SEARCH though the LLPs are invisible in the ID, the resonance (scalar, Higgs boson) is produced with a significant pT . The two-MS-vertex strategy is designed to be sensitive An MS vertex due to a displaced decay typically has to models where the LLP is pair-produced and decays many more hits than an MS vertex from background; hadronically between the outer region of the HCal and the 052005-8 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) TABLE III. Summary of the baseline criteria used for the separated by at least ΔR ¼ 1.0, which has minimal impact analysis presented in this paper. All selection criteria are also on the overall signal acceptance. applied to signal MC events when determining the number of expected signal events in the dataset. B. MS vertex efficiency Event passes muon RoI cluster trigger. The efficiency for vertex reconstruction is defined as the Event has a PV with at least two tracks with pT > 400 MeV. fraction of simulated LLP decays in the MS fiducial volume Event has at least one MS vertex. which match a reconstructed vertex passing the baseline MS vertex matched to triggering muon RoI cluster event selection and satisfying the vertex isolation criteria [ΔRðvertex; clusterÞ < 0.4]. [40]. A reconstructed vertex is considered matched to a For 2MSVx strategy: in the case of 2 muon RoI clusters, the second vertex should be matched to the displaced decay if the vertex is within ΔR ¼ 0.4 of the second cluster. simulated decay position. The MS vertex efficiency was 300 ≤ nMDT < 3000 parameterized as a function of the transverse (Lxy ) and longitudinal (jLz j) LLP decay position in the barrel and end Barrel End caps caps, respectively. Figure 3(a) shows the efficiency for reconstructing a vertex in the MS barrel for a selection of MS vertex with jηvx j<0.7 MS vertex with 1.3 5 GeV) ΔR < 0.3 ΔR < 0.6 Low-pT track isolation, ðΣpT ðΔR < 0.2ÞÞ ΣpT < 10 GeV ΣpT < 10 GeV Jet isolation ΔR < 0.3 ΔR < 0.6 052005-9 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) 0.7 1 MS vertex reconstruction efficiency MS vertex reconstruction efficiency ATLAS Simulation ATLAS Simulation HCal end 0.9 MDT1 S MDT2 S MDT1 L MDT2 L HCal end MDT1 S MDT2 S 0.6 MDT1 L MDT2 L m~g = 500 GeV m~g = 500 GeV mg~ = 1500 GeV 0.8 mg~ = 1500 GeV 0.5 χ→cbs, mχ = 10 GeV 0.7 χ→cbs, mχ = 10 GeV χ→cbs, mχ = 100 GeV χ→cbs, mχ = 100 GeV 0.4 0.6 Barrel vertices End cap vertices 0.5 2MSVx strategy 2MSVx strategy 0.3 0.4 0.2 0.3 0.2 0.1 0.1 0 0 0 1 2 3 4 5 6 7 8 0 2 4 6 8 10 12 14 Long-lived particle Lxy [m] Long-lived particle |Lz| [m] (a) (b) FIG. 3. Efficiency to reconstruct an MS vertex for some of the stealth SUSY and baryogenesis benchmark samples, for vertices that pass the baseline event selection and satisfy the vertex isolation criteria (no trigger selection is applied). (a) Barrel MS vertex reconstruction efficiency as a function of the transverse decay position of the LLP. (b) End cap MS vertex reconstruction efficiency as a function of the longitudinal decay position of the LLP relative to the center of the detector. The vertical lines show the relevant detector boundaries, where “HCal end” is the outer limit of the hadronic calorimeter, MDT 1=2 represent the first/second layer of MDT chambers and L/S indicate whether they are in large or small sectors. N 2Vx ¼ N 1cl · PVx 2cl Vx 2cl noMStrig þ N 1UMBcl · PBcl þ N 1UMEcl · PEcl : Vx is evaluated as ð159 816  400Þ · ð1.7  0.7Þ × 10−7 ¼ 0.027  0.011, where the uncertainty is statistical only. The events selected by the muon RoI cluster trigger and IX. SINGLE-MS-VERTEX SEARCH containing only one MS vertex are separated into those containing only one cluster of muon RoIs (N 1cl ), and For models with two LLPs, the probability of having those containing two muon RoI clusters, where only one both LLPs decay inside the detector decreases for mean cluster is matched to the reconstructed MS vertex and the lab-frame decay lengths greater than ∼5 m. Thus, extend- other is unmatched in the barrel or end caps (N 2cl 1UMBcl , ing sensitivity to shorter and longer proper lifetimes for a 2cl Vx N 1UMEcl ). The term PnoMStrig is the probability of finding given model also requires a strategy of using only one a vertex in events not selected by the muon RoI cluster reconstructed displaced decay [36]. In the regime of long trigger. This probability is determined from zero-bias lifetimes the single-vertex analysis in the MS has unique events by dividing the number of good, isolated MS sensitivity compared to other displaced searches, although it is affected by higher levels of background. For a search vertices not passing the muon RoI Cluster trigger by the with only one displaced object, a background determina- total number of zero-bias events that satisfy standard tion method similar to the two-vertex search does not work event quality criteria. The terms PVx Vx Bcl and PEcl are the since the ensemble of events with one isolated vertex, used probabilities for finding an MS vertex given a muon RoI to estimate the background, already contains the signal cluster in the barrel and end caps, respectively. Since zero region for the 1MSVx+AO strategies. Instead, nonisolated events are observed with two trigger clusters and one vertices are used in a data-driven method to estimate the vertex, the contribution of the N 2cl terms is negligible. expected number of isolated fake vertices. Therefore, the number of two-MS-vertex events can be The following sections describe the event selection and calculated as N 2Vx ¼ N 1cl · PVx noMStrig . background estimation for the 1MSVx+Jets and 1MSVx þ Six good isolated MS vertices were found in 35 673 956 Emiss strategies. The events considered in these searches T zero-bias triggered events, while 159 816 events with one must satisfy the baseline selection criteria summarized in isolated muon RoI cluster matched to a vertex were selected Sec. VII. in the 2015 and 2016 datasets. The zero-bias sample has no overlap with the muon RoI cluster triggered events and A. Event selection contains zero events with more than one MS vertex. Contamination from signal events would result in over- Two separate signal selections are used for the two estimation of the probabilities and resulting background topologies that are considered in the single-MS-vertex search. rates. The probability PVx noMStrig is thus estimated to be 6=35673956 ¼ ð1.7  0.7Þ × 10−7 , where the uncertainty is 1. 1MSVx+Jets strategy statistical only. Therefore, the expected number of back- The main criterion that is used to distinguish a signal ground events with one trigger cluster and two vertices MS vertex from background is its degree of isolation as 052005-10 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 1 m~g = 250 GeV 1 m~g = 250 GeV m~g = 800 GeV m~g = 800 GeV m~g = 1200 GeV m~g = 1200 GeV m~g = 2000 GeV m~g = 2000 GeV Fraction of events Fraction of events Data Data 10−1 10−1 ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 Barrel vertices End cap vertices 10−2 10−2 10−30 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 10−30 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 min[ ΔR(closest jet),ΔR(closest track)] min[ ΔR(closest jet),ΔR(closest track)] (a) (b) FIG. 4. Distributions of the isolation variable used to select signal events for the 1MSVx+Jet strategy, for the (a) barrel and (b) end caps. The black points are data collected in 2015 and 2016, while the dashed and solid lines show the distributions for four of the MC stealth SUSY signal samples. The black vertical lines show the selection cuts that define the signal region. The events in the plots satisfy the baseline selection criteria described in Sec. VII. Distributions are normalized to unity. described in Sec. VIII A. To characterize the degree Moreover, the two prompt jets produced by the gluino of isolation with a single value, the variable ΔRmin ¼ decays can be used to improve the signal selection for the minðΔRðvertex; closest jetÞ; ΔRðvertex; closest trackÞÞ was stealth SUSY analysis. The second-highest (subleading) defined. Figures 4(a) and 4(b) show the distributions of the jet ET is generally above 150 GeV, though applying this isolation variable used for 1MSVx+Jets events for data and requirement results in some loss of signal efficiency in some of the MC benchmark samples for barrel and end cap the lowest-mass gluino sample (mg̃ ¼ 250 GeV). For events vertices, respectively. with a barrel MS vertex the ET of the leading and Another signal selection variable is the sum of the subleading jets was required to be above 150 GeV, while number of MDT hits and trigger hits (RPC and TGC in for events with an end cap MS vertex, a tighter requirement the barrel and end caps, respectively) in a cone around an of 250 GeV was chosen due to the higher levels of MS vertex, since a signal event is expected to leave more background. Since the isolation variable depends on the hits than a background one. Figures 5(a) and 5(b) present ΔR between a jet and the vertex, jets chosen for this the distributions of the number of MS hits variable used for selection must have ΔRðjet; vertexÞ > 0.7. This prevents the 1MSVx+Jets strategy for data collected during 2015 the selection of a sample containing punch-through jets that and 2016 and for some of the MC benchmark samples for leave a vertex in the MS. In signal events, this requirement barrel and end cap vertices, respectively. has minimal effect, since jets and vertices originate from 0.35 0.25 m~g = 250 GeV m~g = 250 GeV m~g = 800 GeV m~g = 800 GeV 0.3 m~g = 1200 GeV m~g = 1200 GeV 0.2 m~g = 2000 GeV m~g = 2000 GeV 0.25 Fraction of events Fraction of events Data Data ATLAS 0.15 ATLAS 0.2 s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 Barrel vertices End cap vertices 0.15 0.1 0.1 0.05 0.05 0 0 0 2000 4000 6000 8000 10000 0 2000 4000 6000 8000 10000 nMDT+nRPC ∈ vertex nMDT+nTGC ∈ vertex (a) (b) FIG. 5. Distributions of the number of MS hits associated with the displaced vertex, used to select signal events for the 1MSVx+Jet strategy, for the (a) barrel and (b) end caps. The black points are data collected in 2015 and 2016, while the dashed and solid lines show the distributions for four of the MC stealth SUSY signal samples. The black vertical lines show the selection cuts that define the signal region. The events in the plots satisfy the baseline selection criteria described in Sec. VII. Distributions are normalized to unity. 052005-11 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) TABLE V. Summary of the signal selection for the 1MSVx+ All the events used for the 1MSVx þ Emiss T strategy are Jets strategy. An MS vertex satisfying these criteria is selected. required to have a Emiss T > 30 GeV, and in the end caps, Event passes baseline selection only vertices with at least five tracklets are considered, which further reduces the higher level of background Barrel End caps present in this region. The same isolation variable, ΔRmin , defined for the nMDT þ nRPC > 2000 nMDT þ nTGC > 2500 1MSVx+Jets strategy, is also used to select signal events ΔRmin > 0.3 ΔRmin > 0.4 for the 1MSVx þ Emiss strategy, although for the latter the Two jets with ET > 150 GeV, Two jets with ET > 250 GeV, T ΔRðjet; VxÞ > 0.7 ΔRðjet; VxÞ > 0.7 isolation criteria are computed while placing a looser selection on the jets, as described in Sec. VI C 1. Figures 6(a) and 6(b) show the distributions of the isolation variable used for the 1MSVx þ Emiss T strategy for data and different particles and thus tend to be well separated. In data some of the MC benchmark samples for barrel and end cap events, the main background is from multijet production, vertices, respectively. and thus if a jet is near a vertex it is generally well within The angle in the transverse plane between the Emiss T ΔR ¼ 0.7. The selection on the two prompt jets described vector and the direction of the displaced vertex measured above is used to define two regions: one signal-dominated, from the origin of the detector coordinate system, and one background-dominated used to validate the data- jΔϕðEmiss T ; MSVxÞj, was also used to distinguish signal driven background estimation. from background because for signal vertices the Emiss T The signal selection for the 1MSVx+Jets strategy was optimized by examining the signal acceptance and back- vector tends to be aligned with the direction of the ground rejection using data from the background-dominated displaced vertex. Figures 7(a) and 7(b) report the distri- region defined by the ET values of the two prompt jets. The butions of the jΔϕðEmissT ; MSVxÞj variable, used to select minimum values required for isolation ΔRmin are 0.3 and signal events for the 1MSVx þ Emiss T strategy, for data and 0.4 for the barrel and end caps, respectively; a minimum of some of the MC benchmark samples for barrel and end cap 2000 MDT þ RPC hits in the barrel and 2500 MDT þ TGC vertices, respectively. hits in the end caps is required. Table V summarizes the The number of MDT hits and trigger hits (RPC and TGC signal selection for the 1MSVx+Jets strategy. hits in the barrel and end caps, respectively) in a ΔR cone around the MS vertex was used to define one signal- dominated region and one background-dominated region 2. 1MSVx + Emiss T strategy that was used to validate the data-driven background The one-vertex searches for the scalar portal model with estimation. The selection requirements that define the mΦ ¼ 125 GeV and the Higgs portal baryogenesis model two regions were optimized in order to ensure a sufficient are particularly challenging due to the absence of any signal acceptance and background rejection. For events distinctive associated objects produced with the LLPs, such with a barrel MS vertex the number of hits (nMDT þ nRPC ) as the two prompt jets in the stealth SUSY model. is required to be greater than 1200, while for events with an Φ → ss , mΦ,ms=[125,8] GeV Φ → ss , mΦ,ms=[125,8] GeV Φ → ss , mΦ,ms=[125,40] GeV Φ → ss , mΦ,ms=[125,40] GeV 1 h → χχ (→ νbb) , mχ=10 GeV 1 h → χχ (→ νbb) , mχ=10 GeV h → χχ (→ νbb) , mχ=50 GeV h → χχ (→ νbb) , mχ=50 GeV Fraction of events Fraction of events Data Data ATLAS ATLAS 10−1 s = 13 TeV, 36.1 fb-1 10−1 s = 13 TeV, 36.1 fb-1 Barrel vertices End cap vertices 10−2 10−2 10−3 10−3 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 min[ ΔR(closest jet), ΔR(closest track)] min[ ΔR(closest jet), ΔR(closest track)] (a) (b) FIG. 6. Distributions of the isolation variable used to select signal events for the 1MSVx þ Emiss T strategy, for the (a) barrel and (b) end caps. The black points are data collected in 2015 and 2016, while the solid lines show the distributions for four MC signal samples. The black vertical lines show the selection cuts that define the signal region. The events in the plots satisfy the baseline selection criteria described in Sec. VII and have Emiss T > 30 GeV. Distributions are normalized to unity. 052005-12 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 0.2 Φ → ss , mΦ,ms=[125,8] GeV Φ → ss , mΦ,ms=[125,8] GeV 0.18 Φ → ss , mΦ,ms=[125,40] GeV 0.16 Φ → ss , mΦ,ms=[125,40] GeV h → χχ (→ νbb) , mχ=10 GeV h → χχ (→ νbb) , mχ=10 GeV 0.16 h → χχ (→ νbb) , mχ=50 GeV 0.14 h → χχ (→ νbb) , mχ=50 GeV Fraction of events Fraction of events 0.14 Data 0.12 Data ATLAS ATLAS 0.12 0.1 s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 0.1 Barrel vertices End cap vertices 0.08 0.08 0.06 0.06 0.04 0.04 0.02 0.02 0 0 0.5 1 1.5 2 2.5 3 0 0.5 1 1.5 2 2.5 3 |Δφ(Emiss,MSVx)| |Δφ(Emiss,MSVx)| T T (a) (b) FIG. 7. Distributions of the angle in the transverse plane between the Emiss T and the displaced vertex jΔϕðEmiss T ; MSVxÞj used to select signal events for the 1MSVx þ ET strategy, for the (a) barrel and (b) end caps. The black points are data collected in 2015 and 2016, miss while the dashed and solid lines show the distributions for four MC signal samples. The black vertical lines show the selection cuts that define the signal region. The events in the plots satisfy the baseline selection criteria described in Sec. VII and have Emiss T > 30 GeV. Distributions are normalized to unity. end cap MS vertex, the number of hits (nMDT þ nTGC ) must end caps, respectively. Vertices selected for the stealth exceed 1500. SUSY and baryogenesis benchmark samples must satisfy The signal region selection for the 1MSVx þ Emiss T the signal selection criteria described in Secs. IX A 1 strategy was optimized using signal acceptance versus back- and IX A 2, respectively (no trigger selection is applied). ground rejection estimated from data in the background- The behavior of the MS vertex reconstruction efficiency as dominated region. The selection requires values of at least a function of the LLP proper lifetime is similar to that 0.8 for isolation ΔRmin and 1.2 for jΔϕðEmiss T ; MSVxÞj, for shown in Fig. 3, although the efficiency values are different both the barrel and end caps. Due to the higher levels of due to the different event selection. The MS barrel vertex background, the selection requirement imposed on the iso- reconstruction efficiency is 15%–25% near the outer edge lation is stricter than the ones used for the 1MSVx+Jets of the hadronic calorimeter (r ≈ 4 m) and it substantially strategy. Table VI summarizes the signal selection for the decreases as the decay occurs closer to the middle station 1MSVx þ Emiss T strategy. (r ≈ 7 m). The efficiency for reconstructing vertices in the MS end caps reaches 40% for baryogenesis and stealth 3. MS vertex efficiency SUSY high-mass gluino benchmark models. The lower efficiency for the stealth SUSY sample with mg̃ ¼ The efficiency for vertex reconstruction is defined as the 500 GeV is due to the selection requirement on the ET fraction of simulated LLP decays in the MS fiducial volume values of the two prompt jets, which is not optimal for the which match a reconstructed vertex satisfying the signal selection criteria. A reconstructed vertex is considered lower masses. matched to a displaced decay if the vertex is within ΔR ¼ 0.4 of the simulated decay position. Figures 8(a) and 8(b) B. Background estimation show the efficiency for reconstructing a vertex for a The ABCD method developed for the 1MSVx+AO selection of benchmark samples in the MS barrel and strategies uses two, uncorrelated vertex-based variables to create a two-dimensional plane that is split into four TABLE VI. Summary of the signal selection for the 1MSVx þ parts: region A is where most signal events are located, and Emiss T strategy. An MS vertex satisfying these criteria is selected. three control regions (B, C, and D) that contain mostly background. The number of background events in A can be Event passes baseline selection predicted from the population of the other three regions: Emiss T > 30 GeV N A ¼ N B × N C =N D , assuming negligible leakage of signal jΔϕðEmiss T ; MSVxÞj < 1.2 into regions B, C, and D. This calculation is performed in ΔRmin > 0.8 two separate regions: one background-dominated valida- tion region (VR) and one signal region (SR). Two different Barrel End caps ABCD planes were defined for the 1MSVx+Jets and nMDT þ nRPC > 1200 nMDT þ nTGC > 1500 1MSVx þ Emiss strategies. Figures 9(a) and 9(b) show T ntracklets ≥ 5 the distribution of barrel vertices for data in the ABCD 052005-13 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) 0.5 0.8 MS vertex reconstruction efficiency MS vertex reconstruction efficiency ATLAS Simulation ATLAS Simulation 0.45 0.7 m~g = 500 GeV m~g = 500 GeV HCal end HCal end MDT1 S MDT2 S MDT1 L MDT2 L 0.4 MDT1 S MDT2 S MDT1 L MDT2 L mg~ = 1500 GeV mg~ = 1500 GeV χ→cbs, mχ = 10 GeV 0.6 χ→cbs, mχ = 10 GeV 0.35 χ→cbs, mχ = 100 GeV χ→cbs, mχ = 100 GeV 0.3 0.5 Barrel vertices End cap vertices 0.25 0.4 1MSVx+AO strategies 1MSVx+AO strategies 0.2 Signal region 0.3 Signal region 0.15 0.2 0.1 0.05 0.1 0 0 0 1 2 3 4 5 6 7 8 0 2 4 6 8 10 12 14 Long-lived particle Lxy [m] Long-lived particle |Lz| [m] (a) (b) FIG. 8. Efficiency to reconstruct an MS vertex for some of the stealth SUSY and baryogenesis benchmark samples, for vertices that satisfy the signal selection criteria for the 1MSVx+AO strategies (no trigger selection is applied). (a): Barrel MS vertex reconstruction efficiency as a function of the transverse decay position of the LLP. (b): End cap MS vertex reconstruction efficiency as a function of the longitudinal decay position of the LLP. The vertical lines show the relevant detector boundaries. 10000 3.5 ATLAS s = 13 TeV, 36.1 fb-1 ATLAS s = 13 TeV, 36.1 fb-1 9000 Barrel vertices 10 2 nMDT+nRPC hits > 1200 3 8000 ET,1 > 150 GeV, Barrel vertices 103 vertex(nMDT + nRPC hits) ET,2 > 150 GeV Correlation: 0.02 2.5 |Δφ(Emiss,MSVx)| 7000 Correlation: -0.01 Signal region 6000 B A Signal region 10 2 D B 102 5000 T 4000 1.5 3000 1 10 2000 1 0.5 1000 D C C A 0 0 1 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.5 1 1.5 2 2.5 3 3.5 4 min[ΔR(closest jet),ΔR(closest track)] min[ ΔR(closest jet),ΔR(closest track)] (a) (b) FIG. 9. Distribution of barrel vertices in the ABCD plane for the SR and the definition of the four subregions for the (a) 1MSVx+Jets strategy and (b) 1MSVx þ Emiss T strategy. plane and the definition of the four subregions for the 1MSVx+Jets strategy while for the 1MSVx þ Emiss T strat- 1MSVx+Jets and 1MSVx þ Emiss T strategies, respectively. egy it corresponds to 0.8% (0.6%) of the total number of The ABCD method relies on there being only one source background events expected in the SR in the barrel (end of background, or multiple sources that have identical caps). Noncollision background events are equally distrib- distributions in the ABCD plane. In general, noncollision uted in the ABCD plane and they are taken into account as a background, which does not originate from the pp inter- systematic uncertainty. action point, will have a different distribution in the ABCD Signal contamination in the VR, which can bias the plane. To determine the noncollision background contami- ABCD method validation, was tested and found to be nation, data collected in LHC empty bunch crossings negligible for both the1MSVx+Jets and 1MSVx þ Emiss T throughout the 2016 data-taking period were used to strategies. estimate the number of noncollision background vertices in coincidence with events otherwise satisfying the single- 1. ABCD plane for 1MSVx+Jets strategy vertex selection criteria. The empty bunch crossing trigger was not available in 2015, but the noncollision back- For stealth SUSY-like events the ABCD plane for ground’s relative contribution is expected to be the same. background estimation is constructed with the isolation The fraction of expected noncollision background vertices ΔRmin variable, and the sum of the numbers of MDT and passing the final signal selection is negligible for the trigger hits associated with the MS vertex, described in 052005-14 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) TABLE VII. Summary of the definition of the VR and SR used for the ABCD method for the 1MSVx+Jets strategy. Region Criteria Barrel VR: 50 < ET;subleading < 150 GeV, ET;leading > 150 GeV SR: ET;leading > 150 GeV, ET;subleading > 150 GeV VR: 100 < ET;subleading < 250 GeV, ET;leading > 250 GeV End caps SR: ET;leading > 250 GeV, ET;subleading > 250 GeV TABLE VIII. Event counts in each of the four regions of the 1MSVx+Jets ABCD plane and expected number in region A obtained using 2015 and 2016 data from the VR. Both the statistical and systematic errors of the background expectation are reported. VR A Expected background B C D Barrel 46 45  5ðstatÞ  9ðsystÞ 7, 748 90 15 620 End caps 11 15  3ðstatÞ  12ðsystÞ 3, 335 20 4, 365 Sec. IX A 1. These two variables form the x axis and y axis 45  5ðstatÞ  9ðsystÞ and 15  3ðstatÞ  12ðsystÞ events of the ABCD plane, respectively. The SR and the VR are predicted by the ABCD method in the barrel and end caps, built using the ET values of the leading and subleading jets respectively. The systematic uncertainty associated with and their definition is summarized in Table VII. the background estimation reported above is described in Signal contamination in regions B, C, and D in the SR of detail in Sec. X B. the 1MSVx+Jets ABCD plane was found to be negligible. Signal contamination in the VR is negligible for benchmark 2. ABCD plane for 1MSVx + Emiss T strategy samples with mg̃ > 500 GeV, and for mg̃ ¼ 500 GeV in For the 1MSVx þ Emiss strategy the two variables used the barrel region. However, the end caps region for mg̃ ¼ T to define the ABCD plane are the isolation ΔRmin and the 500 GeV and both barrel and end caps regions for mg̃ ¼ angle in the transverse plane between the Emiss vector T 250 GeV have non-negligible signal contamination in the and the displaced vertex jΔϕðEmiss ; MSVxÞj, described in T VR and thus are not included in the 1MSVx+Jets strategy. Sec. IX A 2. The SR and VR are defined using the sum of Both the VR and SR show very low linear correlation the numbers of MDT and trigger hits in a cone around the between the two variables: −0.01 (−0.03) for the VR, and MS vertex and their definition is summarized in Table IX. −0.01 (−0.05) for the SR in the barrel (end caps). Signal contamination in the VR is negligible. Table VIII summarizes the observed and expected Both the VR and SR show very low linear correlation numbers of events in the four regions of the ABCD plane between the two variables: 0.03 (0.01) for the VR, and constructed using events from the VR. The number of 0.02 (−0.01) for the SR in the barrel (end caps). observed events in region A is 46 and 11 in the barrel and Table X summarizes the observed and expected numbers end caps, respectively. These are in agreement with the of events in the four regions of the ABCD plane constructed using events from the VR. The number of observed events in region A is 334 and 1,107 for the barrel and TABLE IX. Summary of the definition of the VR and SR used end caps, respectively. These are in agreement with the for the ABCD method for the 1MSVx þ Emiss T strategy. 319  29ðstatÞ  38ðsystÞ and 1, 153  46ðstatÞ  69ðsystÞ Region Criteria events predicted by the ABCD method in the barrel and end caps, respectively. The systematic uncertainty associated Barrel VR: nMDT þ nRPC < 1200 with the background estimation reported above is described SR: nMDT þ nRPC > 1200 in detail in Sec. X B. VR: nMDT þ nTGC < 1500 End caps SR: nMDT þ nTGC > 1500 For the 1MSVx þ Emiss T strategy the signal contamina- tion in regions B, C, and D of the SR ABCD plane is not TABLE X. Event counts in each of the four regions of the 1MSVx þ Emiss T ABCD plane and expected number in region A obtained using 2015 and 2016 data from the VR. Both the statistical and systematic errors of the background expectation are reported. VR A Expected background B C D Barrel 334 319  29ðstatÞ  38ðsystÞ 119 67 980 25 380 End caps 1,107 1; 153  46ðstatÞ  69ðsystÞ 639 56 970 31 570 052005-15 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) negligible. The traditional method, which estimates the systematic uncertainty due to the PDF used to generate background in region A by taking the ratio of events in signal MC events. For the latter, the PDF uncertainty was the adjacent regions, breaks down in the presence of signal in obtained by considering the envelope of the uncertainty of the control regions. An ABCD-likelihood method addresses the PDF set. The total systematic uncertainty of the signal this issue because it estimates the background in region A efficiency for passing the muon RoI cluster trigger was by fitting simultaneously background and expected signal obtained by summing in quadrature the contributions events in the four regions of the ABCD plane. A likelihood described above and varies from 1% to 12%, depending function is formed from the product of four Poisson on the sample and detector region. The total systematic functions, one for each region A, B, C and D, describing uncertainty of the signal efficiency for reconstructing an signal and background expectations. The likelihood takes MS vertex was obtained by summing in quadrature the the form contributions coming from pileup and PDF uncertainties (evaluated with the similar procedure described above) and Y e−N i N ni i varies from 0.07% to 5.5%, depending on the sample and LðnA ; nB ; nC ; nD js; b; τB ; τC Þ ¼ ; ð1Þ i¼A;B;C;D ni ! detector region. The systematic uncertainty associated with the prompt jets used for the 1MSVx+Jets strategy origi- where nA , nB , nC and nD are the four observables that denote nates from jet energy scale, PDF and pileup uncertainties, the number of events observed in each region in data. The N i and was evaluated with the similar procedure described are linear combinations of the signal and background earlier. The overall systematic uncertainty of the two-jet expectation in each region, defined as follows: efficiency was determined by adding each component in quadrature and varies from 0.3% to 9.8%, depending on the N A ¼ s þ b; sample and detector region. Systematic uncertainties due to the Emiss computation for the 1MSVx þ Emiss strategy are N B ¼ sϵB þ bτB ; T T negligible. By comparing the average number of muon N C ¼ sϵC þ bτC ; segments in a cone around punch-through jets in data and MC simulation, systematic uncertainties associated with N D ¼ sϵD þ bτB τC ; ð2Þ the mismodeling of the MS vertex reconstruction in signal where s is the signal yield, b the estimated background in events were found to be negligible. region A, ϵi the signal contamination derived from MC For each of the scalar boson samples, excluding simulation, and τB and τC are the coefficients that relate the ms ¼ 100 GeV, two proper lifetime points were fully number of background events in region A to the other simulated: one nominal sample and a secondary sample regions. The s, b and τi values are allowed to float in the with longer proper lifetime, as described in Sec. V. The simultaneous fit to the four data regions. secondary sample is used to validate the extrapolation procedure, and a systematic uncertainty is assigned to each X. SYSTEMATIC UNCERTAINTIES sample due to the nonclosure of the extrapolation procedure. This is calculated by determining the fraction of events In this section, experimental and theoretical systematic passing all analysis cuts in each MC sample generated with uncertainties associated with the signal predictions and 9 m lab-frame decay length and comparing them to the background estimation are described. expected global efficiencies obtained with the extrapolation procedure. The systematic uncertainty varies from 2% to A. Uncertainties in the signal predictions 37%, depending on the sample. Stealth SUSY benchmark The signal efficiency systematic uncertainties are domi- samples have events with kinematic behavior similar to that nated by the modeling of the signal physics processes, of events in the high-mass scalar boson samples and they are pileup and detector response and the extrapolation of the thus assigned the average systematic uncertainty of those expected number of signal events as a function of the LLP samples (11%). The kinematics of events in the baryo- proper lifetime. genesis samples is very close to the Φð125Þ → ss kinemat- One of the sources of systematic uncertainty associated ics and a comparable systematic uncertainty related to the with the muon RoI cluster trigger stems from the trigger extrapolation procedure is assumed. For that reason, for all scale factors, and it was estimated by moving them up and the baryogenesis benchmark samples the average systematic down by their statistical uncertainty. The trigger efficiency uncertainty of the five Φð125Þ → ss samples (32%) is used. values obtained with these modified MC samples were The uncertainty in the combined 2015 þ 2016 integrated compared with the efficiency of the nominal sample, and luminosity is 2.1%. It is derived, following a methodology the difference was taken as the systematic uncertainty. A similar to that detailed in Ref. [74], using the LUCID-2 similar strategy was also adopted to estimate the trigger detector for the baseline luminosity measurements [75], systematic uncertainty associated with the modeling of the from calibration of the luminosity scale using x–y beam- minimum-bias interactions used to emulate pileup and the separation scans. 052005-16 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 3.5 ATLAS s = 13 TeV, 36.1 fb-1 103 the bootstrap method and the statistical uncertainty from 3 nMDT+nRPC hits < 1200 the background prediction in region A, and corresponds to Barrel vertices Correlation: 0.03 20% in the barrel and 81% in the end caps. 2.5 |Δφ(Emiss,MSVx)| Validation region For the 1MSVx þ Emiss T strategy the size of the two 102 2 D B removed bands corresponds to 0.1 and 0.2 for the isolation variable and 0.2 and 0.4 for jΔϕðEmiss T ; MSVxÞj. The T 1.5 relative difference in the validation region is lower than 10 1 the statistical uncertainty on the relative difference obtained 0.5 from the bootstrap method in both the barrel and end caps. C A The final systematic uncertainty of the background estimate 0 0 0.5 1 1.5 2 2.5 3 3.5 4 1 is taken to be the maximum of the statistical uncertainty min[ ΔR(closest jet),ΔR(closest track)] from the bootstrap method and the statistical uncertainty of the background prediction in region A, corresponding to FIG. 10. ABCD plane for the 1MSVx þ Emiss T strategy in the 12% and 6% for barrel and end caps, respectively. The barrel and definition of the regions excluded from the estimation small contribution from noncollision background was taken of the background’s systematic uncertainty. into account as a systematic uncertainty of the background estimate, as discussed in Sec. IX B. B. Uncertainties in the background prediction XI. RESULTS The systematic uncertainty associated with the back- ground estimation of the ABCD method was evaluated For the 2MSVx strategy, 0.027  0.011 background using data events passing the validation region selection. events are expected. After unblinding, no events passing Events falling in each of the two bands of the ABCD plane the full signal selection were found. that surround region A, and that are shown in Fig. 10 for the For the 1MSVx+AO strategies, the number of observed 1MSVx þ Emiss T strategy in the barrel, were excluded and events in the four regions of the ABCD plane and the the expected background in the signal region was reeval- background prediction in region A for events passing the uated. The definition of region A was not modified in this SR selection are summarized in Table XI. No significant procedure. The relative variation with respect to the excess above the predicted number of background events observed events in region A was then evaluated. The size is found. of the two bands is defined by the resolution of the two Upper limits on the production cross section times variables used to define the ABCD plane. The maximum branching fraction were derived using the CLs prescrip- value of the two results obtained by separately removing tion [78], implemented with the ROOSTAT [79] and bands with widths of 1σ and 2σ was taken as the systematic HISTFACTORY [80] packages using a profile likelihood uncertainty associated with the background estimation. function [81]. For the 2MSVx and 1MSVx+Jets strategies Since the numbers of events in regions A and B are small, the likelihood includes a Poisson probability term describ- a bootstrap method [76,77] was used to determine the ing the total number of observed events. For the 1MSVx þ statistical uncertainty of the background estimate. Emiss T strategy the likelihood described in Sec. IX B 2 For the 1MSVx+Jets strategy the size of the two was used. For scalar boson benchmark samples with removed bands corresponds to 0.1 and 0.2 for the isolation mΦ ≠ 125 GeV, upper limits were set on σ × B, where and 100 and 200 for the number of MS hits. In the end cap B represents the branching fraction for Φ → ss assuming validation region the uncertainty in the relative difference 100% branching fraction into fermion pairs. For scalar obtained from the bootstrap method is much higher than the boson benchmark samples with mΦ ¼ 125 GeV, upper statistical uncertainty of the background estimate in region limits were set on σ=σ SM × B, where σ SM is the SM Higgs A, while in the barrel the two are comparable. The final boson production cross section, 48.58 pb [82]. For the systematic uncertainty of the background estimate was stealth SUSY benchmarks, upper limits were set on taken to be the maximum of the statistical uncertainty from σ=σ SUSY × B, where σ SUSY is the SUSY production cross TABLE XI. Event counts in each of the four regions of the ABCD plane and expected number in region A for the SR, using the 2015 and 2016 datasets. Both the statistical and systematic errors of the background expectation are reported. Strategy Region A Expected background B C D 1MSVx þ Jets Barrel 14 15  3ðstatÞ  3ðsystÞ 2,057 25 3,414 End caps 4 11  3ðstatÞ  9ðsystÞ 560 15 761 1MSVx þ Emiss T Barrel 224 243  38ðstatÞ  29ðsystÞ 42 132 000 22 800 End caps 489 497  51ðstatÞ  30ðsystÞ 94 165 800 31 390 052005-17 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) 106 95% C.L. Upper Limit on σ/ σSUSY × B~g → S~ g 95 % C.L. Upper Limit on σ / σSM × BΦ(125) → ss 105 ATLAS s = 13 TeV, 36.1 fb , Combined limit -1 1 BΦ(125) → ss = 100% m~g=250 GeV m~g=500 GeV 104 m~g=800 GeV m~g=1200 GeV BΦ(125) → ss = 10% 103 m~g=1500 GeV m~g=2000 GeV 10−1 102 BΦ(125) → ss = 1% 10 10−2 1 10−1 10−3 10−2 10−3 ATLAS Φ(125) Φ(125) → ss, ms = 5 GeV → ss, ms = 8 GeV 10−4 10−4 s=13 TeV, 36.1 fb-1 Φ(125) → ss, ms = 15 GeV Φ(125) → ss, ms = 25 GeV 10−5 Combined limit Φ(125) → ss, ms = 40 GeV 10−6 −1 10−5 −2 10 1 10 102 103 10 10−1 1 10 102 103 Singlino proper lifetime (cτ) [m] Scalar proper lifetime (cτ) [m] (a) (b) FIG. 11. Observed limits for (a) stealth SUSY and (b) Φð125Þ → ss benchmark samples obtained from the combination of 2MSVx and 1MSVx+AO strategies. 102 102 95% C.L. Upper Limit on σ × BΦ → ss [pb] 95% C.L. Upper Limit on σ × BΦ → ss [pb] 10 10 1 1 10−1 mΦ = 200 GeV mΦ = 100 GeV ms = 8 GeV −1 10 ms = 8 GeV ATLAS ms = 25 GeV ATLAS -1 -1 ms = 25 GeV s = 13 TeV, 36.1 fb ms = 50 GeV s = 13 TeV, 36.1 fb −2 10 10−2 10−1 1 10 102 10−2 10−1 1 10 102 Scalar proper lifetime (cτ) [m] Scalar proper lifetime (cτ) [m] 102 102 95% C.L. Upper Limit on σ × BΦ → ss [pb] 95% C.L. Upper Limit on σ × BΦ → ss [pb] 10 10 1 1 10−1 10−1 mΦ = 400 GeV mΦ = 600 GeV ms = 50 GeV ATLAS ms = 50 GeV ATLAS -1 ms = 100 GeV s = 13 TeV, 36.1 fb ms = 150 GeV s = 13 TeV, 36.1 fb-1 10−2 10−2 10−2 10−1 1 10 102 10−2 10−1 1 10 102 Scalar proper lifetime (cτ) [m] Scalar proper lifetime (cτ) [m] 102 95% C.L. Upper Limit on σ × BΦ → ss [pb] 10 1 10−1 mΦ = 1000 GeV ms = 50 GeV ms = 150 GeV ATLAS -1 s = 13 TeV, 36.1 fb 10−2 ms = 400 GeV −2 −1 2 10 10 1 10 10 Scalar proper lifetime (cτ) [m] FIG. 12. Observed limits for scalar boson benchmark samples with mΦ ¼ 100 GeV and mΦ > 125 GeV obtained from the 2MSVx strategy. The different plots show the results obtained for different Φ mass points. 052005-18 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 95 % C.L. Upper Limit on σ × Bh → χχ [pb] 95 % C.L. Upper Limit on σ × Bh → χχ [pb] 103 103 σSM × (B = 100%) σSM × (B = 100%) 102 h → χχ 102 h → χχ σSM × (B = 10%) σSM × (B = 10%) 10 h → χχ 10 h → χχ 1 1 −1 −1 10 10 −2 σ × (B = 100%) [mχ=100 GeV] σ × (B = 100%) [mχ=100 GeV] 10 h → χχ 10−2 h → χχ χ → ν bb, mχ = 10 GeV (comb.) χ → lcb, mχ = 10 GeV (comb.) 10−3 ATLAS χ → ν bb, mχ = 30 GeV (comb.) 10−3 ATLAS χ → lcb, mχ = 30 GeV (comb.) s=13 TeV, 36.1 fb-1 χ → ν bb, mχ = 50 GeV (comb.) s=13 TeV, 36.1 fb-1 χ → lcb, mχ = 50 GeV (comb.) −4 −4 10 χ → ν bb, mχ = 100 GeV (2MSVx) 10 χ → lcb, mχ = 100 GeV (2MSVx) −2 −1 3 −2 −1 10 10 1 10 10 2 10 10 10 1 10 102 103 χ proper lifetime (cτ) [m] χ proper lifetime (cτ) [m] (a) (b) 95 % C.L. Upper Limit on σ × Bh → χχ [pb] 95 % C.L. Upper Limit on σ × Bh → χχ [pb] 103 103 σSM × (B = 100%) h → χχ σSM × (B = 100%) 102 h → χχ 102 σSM × (B = 10%) 10 h → χχ 10 σSM × (B = 10%) h → χχ 1 1 10−1 10−1 σ × (B = 100%) [mχ=100 GeV] σ × (B = 100%) [mχ=100 GeV] 10−2 h → χχ 10−2 h → χχ χ → cbs, mχ = 10 GeV (comb.) χ → τ τ ν , mχ = 10 GeV (2MSVx) 10−3 ATLAS χ → cbs, mχ = 30 GeV (comb.) 10−3 ATLAS χ → τ τ ν , mχ = 30 GeV (2MSVx) s=13 TeV, 36.1 fb-1 χ → cbs, mχ = 50 GeV (comb.) s=13 TeV, 36.1 fb-1 χ → τ τ ν , mχ = 50 GeV (2MSVx) 10−4 χ → cbs, mχ = 100 GeV (2MSVx) 10−4 χ → τ τ ν , mχ = 100 GeV (2MSVx) 10−2 10−1 1 10 102 103 10−2 10−1 1 10 102 103 χ proper lifetime (cτ) [m] χ proper lifetime (cτ) [m] (c) (d) FIG. 13. Observed limits obtained for all the baryogenesis benchmark samples. Limits for the on-shell h → χχ production in (a), (b) and (c) are obtained from the combination of 2MSVx and 1MSVx þ Emiss T strategies, while for the off-shell sample (mχ ¼ 100 GeV) the limits shown are obtained from the 2MSVx strategy only. Limits for the χ → ττν channel shown in (d) are obtained from the 2MSVx strategy only. For reference, the black solid and dashed lines show respectively the 100% and 10% σ × B assuming the SM Higgs boson total production cross section, while the red dash-dotted line reports the 100% σ × B for the off-shell h → χχ production with mχ ¼ 100 GeV, which is equal to 7 fb. section for pp → g̃g̃ [83] and B represents the branching Table XII summarizes the lifetime ranges excluded by fraction for g̃ → S̃g, assuming that both S̃ → SG̃ and the analysis presented in this paper for branching fractions S → gg have 100% branching fraction. of 10% and 1% for the scalar boson with mΦ ¼ 125 GeV Figures 11–13 show the observed limits for all the MC decaying into two long-lived scalars. The results are benchmark samples considered in this paper. The limits substantially improved compared to the Run 1 analysis, were obtained from the combination of 2MSVx and where for 25 and 40 GeV long-lived scalar masses the cτ 1MSVx+AO strategies, performing a simultaneous fit of the 2MSVx and 1MSVx+AO likelihood functions, except TABLE XII. Ranges of mean proper lifetime excluded at for the scalar boson samples with mΦ ¼ 100 GeV and 95% C.L. for scalar boson benchmark models with mΦ > 125 GeV, stealth SUSY with mg̃ ¼ 250 GeV (both mΦ ¼ 125 GeV, assuming production cross sections equal to barrel and end caps regions) and mg̃ ¼ 500 GeV (end caps 10% or 1% of the SM Higgs boson production cross section [82] region), baryogenesis with mχ ¼ 100 GeV and baryogen- for the combination of 2MSVx and 1MSVx þ EmissT strategies. esis χ → ττν benchmark samples. In these cases, the Φð125Þ → ss Excluded cτ range [m] ABCD method developed for the analysis reported in this paper was found to be not optimal due to a large ms [GeV] 10% 1% contamination by signal events in the VR or small 5 0.04–10.8 0.1–1.6 signal-background separation for one of the variables of 8 0.07–15 0.14–3.8 the ABCD plane. For those samples, the 2MSVx strategy 15 0.1–58 0.22–10.8 provides strong limits and only those results are presented 25 0.2–149 0.4–25 in this paper. 40 0.3–221 0.7–39 052005-19 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) ranges excluded for 1% branching fraction were respec- BMWFW and FWF, Austria; Azerbaijan National tively 1.10–5.35 m and 2.82–7.45 m, while for lower long- Academy of Sciences, Azerbaijan; State Science and lived scalar masses the Run 1 analysis did not have Technology Committee, Belarus; CNPq and FAPESP, sensitivity at this level. Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; XII. SUMMARY COLCIENCIAS, Colombia; MSMT CR, MPO CR and This paper presents the results of a search for long-lived VSC CR, Czech Republic; DNRF and Danish Natural −1 Science Research Council, Denmark; Institut national de pffiffiffi particles using 36.1 fb of proton-proton collisions neutral physique nucléaire et de physique des particules, Centre at s ¼ 13 TeV recorded at the LHC by the ATLAS detector in 2015 and 2016. Three separate strategies have National de la Recherche Scientifique, Institut de recherche been considered: two displaced vertices in the muon sur les lois fondamentales de l'Univers, Direction des spectrometer (MS), one displaced vertex in the MS with Sciences de la Matière, Commissariat à l'Énergie two additional prompt jets, and one displaced vertex in the Atomique, France; Shota Rustaveli National Science Foundation of Georgia, Georgia; BMBF, HGF, and MS with EmissT > 30 GeV. The observed number of events MPG, Germany; General Secretariat for Research and are consistent with the expected background and exclusion limits on the LLP production cross section as a function Technology, Greece; RGC, Hong Kong SAR, China; ISF of its proper lifetime were computed for the theoretical and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, benchmark models. Japan; CNRST, Morocco; NWO, Netherlands; RCN, The results reported here are interpreted in terms of a Norway; MNiSW and NCN, Poland; FCT, Portugal; scalar portal model similar to hidden-valley models where a Ministry of National Education, Institute of Atomic boson can decay into two long-lived scalars, a stealth Physics, Romania; Ministry of Education and Science of SUSY model where each of the two long-lived singlino are the Russian Federation of Russia and NRC KI, Russian produced from the gluino in association with a prompt jet, Federation; Joint Institute for Nuclear Research; Ministry and a Higgs-boson-mediated baryogenesis model where of Education, Science and Technological Development, the long-lived χ can decay into jets or leptons that violate Serbia; Ministry of Education, Science, Research and the baryon and/or lepton number conservation. Sport, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, The two-vertex search was performed with the same South Africa; MINECO, Spain; Swedish Research Council strategy as adopted in Run 1 and benefits from very low and Wallenberg Foundation, Sweden; Secretariat for background, but at large ðcτÞ its sensitivity scales as Education and Research, SNSF and Cantons of Bern 1=ðcτÞ2 , where τ is the proper lifetime of the LLP. The and Geneva, Switzerland; MOST, Taiwan; TAEK, increased statistics and the analysis enhancements have Turkey; STFC, United Kingdom; DOE and NSF, United improved the cross-section sensitivity for some of the States of America. In addition, individual groups and Φ → ss decays by about an order of magnitude compared members have received support from BCKDF, to the ATLAS Run 1 analysis, and extended the sensitivity CANARIE, CRC and Compute Canada, Canada; COST, for the stealth SUSY model to higher gluino masses that ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie could not be reached with the Run 1 search. Actions, European Union; Investissements d’ Avenir Labex The one-vertex search extends the sensitivity, which scales and Idex, ANR, France; DFG and AvH Foundation, as 1=ðcτÞ at large ðcτÞ, to much longer lifetimes. For the low- Germany; Herakleitos, Thales and Aristeia programmes mass samples [Φð125Þ → ss and Higgs portal baryogenesis] co-financed by EU-ESF and the Greek NSRF, Greece; the sensitivity at shorter lifetimes is weaker than that attained BSF-NSF and GIF, Israel; CERCA Programme Generalitat with the two-MS-vertex search, while for the stealth SUSY de Catalunya, Spain; The Royal Society and Leverhulme model in the high-mass regime (mg̃ > 500 GeV) the con- Trust, United Kingdom. The crucial computing support tribution of the one-MS-vertex search is dominant in the from all WLCG partners is acknowledged gratefully, in whole spectrum of proper lifetimes. particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, ACKNOWLEDGMENTS Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), We thank CERN for the very successful operation of the ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 LHC, as well as the support staff from our institutions facilities worldwide and large non-WLCG resource pro- without whom ATLAS could not be operated efficiently. viders. Major contributors of computing resources are We acknowledge the support of ANPCyT, Argentina; listed in Ref. [84]. Yerevan Physics Institute, Armenia; ARC, Australia; 052005-20 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) [1] A. Fradette and M. 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Chiu,173 M. V. Chizhov,77 K. Choi,63 A. R. Chomont,129 S. Chouridou,159 Y. S. Chow,118 V. Christodoulou,92 M. C. Chu,61a J. Chudoba,138 A. J. Chuinard,101 J. J. Chwastowski,82 L. Chytka,127 D. Cinca,45 V. Cindro,89 I. A. Cioară,24 A. Ciocio,18 F. Cirotto,67a,67b Z. H. Citron,177 M. Citterio,66a A. Clark,52 M. R. Clark,38 P. J. Clark,48 C. Clement,43a,43b Y. Coadou,99 M. Cobal,64a,64c A. Coccaro,53b,53a J. Cochran,76 H. Cohen,158 A. E. C. Coimbra,177 L. Colasurdo,117 B. Cole,38 A. P. Colijn,118 J. Collot,56 P. Conde Muiño,137a,m E. Coniavitis,50 S. H. Connell,32b I. A. Connelly,98 S. Constantinescu,27b F. Conventi,67a,n A. M. Cooper-Sarkar,132 F. Cormier,172 K. J. R. Cormier,164 L. D. Corpe,92 M. Corradi,70a,70b E. E. Corrigan,94 F. Corriveau,101,o A. Cortes-Gonzalez,35 M. J. Costa,171 F. Costanza,5 D. Costanzo,146 G. Cottin,31 G. Cowan,91 B. E. Cox,98 J. Crane,98 K. Cranmer,122 S. J. Crawley,55 R. A. Creager,134 G. Cree,33 S. Crépé-Renaudin,56 F. Crescioli,133 M. Cristinziani,24 V. Croft,122 G. Crosetti,40b,40a A. Cueto,96 T. Cuhadar Donszelmann,146 A. R. Cukierman,150 S. Czekierda,82 P. Czodrowski,35 M. J. Da Cunha Sargedas De Sousa,58b C. Da Via,98 W. Dabrowski,81a T. Dado,28a,p S. Dahbi,34e T. Dai,103 F. Dallaire,107 C. Dallapiccola,100 M. Dam,39 G. D’amen,23b,23a J. Damp,97 J. R. Dandoy,134 M. F. Daneri,30 N. P. Dang,178,g N. D Dann,98 M. Danninger,172 V. Dao,35 G. Darbo,53b S. Darmora,8 O. Dartsi,5 A. Dattagupta,128 T. Daubney,44 S. D’Auria,55 W. Davey,24 C. David,44 T. Davidek,140 D. R. Davis,47 E. Dawe,102 I. Dawson,146 K. De,8 R. De Asmundis,67a A. De Benedetti,125 M. De Beurs,118 S. De Castro,23b,23a S. De Cecco,70a,70b N. De Groot,117 P. de Jong,118 H. De la Torre,104 F. De Lorenzi,76 A. De Maria,51,q D. De Pedis,70a A. De Salvo,70a U. De Sanctis,71a,71b M. De Santis,71a,71b A. De Santo,153 K. De Vasconcelos Corga,99 J. B. De Vivie De Regie,129 C. Debenedetti,143 D. V. Dedovich,77 N. Dehghanian,3 M. Del Gaudio,40b,40a J. Del Peso,96 Y. Delabat Diaz,44 D. Delgove,129 F. Deliot,142 C. M. Delitzsch,7 M. Della Pietra,67a,67b D. Della Volpe,52 A. Dell’Acqua,35 L. Dell’Asta,25 M. Delmastro,5 C. Delporte,129 P. A. Delsart,56 D. A. DeMarco,164 S. Demers,180 M. Demichev,77 S. P. Denisov,121 D. Denysiuk,118 L. D’Eramo,133 D. Derendarz,82 J. E. Derkaoui,34d F. Derue,133 P. Dervan,88 K. Desch,24 C. Deterre,44 K. Dette,164 M. R. Devesa,30 P. O. Deviveiros,35 A. Dewhurst,141 S. Dhaliwal,26 F. A. Di Bello,52 A. Di Ciaccio,71a,71b L. Di Ciaccio,5 W. K. Di Clemente,134 C. Di Donato,67a,67b A. Di Girolamo,35 B. Di Micco,72a,72b R. Di Nardo,100 K. F. Di Petrillo,57 R. Di Sipio,164 D. Di Valentino,33 C. Diaconu,99 M. Diamond,164 F. A. Dias,39 T. Dias Do Vale,137a M. A. Diaz,144a J. Dickinson,18 E. B. Diehl,103 J. Dietrich,19 S. Díez Cornell,44 A. Dimitrievska,18 J. Dingfelder,24 F. Dittus,35 F. Djama,99 T. Djobava,156b J. I. Djuvsland,59a M. A. B. Do Vale,78c M. Dobre,27b D. Dodsworth,26 C. Doglioni,94 J. Dolejsi,140 Z. Dolezal,140 M. Donadelli,78d J. Donini,37 A. D’onofrio,90 M. D’Onofrio,88 J. Dopke,141 A. Doria,67a M. T. Dova,86 A. T. Doyle,55 E. Drechsler,51 E. Dreyer,149 T. Dreyer,51 Y. Du,58b F. Dubinin,108 M. Dubovsky,28a A. Dubreuil,52 E. Duchovni,177 G. Duckeck,112 A. Ducourthial,133 O. A. Ducu,107,r D. Duda,113 A. Dudarev,35 A. C. Dudder,97 E. M. Duffield,18 L. Duflot,129 M. Dührssen,35 C. Dülsen,179 M. Dumancic,177 A. E. Dumitriu,27b,s A. K. Duncan,55 M. Dunford,59a A. Duperrin,99 H. Duran Yildiz,4a M. Düren,54 A. Durglishvili,156b D. Duschinger,46 B. Dutta,44 D. Duvnjak,1 M. Dyndal,44 S. Dysch,98 B. S. Dziedzic,82 C. Eckardt,44 K. M. Ecker,113 R. C. Edgar,103 T. Eifert,35 052005-24 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) G. Eigen,17 K. Einsweiler,18 T. Ekelof,169 M. El Kacimi,34c R. El Kosseifi,99 V. Ellajosyula,99 M. Ellert,169 F. Ellinghaus,179 A. A. Elliot,90 N. Ellis,35 J. Elmsheuser,29 M. Elsing,35 D. Emeliyanov,141 Y. Enari,160 J. S. Ennis,175 M. B. Epland,47 J. Erdmann,45 A. Ereditato,20 S. Errede,170 M. Escalier,129 C. Escobar,171 O. Estrada Pastor,171 A. I. Etienvre,142 E. Etzion,158 H. Evans,63 A. Ezhilov,135 M. Ezzi,34e F. Fabbri,55 L. Fabbri,23b,23a V. Fabiani,117 G. Facini,92 R. M. Faisca Rodrigues Pereira,137a R. M. Fakhrutdinov,121 S. Falciano,70a P. J. Falke,5 S. Falke,5 J. Faltova,140 Y. Fang,15a M. Fanti,66a,66b A. Farbin,8 A. Farilla,72a E. M. Farina,68a,68b T. Farooque,104 S. Farrell,18 S. M. Farrington,175 P. Farthouat,35 F. Fassi,34e P. Fassnacht,35 D. Fassouliotis,9 M. Faucci Giannelli,48 A. Favareto,53b,53a W. J. Fawcett,31 L. Fayard,129 O. L. Fedin,135,t W. Fedorko,172 M. Feickert,41 S. Feigl,131 L. Feligioni,99 C. Feng,58b E. J. Feng,35 M. Feng,47 M. J. Fenton,55 A. B. Fenyuk,121 L. Feremenga,8 J. Ferrando,44 A. Ferrari,169 P. Ferrari,118 R. Ferrari,68a D. E. Ferreira de Lima,59b A. Ferrer,171 D. Ferrere,52 C. Ferretti,103 F. Fiedler,97 A. Filipčič,89 F. Filthaut,117 K. D. Finelli,25 M. C. N. Fiolhais,137a,137c,u L. Fiorini,171 C. Fischer,14 W. C. Fisher,104 N. Flaschel,44 I. Fleck,148 P. Fleischmann,103 R. R. M. Fletcher,134 T. Flick,179 B. M. Flierl,112 L. M. Flores,134 L. R. Flores Castillo,61a F. M. Follega,73a,73b N. Fomin,17 G. T. Forcolin,73a,73b A. Formica,142 F. A. Förster,14 A. C. Forti,98 A. G. Foster,21 D. Fournier,129 H. Fox,87 S. Fracchia,146 P. Francavilla,69a,69b M. Franchini,23b,23a S. Franchino,59a D. Francis,35 L. Franconi,131 M. Franklin,57 M. Frate,168 M. Fraternali,68a,68b A. N. Fray,90 D. Freeborn,92 S. M. Fressard-Batraneanu,35 B. Freund,107 W. S. Freund,78b E. M. Freundlich,45 D. C. Frizzell,125 D. Froidevaux,35 J. A. Frost,132 C. Fukunaga,161 E. Fullana Torregrosa,171 T. Fusayasu,114 J. Fuster,171 O. Gabizon,157 A. Gabrielli,23b,23a A. Gabrielli,18 G. P. Gach,81a S. Gadatsch,52 P. Gadow,113 G. Gagliardi,53b,53a L. G. Gagnon,107 C. Galea,27b B. Galhardo,137a,137c E. J. Gallas,132 B. J. Gallop,141 P. Gallus,139 G. Galster,39 R. Gamboa Goni,90 K. K. Gan,123 S. Ganguly,177 J. Gao,58a Y. Gao,88 Y. S. Gao,150,h C. García,171 J. E. García Navarro,171 J. A. García Pascual,15a M. Garcia-Sciveres,18 R. W. Gardner,36 N. Garelli,150 V. Garonne,131 K. Gasnikova,44 A. Gaudiello,53b,53a G. Gaudio,68a I. L. Gavrilenko,108 A. Gavrilyuk,109 C. Gay,172 G. Gaycken,24 E. N. Gazis,10 C. N. P. Gee,141 J. Geisen,51 M. Geisen,97 M. P. Geisler,59a K. Gellerstedt,43a,43b C. Gemme,53b M. H. Genest,56 C. Geng,103 S. Gentile,70a,70b S. George,91 D. Gerbaudo,14 G. Gessner,45 S. Ghasemi,148 M. Ghasemi Bostanabad,173 M. Ghneimat,24 B. Giacobbe,23b S. Giagu,70a,70b N. Giangiacomi,23b,23a P. Giannetti,69a A. Giannini,67a,67b S. M. Gibson,91 M. Gignac,143 D. Gillberg,33 G. Gilles,179 D. M. Gingrich,3,f M. P. Giordani,64a,64c F. M. Giorgi,23b P. F. Giraud,142 P. Giromini,57 G. Giugliarelli,64a,64c D. Giugni,66a F. Giuli,132 M. Giulini,59b S. Gkaitatzis,159 I. Gkialas,9,v E. L. Gkougkousis,14 P. Gkountoumis,10 L. K. Gladilin,111 C. Glasman,96 J. Glatzer,14 P. C. F. Glaysher,44 A. Glazov,44 M. Goblirsch-Kolb,26 J. Godlewski,82 S. Goldfarb,102 T. Golling,52 D. Golubkov,121 A. Gomes,137a,137b R. Goncalves Gama,78a R. Gonçalo,137a G. Gonella,50 L. Gonella,21 A. Gongadze,77 F. Gonnella,21 J. L. Gonski,57 S. González de la Hoz,171 S. Gonzalez-Sevilla,52 L. Goossens,35 P. A. Gorbounov,109 H. A. Gordon,29 B. Gorini,35 E. Gorini,65a,65b A. Gorišek,89 A. T. Goshaw,47 C. Gössling,45 M. I. Gostkin,77 C. A. Gottardo,24 C. R. Goudet,129 D. Goujdami,34c A. G. Goussiou,145 N. Govender,32b,w C. Goy,5 E. Gozani,157 I. Grabowska-Bold,81a P. O. J. Gradin,169 E. C. Graham,88 J. Gramling,168 E. Gramstad,131 S. Grancagnolo,19 V. Gratchev,135 P. M. Gravila,27f F. G. Gravili,65a,65b C. Gray,55 H. M. Gray,18 Z. D. Greenwood,93,x C. Grefe,24 K. Gregersen,94 I. M. Gregor,44 P. Grenier,150 K. Grevtsov,44 N. A. Grieser,125 J. Griffiths,8 A. A. Grillo,143 K. Grimm,150,y S. Grinstein,14,z Ph. Gris,37 J.-F. Grivaz,129 S. Groh,97 E. Gross,177 J. Grosse-Knetter,51 G. C. Grossi,93 Z. J. Grout,92 C. Grud,103 A. Grummer,116 L. Guan,103 W. Guan,178 J. Guenther,35 A. Guerguichon,129 F. Guescini,165a D. Guest,168 R. Gugel,50 B. Gui,123 T. Guillemin,5 S. Guindon,35 U. Gul,55 C. Gumpert,35 J. Guo,58c W. Guo,103 Y. Guo,58a,aa Z. Guo,99 R. Gupta,41 S. Gurbuz,12c G. Gustavino,125 B. J. Gutelman,157 P. Gutierrez,125 C. Gutschow,92 C. Guyot,142 M. P. Guzik,81a C. Gwenlan,132 C. B. Gwilliam,88 A. Haas,122 C. Haber,18 H. K. Hadavand,8 N. Haddad,34e A. Hadef,58a S. Hageböck,24 M. Hagihara,166 H. Hakobyan,181,a M. Haleem,174 J. Haley,126 G. Halladjian,104 G. D. Hallewell,99 K. Hamacher,179 P. Hamal,127 K. Hamano,173 A. Hamilton,32a G. N. Hamity,146 K. Han,58a,bb L. Han,58a S. Han,15d K. Hanagaki,79,cc M. Hance,143 D. M. Handl,112 B. Haney,134 R. Hankache,133 P. Hanke,59a E. Hansen,94 J. B. Hansen,39 J. D. Hansen,39 M. C. Hansen,24 P. H. Hansen,39 K. Hara,166 A. S. Hard,178 T. Harenberg,179 S. Harkusha,105 P. F. Harrison,175 N. M. Hartmann,112 Y. Hasegawa,147 A. Hasib,48 S. Hassani,142 S. Haug,20 R. Hauser,104 L. Hauswald,46 L. B. Havener,38 M. Havranek,139 C. M. Hawkes,21 R. J. Hawkings,35 D. Hayden,104 C. Hayes,152 C. P. Hays,132 J. M. Hays,90 H. S. Hayward,88 S. J. Haywood,141 M. P. Heath,48 V. Hedberg,94 L. Heelan,8 S. Heer,24 K. K. Heidegger,50 J. Heilman,33 S. Heim,44 T. Heim,18 B. Heinemann,44,dd J. J. Heinrich,112 L. Heinrich,122 C. Heinz,54 J. Hejbal,138 L. Helary,35 A. Held,172 S. Hellesund,131 S. Hellman,43a,43b C. Helsens,35 R. C. W. Henderson,87 Y. Heng,178 S. Henkelmann,172 A. M. Henriques Correia,35 G. H. Herbert,19 H. Herde,26 V. Herget,174 Y. Hernández Jiménez,32c H. Herr,97 052005-25 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) M. G. Herrmann,112 G. Herten,50 R. Hertenberger,112 L. Hervas,35 T. C. Herwig,134 G. G. Hesketh,92 N. P. Hessey,165a J. W. Hetherly,41 S. Higashino,79 E. Higón-Rodriguez,171 K. Hildebrand,36 E. Hill,173 J. C. Hill,31 K. K. Hill,29 K. H. Hiller,44 S. J. Hillier,21 M. Hils,46 I. Hinchliffe,18 M. Hirose,130 D. Hirschbuehl,179 B. Hiti,89 O. Hladik,138 D. R. Hlaluku,32c X. Hoad,48 J. Hobbs,152 N. Hod,165a M. C. Hodgkinson,146 A. Hoecker,35 M. R. Hoeferkamp,116 F. Hoenig,112 D. Hohn,24 D. Hohov,129 T. R. Holmes,36 M. Holzbock,112 M. Homann,45 S. Honda,166 T. Honda,79 T. M. Hong,136 A. Hönle,113 B. H. Hooberman,170 W. H. Hopkins,128 Y. Horii,115 P. Horn,46 A. J. Horton,149 L. A. Horyn,36 J-Y. Hostachy,56 A. Hostiuc,145 S. Hou,155 A. Hoummada,34a J. Howarth,98 J. Hoya,86 M. Hrabovsky,127 I. Hristova,19 J. Hrivnac,129 A. Hrynevich,106 T. Hryn’ova,5 P. J. Hsu,62 S.-C. Hsu,145 Q. Hu,29 S. Hu,58c Y. Huang,15a Z. Hubacek,139 F. Hubaut,99 M. Huebner,24 F. Huegging,24 T. B. Huffman,132 E. W. Hughes,38 M. Huhtinen,35 R. F. H. Hunter,33 P. Huo,152 A. M. Hupe,33 N. Huseynov,77,e J. Huston,104 J. Huth,57 R. Hyneman,103 G. Iacobucci,52 G. Iakovidis,29 I. Ibragimov,148 L. Iconomidou-Fayard,129 Z. Idrissi,34e P. Iengo,35 R. Ignazzi,39 O. Igonkina,118,ee R. Iguchi,160 T. Iizawa,52 Y. Ikegami,79 M. Ikeno,79 D. Iliadis,159 N. Ilic,117 F. Iltzsche,46 G. Introzzi,68a,68b M. Iodice,72a K. Iordanidou,38 V. Ippolito,70a,70b M. F. Isacson,169 N. Ishijima,130 M. Ishino,160 M. Ishitsuka,162 W. Islam,126 C. Issever,132 S. Istin,157 F. Ito,166 J. M. Iturbe Ponce,61a R. Iuppa,73a,73b A. Ivina,177 H. Iwasaki,79 J. M. Izen,42 V. Izzo,67a P. Jacka,138 P. Jackson,1 R. M. Jacobs,24 V. Jain,2 G. Jäkel,179 K. B. Jakobi,97 K. Jakobs,50 S. Jakobsen,74 T. Jakoubek,138 D. O. Jamin,126 D. K. Jana,93 R. Jansky,52 J. Janssen,24 M. Janus,51 P. A. Janus,81a G. Jarlskog,94 N. Javadov,77,e T. Javůrek,35 M. Javurkova,50 F. Jeanneau,142 L. Jeanty,18 J. Jejelava,156a,ff A. Jelinskas,175 P. Jenni,50,gg J. Jeong,44 N. Jeong,44 S. Jézéquel,5 H. Ji,178 J. Jia,152 H. Jiang,76 Y. Jiang,58a Z. Jiang,150,hh S. Jiggins,50 F. A. Jimenez Morales,37 J. Jimenez Pena,171 S. Jin,15c A. Jinaru,27b O. Jinnouchi,162 H. Jivan,32c P. Johansson,146 K. A. Johns,7 C. A. Johnson,63 W. J. Johnson,145 K. Jon-And,43a,43b R. W. L. Jones,87 S. D. Jones,153 S. Jones,7 T. J. Jones,88 J. Jongmanns,59a P. M. Jorge,137a,137b J. Jovicevic,165a X. Ju,18 J. J. Junggeburth,113 A. Juste Rozas,14,z A. Kaczmarska,82 M. Kado,129 H. Kagan,123 M. Kagan,150 T. Kaji,176 E. Kajomovitz,157 C. W. Kalderon,94 A. Kaluza,97 S. Kama,41 A. Kamenshchikov,121 L. Kanjir,89 Y. Kano,160 V. A. Kantserov,110 J. Kanzaki,79 B. Kaplan,122 L. S. Kaplan,178 D. Kar,32c M. J. Kareem,165b E. Karentzos,10 S. N. Karpov,77 Z. M. Karpova,77 V. Kartvelishvili,87 A. N. Karyukhin,121 L. Kashif,178 R. D. Kass,123 A. Kastanas,151 Y. Kataoka,160 C. Kato,58d,58c J. Katzy,44 K. Kawade,80 K. Kawagoe,85 T. Kawamoto,160 G. Kawamura,51 E. F. Kay,88 V. F. Kazanin,120b,120a R. Keeler,173 R. Kehoe,41 J. S. Keller,33 E. Kellermann,94 J. J. Kempster,21 J. Kendrick,21 O. Kepka,138 S. Kersten,179 B. P. Kerševan,89 R. A. Keyes,101 M. Khader,170 F. Khalil-Zada,13 A. Khanov,126 A. G. Kharlamov,120b,120a T. Kharlamova,120b,120a E. E. Khoda,172 A. Khodinov,163 T. J. Khoo,52 E. Khramov,77 J. Khubua,156b S. Kido,80 M. Kiehn,52 C. R. Kilby,91 Y. K. Kim,36 N. Kimura,64a,64c O. M. Kind,19 B. T. King,88 D. Kirchmeier,46 J. Kirk,141 A. E. Kiryunin,113 T. Kishimoto,160 D. Kisielewska,81a V. Kitali,44 O. Kivernyk,5 E. Kladiva,28b,a T. Klapdor-Kleingrothaus,50 M. H. Klein,103 M. Klein,88 U. Klein,88 K. Kleinknecht,97 P. Klimek,119 A. Klimentov,29 R. Klingenberg,45,a T. Klingl,24 T. Klioutchnikova,35 F. F. Klitzner,112 P. Kluit,118 S. Kluth,113 E. Kneringer,74 E. B. F. G. Knoops,99 A. Knue,50 A. Kobayashi,160 D. Kobayashi,85 T. Kobayashi,160 M. Kobel,46 M. Kocian,150 P. Kodys,140 P. T. Koenig,24 T. Koffas,33 E. Koffeman,118 N. M. Köhler,113 T. Koi,150 M. Kolb,59b I. Koletsou,5 T. Kondo,79 N. Kondrashova,58c K. Köneke,50 A. C. König,117 T. Kono,79 R. Konoplich,122,ii V. Konstantinides,92 N. Konstantinidis,92 B. Konya,94 R. Kopeliansky,63 S. Koperny,81a K. Korcyl,82 K. Kordas,159 G. Koren,158 A. Korn,92 I. Korolkov,14 E. V. Korolkova,146 N. Korotkova,111 O. Kortner,113 S. Kortner,113 T. Kosek,140 V. V. Kostyukhin,24 A. Kotwal,47 A. Koulouris,10 A. Kourkoumeli-Charalampidi,68a,68b C. Kourkoumelis,9 E. Kourlitis,146 V. Kouskoura,29 A. B. Kowalewska,82 R. Kowalewski,173 T. Z. Kowalski,81a C. Kozakai,160 W. Kozanecki,142 A. S. Kozhin,121 V. A. Kramarenko,111 G. Kramberger,89 D. Krasnopevtsev,58a M. W. Krasny,133 A. Krasznahorkay,35 D. Krauss,113 J. A. Kremer,81a J. Kretzschmar,88 P. Krieger,164 K. Krizka,18 K. Kroeninger,45 H. Kroha,113 J. Kroll,138 J. Kroll,134 J. Krstic,16 U. Kruchonak,77 H. Krüger,24 N. Krumnack,76 M. C. Kruse,47 T. Kubota,102 S. Kuday,4b J. T. Kuechler,179 S. Kuehn,35 A. Kugel,59a F. Kuger,174 T. Kuhl,44 V. Kukhtin,77 R. Kukla,99 Y. Kulchitsky,105 S. Kuleshov,144b Y. P. Kulinich,170 M. Kuna,56 T. Kunigo,83 A. Kupco,138 T. Kupfer,45 O. Kuprash,158 H. Kurashige,80 L. L. Kurchaninov,165a Y. A. Kurochkin,105 M. G. Kurth,15d E. S. Kuwertz,35 M. Kuze,162 A. K. Kvam,145 J. Kvita,127 T. Kwan,101 A. La Rosa,113 J. L. La Rosa Navarro,78d L. La Rotonda,40b,40a F. La Ruffa,40b,40a C. Lacasta,171 F. Lacava,70a,70b J. Lacey,44 D. P. J. Lack,98 H. Lacker,19 D. Lacour,133 E. Ladygin,77 R. Lafaye,5 B. Laforge,133 T. Lagouri,32c S. Lai,51 S. Lammers,63 W. Lampl,7 E. Lançon,29 U. Landgraf,50 M. P. J. Landon,90 M. C. Lanfermann,52 V. S. Lang,44 J. C. Lange,14 R. J. Langenberg,35 A. J. Lankford,168 F. Lanni,29 K. Lantzsch,24 A. Lanza,68a A. Lapertosa,53b,53a S. Laplace,133 J. F. Laporte,142 T. Lari,66a 052005-26 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) F. Lasagni Manghi,23b,23a M. Lassnig,35 T. S. Lau,61a A. Laudrain,129 M. Lavorgna,67a,67b A. T. Law,143 M. Lazzaroni,66a,66b B. Le,102 O. Le Dortz,133 E. Le Guirriec,99 E. P. Le Quilleuc,142 M. LeBlanc,7 T. LeCompte,6 F. Ledroit-Guillon,56 C. A. Lee,29 G. R. Lee,144a L. Lee,57 S. C. Lee,155 B. Lefebvre,101 M. Lefebvre,173 F. Legger,112 C. Leggett,18 K. Lehmann,149 N. Lehmann,179 G. Lehmann Miotto,35 W. A. Leight,44 A. Leisos,159,jj M. A. L. Leite,78d R. Leitner,140 D. Lellouch,177 B. Lemmer,51 K. J. C. Leney,92 T. Lenz,24 B. Lenzi,35 R. Leone,7 S. Leone,69a C. Leonidopoulos,48 G. Lerner,153 C. Leroy,107 R. Les,164 A. A. J. Lesage,142 C. G. Lester,31 M. Levchenko,135 J. Levêque,5 D. Levin,103 L. J. Levinson,177 D. Lewis,90 B. Li,103 C-Q. Li,58a,kk H. Li,58b L. Li,58c M. Li,15a Q. Li,15d Q. Y. Li,58a S. Li,58d,58c X. Li,58c Y. Li,148 Z. Liang,15a B. Liberti,71a A. Liblong,164 K. Lie,61c S. Liem,118 A. Limosani,154 C. Y. Lin,31 K. Lin,104 T. H. Lin,97 R. A. Linck,63 J. H. Lindon,21 B. E. Lindquist,152 A. L. Lionti,52 E. Lipeles,134 A. Lipniacka,17 M. Lisovyi,59b T. M. Liss,170,ll A. Lister,172 A. M. Litke,143 J. D. Little,8 B. Liu,76 B. L Liu,6 H. B. Liu,29 H. Liu,103 J. B. Liu,58a J. K. K. Liu,132 K. Liu,133 M. Liu,58a P. Liu,18 Y. Liu,15a Y. L. Liu,58a Y. W. Liu,58a M. Livan,68a,68b A. Lleres,56 J. Llorente Merino,15a S. L. Lloyd,90 C. Y. Lo,61b F. Lo Sterzo,41 E. M. Lobodzinska,44 P. Loch,7 T. Lohse,19 K. Lohwasser,146 M. Lokajicek,138 B. A. Long,25 J. D. Long,170 R. E. Long,87 L. Longo,65a,65b K. A. Looper,123 J. A. Lopez,144b I. Lopez Paz,14 A. Lopez Solis,146 J. Lorenz,112 N. Lorenzo Martinez,5 M. Losada,22 P. J. Lösel,112 A. Lösle,50 X. Lou,44 X. Lou,15a A. Lounis,129 J. Love,6 P. A. Love,87 J. J. Lozano Bahilo,171 H. Lu,61a M. Lu,58a N. Lu,103 Y. J. Lu,62 H. J. Lubatti,145 C. Luci,70a,70b A. Lucotte,56 C. Luedtke,50 F. Luehring,63 I. Luise,133 L. Luminari,70a B. Lund-Jensen,151 M. S. Lutz,100 P. M. Luzi,133 D. Lynn,29 R. Lysak,138 E. Lytken,94 F. Lyu,15a V. Lyubushkin,77 H. Ma,29 L. L. Ma,58b Y. Ma,58b G. Maccarrone,49 A. Macchiolo,113 C. M. Macdonald,146 J. Machado Miguens,134,137b D. Madaffari,171 R. Madar,37 W. F. Mader,46 A. Madsen,44 N. Madysa,46 J. Maeda,80 K. Maekawa,160 S. Maeland,17 T. Maeno,29 A. S. Maevskiy,111 V. Magerl,50 C. Maidantchik,78b T. Maier,112 A. Maio,137a,137b,137d O. Majersky,28a S. Majewski,128 Y. Makida,79 N. Makovec,129 B. Malaescu,133 Pa. Malecki,82 V. P. Maleev,135 F. Malek,56 U. Mallik,75 D. Malon,6 C. Malone,31 S. Maltezos,10 S. Malyukov,35 J. Mamuzic,171 G. Mancini,49 I. Mandić,89 J. Maneira,137a L. Manhaes de Andrade Filho,78a J. Manjarres Ramos,46 K. H. Mankinen,94 A. Mann,112 A. Manousos,74 B. Mansoulie,142 J. D. Mansour,15a M. Mantoani,51 S. Manzoni,66a,66b G. Marceca,30 L. March,52 L. Marchese,132 G. Marchiori,133 M. Marcisovsky,138 C. A. Marin Tobon,35 M. Marjanovic,37 D. E. Marley,103 F. Marroquim,78b Z. Marshall,18 M. U. F Martensson,169 S. Marti-Garcia,171 C. B. Martin,123 T. A. Martin,175 V. J. Martin,48 B. Martin dit Latour,17 M. Martinez,14,z V. I. Martinez Outschoorn,100 S. Martin-Haugh,141 V. S. Martoiu,27b A. C. Martyniuk,92 A. Marzin,35 L. Masetti,97 T. Mashimo,160 R. Mashinistov,108 J. Masik,98 A. L. Maslennikov,120b,120a L. H. Mason,102 L. Massa,71a,71b P. Massarotti,67a,67b P. Mastrandrea,5 A. Mastroberardino,40b,40a T. Masubuchi,160 P. Mättig,179 J. Maurer,27b B. Maček,89 S. J. Maxfield,88 D. A. Maximov,120b,120a R. Mazini,155 I. Maznas,159 S. M. Mazza,143 N. C. Mc Fadden,116 G. Mc Goldrick,164 S. P. Mc Kee,103 A. McCarn,103 T. G. McCarthy,113 L. I. McClymont,92 E. F. McDonald,102 J. A. Mcfayden,35 G. Mchedlidze,51 M. A. McKay,41 K. D. McLean,173 S. J. McMahon,141 P. C. McNamara,102 C. J. McNicol,175 R. A. McPherson,173,o J. E. Mdhluli,32c Z. A. Meadows,100 S. Meehan,145 T. M. Megy,50 S. Mehlhase,112 A. Mehta,88 T. Meideck,56 B. Meirose,42 D. Melini,171,mm B. R. Mellado Garcia,32c J. D. Mellenthin,51 M. Melo,28a F. Meloni,44 A. Melzer,24 S. B. Menary,98 E. D. Mendes Gouveia,137a L. Meng,88 X. T. Meng,103 A. Mengarelli,23b,23a S. Menke,113 E. Meoni,40b,40a S. Mergelmeyer,19 C. Merlassino,20 P. Mermod,52 L. Merola,67a,67b C. Meroni,66a F. S. Merritt,36 A. Messina,70a,70b J. Metcalfe,6 A. S. Mete,168 C. Meyer,134 J. Meyer,157 J-P. Meyer,142 H. Meyer Zu Theenhausen,59a F. Miano,153 R. P. Middleton,141 L. Mijović,48 G. Mikenberg,177 M. Mikestikova,138 M. Mikuž,89 M. Milesi,102 A. Milic,164 D. A. Millar,90 D. W. Miller,36 A. Milov,177 D. A. Milstead,43a,43b A. A. Minaenko,121 M. Miñano Moya,171 I. A. Minashvili,156b A. I. Mincer,122 B. Mindur,81a M. Mineev,77 Y. Minegishi,160 Y. Ming,178 L. M. Mir,14 A. Mirto,65a,65b K. P. Mistry,134 T. Mitani,176 J. Mitrevski,112 V. A. Mitsou,171 A. Miucci,20 P. S. Miyagawa,146 A. Mizukami,79 J. U. Mjörnmark,94 T. Mkrtchyan,181 M. Mlynarikova,140 T. Moa,43a,43b K. Mochizuki,107 P. Mogg,50 S. Mohapatra,38 S. Molander,43a,43b R. Moles-Valls,24 M. C. Mondragon,104 K. Mönig,44 J. Monk,39 E. Monnier,99 A. Montalbano,149 J. Montejo Berlingen,35 F. Monticelli,86 S. Monzani,66a N. Morange,129 D. Moreno,22 M. Moreno Llácer,35 P. Morettini,53b M. Morgenstern,118 S. Morgenstern,46 D. Mori,149 M. Morii,57 M. Morinaga,176 V. Morisbak,131 A. K. Morley,35 G. Mornacchi,35 A. P. Morris,92 J. D. Morris,90 L. Morvaj,152 P. Moschovakos,10 M. Mosidze,156b H. J. Moss,146 J. Moss,150,nn K. Motohashi,162 R. Mount,150 E. Mountricha,35 E. J. W. Moyse,100 S. Muanza,99 F. Mueller,113 J. Mueller,136 R. S. P. Mueller,112 D. Muenstermann,87 G. A. Mullier,20 F. J. Munoz Sanchez,98 P. Murin,28b W. J. Murray,175,141 A. Murrone,66a,66b M. Muškinja,89 C. Mwewa,32a A. G. Myagkov,121,oo J. Myers,128 M. Myska,139 B. P. Nachman,18 O. Nackenhorst,45 K. Nagai,132 K. Nagano,79 Y. Nagasaka,60 M. Nagel,50 E. Nagy,99 052005-27 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) A. M. Nairz,35 Y. Nakahama,115 K. Nakamura,79 T. Nakamura,160 I. Nakano,124 H. Nanjo,130 F. Napolitano,59a R. F. Naranjo Garcia,44 R. Narayan,11 D. I. Narrias Villar,59a I. Naryshkin,135 T. Naumann,44 G. Navarro,22 R. Nayyar,7 H. A. Neal,103,a P. Y. Nechaeva,108 T. J. Neep,142 A. Negri,68a,68b M. Negrini,23b S. Nektarijevic,117 C. Nellist,51 M. E. Nelson,132 S. Nemecek,138 P. Nemethy,122 M. Nessi,35,pp M. S. Neubauer,170 M. Neumann,179 P. R. Newman,21 T. Y. Ng,61c Y. S. Ng,19 H. D. N. Nguyen,99 T. Nguyen Manh,107 E. Nibigira,37 R. B. Nickerson,132 R. Nicolaidou,142 J. Nielsen,143 N. Nikiforou,11 V. Nikolaenko,121,oo I. Nikolic-Audit,133 K. Nikolopoulos,21 P. Nilsson,29 Y. Ninomiya,79 A. Nisati,70a N. Nishu,58c R. Nisius,113 I. Nitsche,45 T. Nitta,176 T. Nobe,160 Y. Noguchi,83 M. Nomachi,130 I. Nomidis,133 M. A. Nomura,29 T. Nooney,90 M. Nordberg,35 N. Norjoharuddeen,132 T. Novak,89 O. Novgorodova,46 R. Novotny,139 L. Nozka,127 K. Ntekas,168 E. Nurse,92 F. Nuti,102 F. G. Oakham,33,f H. Oberlack,113 T. Obermann,24 J. Ocariz,133 A. Ochi,80 I. Ochoa,38 J. P. Ochoa-Ricoux,144a K. O’Connor,26 S. Oda,85 S. Odaka,79 S. Oerdek,51 A. Oh,98 S. H. Oh,47 C. C. Ohm,151 H. Oide,53b,53a M. L. Ojeda,164 H. Okawa,166 Y. Okazaki,83 Y. Okumura,160 T. Okuyama,79 A. Olariu,27b L. F. Oleiro Seabra,137a S. A. Olivares Pino,144a D. Oliveira Damazio,29 J. L. Oliver,1 M. J. R. Olsson,36 A. Olszewski,82 J. Olszowska,82 D. C. O’Neil,149 A. Onofre,137a,137e K. Onogi,115 P. U. E. Onyisi,11 H. Oppen,131 M. J. Oreglia,36 G. E. Orellana,86 Y. Oren,158 D. Orestano,72a,72b E. C. Orgill,98 N. Orlando,61b A. A. O’Rourke,44 R. S. Orr,164 B. Osculati,53b,53a,a V. O’Shea,55 R. Ospanov,58a G. Otero y Garzon,30 H. Otono,85 M. Ouchrif,34d F. Ould-Saada,131 A. Ouraou,142 Q. Ouyang,15a M. Owen,55 R. E. Owen,21 V. E. Ozcan,12c N. Ozturk,8 J. Pacalt,127 H. A. Pacey,31 K. Pachal,149 A. Pacheco Pages,14 L. Pacheco Rodriguez,142 C. Padilla Aranda,14 S. Pagan Griso,18 M. Paganini,180 G. Palacino,63 S. Palazzo,40b,40a S. Palestini,35 M. Palka,81b D. Pallin,37 I. Panagoulias,10 C. E. Pandini,35 J. G. Panduro Vazquez,91 P. Pani,35 G. Panizzo,64a,64c L. Paolozzi,52 T. D. Papadopoulou,10 K. Papageorgiou,9,v A. Paramonov,6 D. Paredes Hernandez,61b S. R. Paredes Saenz,132 B. Parida,163 A. J. Parker,87 K. A. Parker,44 M. A. Parker,31 F. Parodi,53b,53a J. A. Parsons,38 U. Parzefall,50 V. R. Pascuzzi,164 J. M. P. Pasner,143 E. Pasqualucci,70a S. Passaggio,53b F. Pastore,91 P. Pasuwan,43a,43b S. Pataraia,97 J. R. Pater,98 A. Pathak,178,g T. Pauly,35 B. Pearson,113 M. Pedersen,131 L. Pedraza Diaz,117 R. Pedro,137a,137b S. V. Peleganchuk,120b,120a O. Penc,138 C. Peng,15d H. Peng,58a B. S. Peralva,78a M. M. Perego,142 A. P. Pereira Peixoto,137a D. V. Perepelitsa,29 F. Peri,19 L. Perini,66a,66b H. Pernegger,35 S. Perrella,67a,67b V. D. Peshekhonov,77,a K. Peters,44 R. F. Y. Peters,98 B. A. Petersen,35 T. C. Petersen,39 E. Petit,56 A. Petridis,1 C. Petridou,159 P. Petroff,129 M. Petrov,132 F. Petrucci,72a,72b M. Pettee,180 N. E. Pettersson,100 A. Peyaud,142 R. Pezoa,144b T. Pham,102 F. H. Phillips,104 P. W. Phillips,141 M. W. Phipps,170 G. Piacquadio,152 E. Pianori,18 A. Picazio,100 M. A. Pickering,132 R. H. Pickles,98 R. Piegaia,30 J. E. Pilcher,36 A. D. Pilkington,98 M. Pinamonti,71a,71b J. L. Pinfold,3 M. Pitt,177 M.-A. Pleier,29 V. Pleskot,140 E. Plotnikova,77 D. Pluth,76 P. Podberezko,120b,120a R. Poettgen,94 R. Poggi,52 L. Poggioli,129 I. Pogrebnyak,104 D. Pohl,24 I. Pokharel,51 G. Polesello,68a A. Poley,18 A. Policicchio,70a,70b R. Polifka,35 A. Polini,23b C. S. Pollard,44 V. Polychronakos,29 D. Ponomarenko,110 L. Pontecorvo,35 G. A. Popeneciu,27d D. M. Portillo Quintero,133 S. Pospisil,139 K. Potamianos,44 I. N. Potrap,77 C. J. Potter,31 H. Potti,11 T. Poulsen,94 J. Poveda,35 T. D. Powell,146 M. E. Pozo Astigarraga,35 P. Pralavorio,99 S. Prell,76 D. Price,98 M. Primavera,65a S. Prince,101 N. Proklova,110 K. Prokofiev,61c F. Prokoshin,144b S. Protopopescu,29 J. Proudfoot,6 M. Przybycien,81a A. Puri,170 P. Puzo,129 J. Qian,103 Y. Qin,98 A. Quadt,51 M. Queitsch-Maitland,44 A. Qureshi,1 P. Rados,102 F. Ragusa,66a,66b G. Rahal,95 J. A. Raine,52 S. Rajagopalan,29 A. Ramirez Morales,90 T. Rashid,129 S. Raspopov,5 M. G. Ratti,66a,66b D. M. Rauch,44 F. Rauscher,112 S. Rave,97 B. Ravina,146 I. Ravinovich,177 J. H. Rawling,98 M. Raymond,35 A. L. Read,131 N. P. Readioff,56 M. Reale,65a,65b D. M. Rebuzzi,68a,68b A. Redelbach,174 G. Redlinger,29 R. Reece,143 R. G. Reed,32c K. Reeves,42 L. Rehnisch,19 J. Reichert,134 D. Reikher,158 A. Reiss,97 C. 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D 99, 052005 (2019) 32b Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa 32c School of Physics, University of the Witwatersrand, Johannesburg, South Africa 33 Department of Physics, Carleton University, Ottawa ON, Canada 34a Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies—Université Hassan II, Casablanca, Morocco 34b Centre National de l’Energie des Sciences Techniques Nucleaires (CNESTEN), Rabat, Morocco 34c Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech, Morocco 34d Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda, Morocco 34e Faculté des sciences, Université Mohammed V, Rabat, Morocco 35 CERN, Geneva, Switzerland 36 Enrico Fermi Institute, University of Chicago, Chicago, Illinois, USA 37 LPC, Université Clermont Auvergne, CNRS/IN2P3, Clermont-Ferrand, France 38 Nevis Laboratory, Columbia University, Irvington, New York, USA 39 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 40a Dipartimento di Fisica, Università della Calabria, Rende, Italy 40b INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati, Italy 41 Physics Department, Southern Methodist University, Dallas, Texas, USA 42 Physics Department, University of Texas at Dallas, Richardson, Texas, USA 43a Department of Physics, Stockholm University, Sweden 43b Oskar Klein Centre, Stockholm, Sweden 44 Deutsches Elektronen-Synchrotron DESY, Hamburg and Zeuthen, Germany 45 Lehrstuhl für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany 46 Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany 47 Department of Physics, Duke University, Durham, North Carolina, USA 48 SUPA—School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom 49 INFN e Laboratori Nazionali di Frascati, Frascati, Italy 50 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany 51 II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany 52 Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland 53a Dipartimento di Fisica, Università di Genova, Genova, Italy 53b INFN Sezione di Genova, Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 55 SUPA—School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, Massachusetts, USA 58a Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei, China 58b Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao, China 58c School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai, China 58d Tsung-Dao Lee Institute, Shanghai, China 59a Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 59b Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 61a Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China 61b Department of Physics, University of Hong Kong, Hong Kong, China 61c Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 62 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan 63 Department of Physics, Indiana University, Bloomington, Indiana, USA 64a INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy 64b ICTP, Trieste, Italy 64c Dipartimento di Chimica, Fisica e Ambiente, Università di Udine, Udine, Italy 65a INFN Sezione di Lecce, Italy 65b Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 66a INFN Sezione di Milano, Italy 66b Dipartimento di Fisica, Università di Milano, Milano, Italy 67a INFN Sezione di Napoli, Italy 052005-32 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 67b Dipartimento di Fisica, Università di Napoli, Napoli, Italy 68a INFN Sezione di Pavia, Italy 68b Dipartimento di Fisica, Università di Pavia, Pavia, Italy 69a INFN Sezione di Pisa, Italy 69b Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 70a INFN Sezione di Roma, Italy 70b Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy 71a INFN Sezione di Roma Tor Vergata, Italy 71b Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy 72a INFN Sezione di Roma Tre, Italy 72b Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy 73a INFN-TIFPA, Italy 73b Università degli Studi di Trento, Trento, Italy 74 Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria 75 University of Iowa, Iowa City, Iowa, USA 76 Department of Physics and Astronomy, Iowa State University, Ames, Iowa, USA 77 Joint Institute for Nuclear Research, Dubna, Russia 78a Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil 78b Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil 78c Universidade Federal de São João del Rei (UFSJ), São João del Rei, Brazil 78d Instituto de Física, Universidade de São Paulo, São Paulo, Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 80 Graduate School of Science, Kobe University, Kobe, Japan 81a AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow, Poland 81b Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 83 Faculty of Science, Kyoto University, Kyoto, Japan 84 Kyoto University of Education, Kyoto, Japan 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 86 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 87 Physics Department, Lancaster University, Lancaster, United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham, United Kingdom 92 Department of Physics and Astronomy, University College London, London, United Kingdom 93 Louisiana Tech University, Ruston, Los Angeles, USA 94 Fysiska institutionen, Lunds universitet, Lund, Sweden 95 Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3), Villeurbanne, France 96 Departamento de Física Teorica C-15 and CIAFF, Universidad Autónoma de Madrid, Madrid, Spain 97 Institut für Physik, Universität Mainz, Mainz, Germany 98 School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom 99 CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France 100 Department of Physics, University of Massachusetts, Amherst, Massachusetts, USA 101 Department of Physics, McGill University, Montreal QC, Canada 102 School of Physics, University of Melbourne, Victoria, Australia 103 Department of Physics, University of Michigan, Ann Arbor, Michigan, USA 104 Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, USA 105 B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus 106 Research Institute for Nuclear Problems of Byelorussian State University, Minsk, Belarus 107 Group of Particle Physics, University of Montreal, Montreal QC, Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 109 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 110 National Research Nuclear University MEPhI, Moscow, Russia 052005-33 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) 111 D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 112 Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany 113 Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany 114 Nagasaki Institute of Applied Science, Nagasaki, Japan 115 Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 116 Department of Physics and Astronomy, University of New Mexico, Albuquerque, New Mexico, USA 117 Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands 118 Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam, Netherlands 119 Department of Physics, Northern Illinois University, DeKalb, Illinois, USA 120a Budker Institute of Nuclear Physics and NSU, SB RAS, Novosibirsk, Russia 120b Novosibirsk State University Novosibirsk, Russia 121 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino, Russia 122 Department of Physics, New York University, New York, New York, USA 123 The Ohio State University, Columbus, Ohio, USA 124 Faculty of Science, Okayama University, Okayama, Japan 125 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, Oklahoma, USA 126 Department of Physics, Oklahoma State University, Stillwater, Oklahoma, USA 127 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 128 Center for High Energy Physics, University of Oregon, Eugene, Oregon, USA 129 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 130 Graduate School of Science, Osaka University, Osaka, Japan 131 Department of Physics, University of Oslo, Oslo, Norway 132 Department of Physics, Oxford University, Oxford, United Kingdom 133 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 134 Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania, USA 135 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 136 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA 137a Laboratório de Instrumentação e Física Experimental de Partículas—LIP, Portugal 137b Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal 137c Departamento de Física, Universidade de Coimbra, Coimbra, Portugal 137d Centro de Física Nuclear da Universidade de Lisboa, Lisboa, Portugal 137e Departamento de Física, Universidade do Minho, Braga, Portugal 137f Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain 137g Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 138 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 139 Czech Technical University in Prague, Prague, Czech Republic 140 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 141 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 142 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 143 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, California, USA 144a Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile 144b Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile 145 Department of Physics, University of Washington, Seattle, Washington, USA 146 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom 147 Department of Physics, Shinshu University, Nagano, Japan 148 Department Physik, Universität Siegen, Siegen, Germany 149 Department of Physics, Simon Fraser University, Burnaby BC, Canada 150 SLAC National Accelerator Laboratory, Stanford, California, USA 151 Physics Department, Royal Institute of Technology, Stockholm, Sweden 152 Departments of Physics and Astronomy, Stony Brook University, Stony Brook, New York, USA 153 Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom 154 School of Physics, University of Sydney, Sydney, Australia 155 Institute of Physics, Academia Sinica, Taipei, Taiwan 156a E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi, Georgia 052005-34 SEARCH FOR LONG-LIVED PARTICLES PRODUCED IN … PHYS. REV. D 99, 052005 (2019) 156b High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 157 Department of Physics, Technion, Israel Institute of Technology, Haifa, Israel 158 Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel 159 Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 160 International Center for Elementary Particle Physics and Department of Physics, University of Tokyo, Tokyo, Japan 161 Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan 162 Department of Physics, Tokyo Institute of Technology, Tokyo, Japan 163 Tomsk State University, Tomsk, Russia 164 Department of Physics, University of Toronto, Toronto ON, Canada 165a TRIUMF, Vancouver BC, Canada 165b Department of Physics and Astronomy, York University, Toronto ON, Canada 166 Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, Tsukuba, Japan 167 Department of Physics and Astronomy, Tufts University, Medford, Massachusetts, USA 168 Department of Physics and Astronomy, University of California Irvine, Irvine, California, USA 169 Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden 170 Department of Physics, University of Illinois, Urbana, Illinois, USA 171 Instituto de Física Corpuscular (IFIC), Centro Mixto Universidad de Valencia—CSIC, Valencia, Spain 172 Department of Physics, University of British Columbia, Vancouver BC, Canada 173 Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada 174 Fakultät für Physik und Astronomie, Julius-Maximilians-Universität Würzburg, Würzburg, Germany 175 Department of Physics, University of Warwick, Coventry, United Kingdom 176 Waseda University, Tokyo, Japan 177 Department of Particle Physics, Weizmann Institute of Science, Rehovot, Israel 178 Department of Physics, University of Wisconsin, Madison, Wisconsin, USA 179 Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische Universität Wuppertal, Wuppertal, Germany 180 Department of Physics, Yale University, New Haven, Connecticut, USA 181 Yerevan Physics Institute, Yerevan, Armenia a Deceased. b Also at Department of Physics, King’s College London, London, United Kingdom. c Also at Istanbul University, Dept. of Physics, Istanbul, Turkey. d Also at Instituto de Física Teórica de la Universidad Autónoma de Madrid, Spain. e Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan. f Also at TRIUMF, Vancouver BC, Canada. g Also at Department of Physics and Astronomy, University of Louisville, Louisville, Kentucky, USA. h Also at Department of Physics, California State University, Fresno, California, USA. i Also at Department of Physics, University of Fribourg, Fribourg, Switzerland. j Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain. k Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. l Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China. m Also at Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal. n Also at Universita di Napoli Parthenope, Napoli, Italy. o Also at Institute of Particle Physics (IPP), Canada. p Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany. q Also at Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy. r Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania. s Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France. t Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia. u Also at Borough of Manhattan Community College, City University of New York, New York, USA. v Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece. w Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa. x Also at Louisiana Tech University, Ruston, Louisiana, USA. y Also at California State University, East Bay, USA. z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain. aa Also at Department of Physics, University of Michigan, Ann Arbor, Michigan, USA. bb Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France. cc Also at Graduate School of Science, Osaka University, Osaka, Japan. 052005-35 M. AABOUD et al. PHYS. REV. D 99, 052005 (2019) dd Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. ee Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands. ff Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia. gg Also at CERN, Geneva, Switzerland. hh Also at Department of Physics, Stanford University, USA. ii Also at Manhattan College, New York, New York, USA. jj Also at Hellenic Open University, Patras, Greece. kk Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France. ll Also at The City College of New York, New York, New York, USA. mm Also at Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain. nn Also at Department of Physics, California State University, Sacramento, California, USA. oo Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. pp Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland. qq Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom. rr Also at School of Physics, Sun Yat-sen University, Guangzhou, China. ss Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates. tt Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany. uu Also at National Research Nuclear University MEPhI, Moscow, Russia. vv Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary. ww Also at Giresun University, Faculty of Engineering, Giresun, Turkey. xx Also at Institute of Physics, Academia Sinica, Taipei, Taiwan. 052005-36