PHYSICAL REVIEW D 99, 012001 (2019) Search for long-lived particles pffiffi in final states with displaced dimuon vertices in pp collisions at s = 13 TeV with the ATLAS detector M. Aaboud et al.* (ATLAS Collaboration) (Received 10 August 2018; published 3 January 2019; corrected 13 November 2019) A search is performed for a long-lived particle decaying into a final state that includes a pair of muons of pffiffiffi opposite-sign electric charge, using proton-proton collision data collected at s ¼ 13 TeV by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 32.9 fb−1 . No significant excess over the Standard Model expectation is observed. Limits at 95% confidence level on the lifetime of the long-lived particle are presented in models of new phenomena including gauge-mediated supersymmetry or decay of the Higgs boson, H, to a pair of dark photons, ZD . Lifetimes in the range cτ ¼ 1–2400 cm are excluded, depending on the parameters of the model. In the supersymmetric model, the lightest neutralino is the next-to-lightest supersymmetric particle, with a relatively long lifetime due to its weak coupling to the gravitino, the lightest supersymmetric particle. The lifetime limits are determined for very light gravitino mass and various assumptions for the neutralino mass in the range 300–1000 GeV. In the dark photon model, the lifetime limits are interpreted as exclusion contours in the plane of the coupling between the ZD and the Standard Model Z boson versus the ZD mass (in the range 20–60 GeV), for various assumptions for the H → ZD ZD branching fraction. DOI: 10.1103/PhysRevD.99.012001 I. INTRODUCTION decay to the scale of the neutron lifetime. There are a number of BSM models where long-lived particles (LLPs) The ATLAS and CMS experiments at the Large Hadron arise naturally [2,3]. Supersymmetry (SUSY) [4–9] with Collider (LHC) were conceived to address a variety of R-parity violation [10,11], general gauge-mediated (GGM) questions not fully explained within the Standard Model supersymmetry breaking [12–14], and split supersymmetry (SM) of particle physics. The data collected by the LHC [15,16] are examples where small couplings, mass scales experiments have not yet revealed evidence of physics associated with the BSM physics, or heavy mediator beyond the Standard Model (BSM). As a result, there is an particles, respectively, lead to high-mass (greater than a increased emphasis on the exploration of unusual final-state few hundred GeV) LLPs. Scenarios with low-mass LLPs signatures that would elude the searches based on exper- include hidden-valley models [17], stealth supersymmetry imental methods aimed at prompt signatures. In many [18], and dark-sector gauge bosons [3,19]. models of BSM physics there are free parameters that Events with long-lived particles may feature vertices that influence the lifetimes of the new particle states, with no are significantly displaced from the proton-proton (pp) strong motivation for assuming that all the particles decay interaction point (IP). This article presents the results of a promptly1 and thus give final states investigated with search for displaced vertices (DVs) formed by a pair of standard analysis techniques. Nor are there any strong muons of opposite-sign electric charge, denoted “OS” demands that these are stable on the detector scale and only muons. The search is designed to be sensitive to decays weakly interacting, leading to missing transverse momen- of LLPs with masses between 20 and 1100 GeV and DVs at tum signatures. Particle lifetimes in the SM, for instance, distances ranging from a few centimeters to a few meters span roughly 28 orders of magnitude [1], from the strong from the IP. The data sample consists of pp collisions at pffiffiffi s ¼ 13 TeV and an integrated luminosity of 32.9 fb−1 * Full author list given at the end of the article. collected with the ATLAS detector at the LHC. 1 For the purposes of this analysis, a promptly decaying particle Although SM decay products typically consist primarily is one with a lifetime no larger than a few tens of picoseconds. of hadrons, due to the relatively large number of color degrees of freedom for quarks, there are notable advantages Published by the American Physical Society under the terms of to searching for DVs using only tracks of identified muons: the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the design of the ATLAS muon spectrometer allows the author(s) and the published article’s title, journal citation, detection of dimuon DVs within an unusually large and DOI. Funded by SCOAP3. decay volume, free from backgrounds associated with 2470-0010=2019=99(1)=012001(32) 012001-1 © 2019 CERN, for the ATLAS Collaboration M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) vertices produced in interactions of hadrons with detector calorimeter modules optimized for electromagnetic and material [20,21]. hadronic measurements respectively. Previous searches by the ATLAS Collaboration for high- The muon spectrometer (MS) comprises separate trigger mass LLPs that decay within the inner detector to give and high-precision tracking chambers measuring the displaced dilepton vertices excluded LLP lifetimes of cτ ¼ deflection of muons in a magnetic field generated by three 0.1–100 cm [22]. ATLAS has also searched for very low superconducting air-core toroidal magnets, each with eight mass LLPs (< 10 GeV) by considering pairs of highly coils. The field integral of the toroids ranges between 2.0 collimated leptons [23], with sensitivity to LLP lifetimes and 6.0 T m across most of the detector. The MS is of cτ ¼ 0.1–20 cm. Several other LLP searches targeting a designed to detect muons in the region jηj < 2.7 and to wide range of lifetimes and signatures have been conducted provide momentum measurements with a relative resolu- by the ATLAS [24–33], CMS [34–40], LHCb [41–44], tion better than 3% over a wide transverse momentum (pT ) CDF [45], D0 [46,47], BABAR [48], Belle [49], and range and up to 10% at pT ∼ 1 TeV. It consists of a barrel ALEPH [50] collaborations. (jηj < 1.05), with an inner radius of about 500 cm, and two end cap sections (1.05 < jηj < 2.7). II. ATLAS DETECTOR Resistive-plate chambers in the barrel and thin-gap chambers in the end cap regions provide triggering The ATLAS detector [51,52] at the LHC covers nearly capability to the detector as well as ðη; ϕÞ position the entire solid angle around the collision point.2 It consists measurements with a typical spatial resolution of 5– of an inner tracking detector surrounded by a thin 10 mm. A precise momentum measurement is provided superconducting solenoid, electromagnetic and hadronic by three layers of monitored drift-tube chambers (MDT), calorimeters, and a muon spectrometer incorporating super- with each chamber providing six to eight η measurements conducting toroidal magnets. along the muon trajectory. For jηj > 2, the inner layer is The inner detector (ID) is immersed in a 2 T axial instrumented with a quadruplet of cathode-strip chambers magnetic field and provides charged-particle tracking in the (CSC) instead of MDTs. The single-hit resolution in the range jηj < 2.5. A high-granularity silicon pixel detector bending plane for the MDT and the CSC is about 80 and covers the vertex region and typically provides four 60 μm, respectively. The muon chambers are aligned with a measurements per track, the first hit being normally in precision between 30 and 60 μm. The material between the the innermost layer. It is followed by a silicon microstrip IP and the MS ranges from approximately 100 to 190 radi- tracker, which usually provides four two-dimensional ation lengths, depending on η, and consists mostly of the measurement points per track. These silicon detectors calorimeters. are complemented by a transition radiation tracker, which Online event selection is performed with a two-level enables radially extended track reconstruction up to trigger system [53]. A hardware-based level-1 trigger jηj ¼ 2.0. The transition radiation tracker also provides which uses information from the MS trigger chambers electron identification information based on the fraction of and the calorimeters is followed by a software-based hits (typically 30 in total) above a higher energy-deposit trigger. threshold corresponding to transition radiation. The calorimeter system covers the pseudorapidity range jηj < 4.9. Within the region jηj < 3.2, electromagnetic III. DATA AND SIMULATED SAMPLES calorimetry is provided by barrel and end cap high- Proton-proton collision data, collectedpatffiffiffi the LHC during granularity lead/liquid-argon (LAr) sampling calorimeters, 2016, with a center-of-mass energy s ¼ 13 TeV, are with an additional thin LAr presampler covering jηj < 1.8 analyzed. After application of detector and data-quality to correct for energy loss in material upstream of the requirements, the integrated luminosity of the data sample calorimeters. Hadronic calorimetry is provided by a steel/ is 32.9 fb−1 . scintillator-tile calorimeter, segmented into three barrel Samples of Monte Carlo (MC) simulated events are used structures within jηj < 1.7, and two copper/LAr hadronic for studies of both the LLP signal and background end cap calorimeters. The solid-angle coverage is com- processes. The detector response was simulated with pleted with forward copper/LAr and tungsten/LAr GEANT4 [54,55], and the events were processed with the same reconstruction software as used for the data. The 2 ATLAS uses a right-handed coordinate system with its distribution of the number of additional pp collisions in origin at the nominal interaction point in the center of the the same or neighboring bunch crossings (“pileup”) is detector and the z axis along the beam pipe. The x axis points accounted for by overlaying minimum-bias events simu- from the IP to the center of the LHC ring, and the y axis points lated with PYTHIA8 [56] using the A2 set of tuned upwards. Cylindrical coordinates ðr; ϕÞ are used in the transverse plane, ϕ being the azimuthal angle around the z axis. The parameters (tune) [57] and MSTW2008LO parton distri- pseudorapidity is defined in terms of the polar angle θ as bution function (PDF) set [58]. The pileup profile in the η ¼ − ln ptan ðθ=2Þ. Angular ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi distances are measured in units of MC samples is reweighted to match the distribution ΔR ≡ ðΔηÞ2 þ ðΔϕÞ2 . observed in the data. 012001-2 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) (a) (b) FIG. 1. Diagrams representing BSM processes considered signals in this article: (a) long-lived neutralino χ̃ 01 decay in a GGM scenario, and (b) long-lived dark photons ZD produced from Higgs boson decay. The quarks, q, may have different flavors (excluding the top quark). The symbol f represents fermions lighter than half the mass of the Z boson. A. BSM signal samples fraction for the decay χ̃ 01 → ZG̃ can be Oð1Þ. The lifetime Monte Carlo simulated samples from two different BSM of the χ̃ 01 is determined by F0 [or, alternatively, by mG̃, physics models are used to tune selection criteria and to according to Eq. (1)] and its mass mχ̃ 01 , evaluate signal efficiencies for use in converting signal    pffiffiffiffiffiffi 4 yields into cross sections. The chosen models, a general 16πF20 100 GeV 5 F0 gauge-mediated supersymmetry and dark-sector gauge cτχ̃ 01 ∝ 5 ≈ × 1 cm; mχ̃ 0 mχ̃ 01 300 TeV boson model, represent a variety of BSM physics possibil- 1 ities, as well as final-state topologies and kinematics, to pffiffiffiffiffiffi which the analysis may be sensitive. The two processes are and hence χ̃ 01 is long-lived (i.e., nonprompt) for F0 ¼ illustrated in Fig. 1. Samples for both models were 103 TeV to 104 TeV. generated with MADGRAPH5_AMC@NLO [59] using the In the GGM model, a pp interaction creates a pair of NNPDF23LO PDF set [60] and PYTHIA8 for parton gluinos, followed by a cascade of decays leading to showering and hadronization. The matrix elements were χ̃ 01 → ZG̃. A simplified model is used whereby the cascade calculated to next-to-leading order in the strong coupling of decays of SUSY particles is reduced to a single vertex: constant. The EVTGEN generator [61] was used for weak g̃ → qqχ̃ 01 , where q represents any of the quarks lighter than decays of heavy-flavor hadrons. The hadronization and the top quark, with equal probability for each. Six signal underlying-event parameters were set according to the samples were generated with mg̃ ¼ 1.1 TeV and χ̃ 01 masses A14 tune [57]. and lifetimes given in Table I. The value of 1.1 TeV for the In R-parity-conserving (RPC) SUSY models where gluino mass was chosen to be consistent with the value gauge interactions mediate the breaking of the supersym- used in Ref. [22], the previous search for DVs with a GGM metry, the gravitino G̃ acquires its mass from a “super- interpretation. The signal cross sections are calculated to Higgs” mechanism and may be very light: mG̃ ¼ OðkeVÞ. next-to-leading order in the strong coupling constant, The mass is given by adding the resummation of soft gluon emission at next-  pffiffiffiffiffiffi 2 to-leading-logarithm accuracy (NLO þ NLL) [63–67]. The F F0 nominal cross sections and their uncertainties are taken mG̃ ¼ pffiffiffi 0 ¼ × 2.4 eV; ð1Þ 3M Pl 100 TeV pffiffiffiffiffiffi TABLE I. MC signal samples for the GGM SUSY interpretation. where F0 is the fundamental scale of supersymmetry For a given mχ̃ 01 , the gravitino mass is chosen to give the desired breaking, typically ≳100 TeV, and MPl is the Planck lifetime. For all samples, mg̃ ¼ 1100 GeV, σðpp → g̃ g̃Þ ¼ scale. Hence, the gravitino is the lightest supersymmetric 163.5 fb, Bðχ̃ 01 → ZG̃Þ ¼ 1.0, and BðZ → μþ μ− Þ ¼ 0.03366. particle (LSP). All heavier supersymmetric particles decay promptly through cascades leading to the next-to-lightest mχ̃ 01 [GeV] cτχ̃ 01 [cm] supersymmetric particle (NLSP), which then decays into 300 100 the LSP gravitino via an interaction with a 1=F0 suppres- 300 500 sion. The NLSP, depending on model choices, is either the 700 100 lightest slepton or lightest neutralino, χ̃ 01 . For the latter case, 700 500 1000 100 chosen for this search and described in Ref. [62], if χ̃ 01 has 1000 500 a significant wino or higgsino component the branching 012001-3 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) from an envelope of cross-section predictions using differ- TABLE II. MC signal samples for the dark-sector interpreta- ent PDF sets and factorization and renormalization scales, tion. For all samples, mH ¼ 125 GeV, mHD ¼ 300 GeV, as described in Ref. [68]. σðpp → HÞ ¼ 44.1 pb (via the gluon-gluon fusion production A number of BSM theories feature a “hidden” or “dark” process) and BðH → ZD ZD Þ ¼ 0.10. sector of matter that does not interact directly with SM mZD [GeV] cτZD [cm] BðZD → μþ μ− Þ particles but may nevertheless interact weakly with SM matter via coupling to the Higgs field. These are “Higgs 20 50 0.1475 40 50 0.1370 portal” models that address the dark-matter problem and 40 500 0.1370 electroweak baryogenesis. The model considered for this 60 50 0.1066 search is one in which there exists a Uð1ÞD symmetry in the 60 500 0.1066 dark sector, and the dark vector gauge boson ZD , often called a “dark photon,” is given mass via a singlet scalar field HD that breaks the symmetry and is analogous to the number of DVs across the full fiducial decay volume of the Higgs field H in the visible SM sector [3,69]. search: approximately 0 < rvtx < 400 cm. To obtain dis- The BSM terms in the Lagrangian density include both tributions corresponding to a different lifetime, cτnew , each a hypercharge portal and a Higgs portal, providing kinetic event is given a weight. The weight wi assigned to each Z-ZD mixing [i.e., mixing between Uð1ÞY and Uð1ÞD ] and LLP i is computed as H-HD mixing, regulated by the small coupling parame- ters ϵ and ζ, respectively. There are two vector-boson τgen e−ti =τnew mass eigenstates, one that is mostly ZD and another that is wi ðti Þ ¼ · ; mostly SM Z, as well as two scalar mass eigenstates, one e−ti =τgen τnew that is mostly HD and another that is mostly H. For where the first factor reweights the exponential decay to a simplicity, the physical (mass) states are denoted by H, constant distribution and the second factor reweights to HD , Z, and ZD . the desired lifetime. The quantity ti is the proper decay In the scenario where the singlet scalar HD is heavier time of the LLP and cτgen is the lifetime assumed in than the SM H boson, which means that the process H → HD HD is kinematically forbidden, and ZD is lighter than generating the sample. The event-level weight is the half the H mass, events with a displaced dimuon vertex product of the weights for the two LLPs in each event. signature would be observable in experiments at the LHC. The event-level signal efficiency is then the sum of The ZD bosons are produced on-shell in Higgs boson weights for all events for which at least one reconstructed decays and decay to SM fermions due to their induced dimuon vertex satisfies the selection criteria, divided by couplings to the electroweak current. A small value of ϵ the total number of events generated. This scheme ensures (≲10−5 ) results in a long-lived ZD state: cτZD ∝ 1=ϵ2 . The that any dependence of the efficiency on the decay time of both LLPs in the event, and not just the one decaying to a branching fraction for H → ZD ZD is determined by the dimuon final state, is properly taken into account for each value of ζ and the masses of the scalar singlets: choice of cτnew . The lifetime reweighting technique is validated by using m2H BðH → ZD ZD Þ ∝ ζ ; a signal sample of a given cτgen to predict the efficiency for jm2HD − m2H j a different lifetime and comparing with the value directly obtained from a sample generated with that lifetime. where values as large as 25% have not yet been ruled out by constraints from Higgs coupling fits [70,71]. For ϵ ≪ 1, the ZD branching fraction to muons, BðZD → μþ μ− Þ, is inde- B. SM background samples pendent of ϵ but varies with mZD [69]: from a value of The MC simulations of background processes are used 0.1475 for mZD ¼ 20 GeV to a value of 0.1066 for only as a guide for some of the selection criteria and for mZD ¼ 60 GeV. Five signal samples were generated with categorization of the types of background, while the ZD masses and lifetimes given in Table II. The Higgs boson background yield itself is predicted from techniques that is produced via the gluon-gluon fusion process, assuming a use solely the data. The MC generators, hadronization, cross section of 44.1 pb, calculated at next-to-next-to- and showering software packages, underlying-event sim- leading order in the strong coupling constant, adding the ulation and choice of parton distribution functions are resummation of soft gluon emission at next-to-next-to- summarized in Table III. Further details about the gen- leading-logarithmic accuracy [72]. The inclusion of other erator settings used for these processes can also be found production processes was found to have a negligible impact in Refs. [73–77]. on the analysis. Each of the simulated background samples is scaled to The signal samples were generated with values of the correspond to an integrated luminosity of 32.9 fb−1 , the LLP lifetime that were chosen to provide sufficiently large size of the data sample. 012001-4 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) TABLE III. The MC generators, hadronization, and showering software package, underlying-event simulation and PDF sets used for the simulated background events. The mass range of the low-mass Drell-Yan sample is restricted to 6 < mμμ < 60 GeV. Nonperturbative tune and Sample MC generator Hard-process PDF Hadronization and showering parton-shower PDF Z þ jets POWHEG [78,79] CT10 [80] PYTHIA8 [56]+EVTGEN [61] AZNLO+CTEQ6L1 [81] Low-mass Drell-Yan POWHEG PYTHIA8+EVTGEN AZNLO+CTEQ6L1 tt̄ POWHEG CT10 PYTHIA6 [82]+EVTGEN P2012 [83]+CTEQ6L1 W þ jets POWHEG CT10 PYTHIA8 AZNLO+CTEQ6L1 ZZ POWHEG-BOX v2 [84] CT10nlo PYTHIA8 AZNLO+CTEQ6L1 WW POWHEG-BOX v2 CT10nlo PYTHIA8 AZNLO+CTEQ6L1 WZ POWHEG-BOX v2 CT10nlo PYTHIA8 AZNLO+CTEQ6L1 Single top POWHEG [85,86] CT10 PYTHIA6 P2012+CTEQ6L1 IV. EVENT SELECTION, SIGNAL EFFICIENCIES, model). All three of the muon triggers use only measure- AND BACKGROUND ESTIMATE ments in the MS to identify muons. Candidate signal events are selected by identifying μþ μ− The thresholds for the Emiss T and collimated-dimuon pairs consistent with having been produced in a vertex triggers changed during the course of 2016 data taking. displaced at least several centimeters from the IP.3 The To account for these changes, the highest available thresh- selection criteria are designed to strongly suppress back- old for each trigger is used and offline requirements are ground from SM processes that produce muons near the IP imposed corresponding to the thresholds listed in the table. while efficiently accepting signal events over a wide range Moreover, additional stricter requirements are imposed on of LLP masses, lifetimes and velocities. To retain the the corresponding offline quantity in order to ensure that greatest possible model independence, minimal require- the trigger efficiency falls on the efficiency plateau. ments are placed on other aspects of the event. For signal events with displaced dimuon vertices, the The initial event selection is performed with a combi- single-muon trigger efficiency falls off approximately nation of triggers that require either the presence of a muon linearly with jd0 j, from a maximum of about 70% at candidate or large missing transverse momentum, whose 0 cm to approximately 10% at the fiducial limit of 400 cm, due to requirements that favor muon candidates that magnitude is denoted Emiss T . Next, offline selection criteria are used to first identify suitable muon candidates, and then originate close to the IP. The calorimeter-based Emiss T trigger pairs of muons of opposite charge consistent with a DV. is employed to recover some signal efficiency. As muons The backgrounds from all SM beam-collision and non- leave little energy in the calorimeter and the Emiss T at the beam-collision processes (cosmic-ray muons or beam-halo trigger level is computed only using the calorimeter signals, particles) are estimated directly from the data. Finally, the the Emiss T trigger is an effective muon trigger. number of vertices expected from background processes is The collimated-dimuon trigger is based on compared with the observed number of vertices in data in reconstruction of muon tracks with low pT thresholds. two signal regions, distinguished by the dimuon invari- The large rates associated with the low pT thresholds are ant mass. offset by requiring two muons in the MS that are within a cone of size ΔR ¼ 0.5. The efficiency of this trigger for a given signal model is strongly dependent on the magnitude A. Trigger requirements of the boost of the particle decaying to the dimuon final Events must satisfy the requirements of at least one of state, as this determines the likelihood of the two muons four different triggers in order to achieve the best possible being found within a cone of size ΔR ¼ 0.5. The trimuon efficiency for a wide variety of signal topologies and trigger increases the efficiency for selecting events with kinematics. The triggers used and their descriptions are particles that have a relatively large branching fraction to given in Table IV. The first two triggers are highly efficient muons, as is the case of the ZD in the signal model explored for signals with high-mass states that feature muons with in this article. large transverse momentum and large transverse impact parameters, d0 , such as the GGM model, while the final two allow efficient selection of signals featuring low-mass B. Offline reconstruction and preselection states, and therefore lower-pT muons (e.g., the dark-sector Interaction vertices from the pp collisions are recon- structed from at least two tracks with pT larger than 3 The RMS spread of the z distribution of the pp interaction 400 MeV that are consistent with originating from the vertices is 47.7 mm and the spreads in the x and y directions are beam-collision region in the x-y plane. Selected events are less than 0.01 mm. required to have at least one reconstructed interaction vertex. 012001-5 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) TABLE IV. Description of triggers used to select events. The quantity ΔRμμ is the angular distance between the two muons in the collimated-dimuon trigger. Signal type Trigger Description Thresholds High mass Emiss T Missing transverse momentum T > 110 GeV Emiss Single muon Single muon restricted to the barrel region Muon jηj < 1.05 and pT > 60 GeV Low mass Collimated dimuon Two muons with small angular separation pT of muons > 15 and 20 GeV and ΔRμμ < 0.5 Trimuon Three muons pT > 6 GeV for all three muons Jet candidates are reconstructed from topological clusters momentum greater than 400 MeV, to have a minimum [87], built from energy deposits in the calorimeters calibrated number of hits in each ID subsystem and to have to the electromagnetic scale, using the anti-kt algorithm [88] jd0 j < 1 cm. Hence, these combined-muon candidates with radius parameter R ¼ 0.4. The reconstructed jets are correspond to muons produced within ∼1 cm of the x-y calibrated to the hadronic energy scale by scaling their four- position of the IP. momenta to the particle level [89]. The jets are required to To suppress background from misidentified jets as well have pT > 20 GeV and jηj < 4.4. If a jet in an event fails the as from hadron decays to muons inside jets, all muon “loose” jet-quality requirements of Ref. [90], the event is candidates are required to have at least a minimum angular vetoed in order to suppress detector noise and noncollision separation from all jets (muon-jet overlap removal) and to backgrounds [90,91]. To reduce the contamination due to satisfy track-based isolation criteria. Muon-jet overlap jets originating from pileup interactions, an additional removal is accomplished by requiring that ΔRμ−jet > requirement on the jet vertex tagger [92] output is made min ð0.4; 0.04 þ 10 GeV=pμT Þ for all jets in the event, for jets with pT < 60 GeV and jηj < 2.4. where ΔRμ−jet is the angular separation between the muon The muon reconstruction algorithm [93] starts by finding candidate and the jet in consideration. The track-based tracks in the MS, denoted MS tracks, and extrapolating isolation quantity I IDΔR¼0.4 is defined as the ratio of the scalar their trajectories towards the IP. All MS track parameters sum of pT of all ID tracks matched to the primary vertex, are expressed at the point of closest approach to the IP and and with pT > 0.5 GeV within a cone of size ΔR ¼ 0.4 their uncertainties reflect the effects of multiple Coulomb around the muon candidate, to the muon pT . To remove the scattering in the detector material. Although the highest contribution of the ID track forming the muon candidate track reconstruction efficiency is obtained for muons (if it exists), the ID track that is nearest to and within ΔR ¼ originating near the IP, appreciable efficiency is obtained 0.1 of the muon candidate and has a pT within 10% of the for muons with transverse impact parameters as large as MS-track pT is not used in the sum. Muon candidates are 200 cm. In order to optimize the resolution of the track required to have I ID ΔR¼0.4 < 0.05. The muon-jet overlap and parameters, the following criteria are imposed. The MS isolation requirements are removed in defining control tracks are required to have transverse momentum greater regions used to study backgrounds described in Sec. IV F. than 10 GeV, jηj < 2.5, measurements in each of the three Muon candidates that trigger in a small set of resistive- layers of both the precision and trigger chambers, an plate chambers that can have timing jitter are rejected. This uncertainty in the d0 measurement less than 20 cm and amounts to no more than 0.3% of selected muon candidates, to not traverse regions of the MS that are poorly aligned. which has a negligible effect on the signal acceptance. Interactions between beam protons and beam collimators To distinguish between muon candidates that originate upstream of the IP are a source of high-momentum muons, from prompt and nonprompt decays, the following classi- denoted beam-induced-background (BIB) muons, that can fication of MS tracks is used. Those for which a successful enter the ATLAS detector nearly parallel to the beam axis. ID-MS combination has been made, defined by the require- Most MS tracks generated by this process are identified and ment that the angular distance between the MS track and rejected with the method described in Ref. [91] and results nearest combined-muon track is less than 0.1, are referred in a negligible reduction in signal efficiency. to as “MScomb” muon candidates and the rest are referred Track reconstruction is performed independently in the to as “MSonly” muon candidates, as summarized in ID, and an attempt is made to match each MS track with an Table V. The large majority of MS tracks are MScomb, ID track. The two matched tracks are then used as input to a which reflects the fact that most muons are produced very combined fit that takes into account all of the ID and MS close to the IP. measurements, the energy loss in the calorimeter and multiple-scattering effects. During the fit, additional MS measurements may be added to or removed from the track C. Selection of dimuon vertices to improve the fit quality. The ID track is required to be The selection criteria described below are used to define within the ID acceptance, jηj < 2.5, to have transverse a sample of dimuon vertices (preselection) to which 012001-6 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) TABLE V. Definition of categories of muon candidates. Tracks the dimuon invariant mass, mμμ , be larger than 15 GeV. in the ID are reconstructed with maximum jd0 j of 1 cm. The ability to determine the spatial location of the vertex Muon candidate Definition varies with the pT of the muons in the vertex and the opening angle between them. The average resolutions of MScomb Successful ID-MS combination rvtx and zvtx are in the range of 2–3 cm. Cosmic-ray muons MSonly Standalone MS (no match with ID track) that pass through the detector in time with a pp collision are sometimes reconstructed as two separate MS tracks that have an opening angle of π: Δϕ ¼ π and Ση ¼ 0, additional criteria are applied to form signal regions (SRs) where Δϕ is the difference in ϕ between the two MS tracks in which data are compared to background estimates, and and Ση is the sum of their η values. Vertices formed by control regions (CRs) which are used to provide those such p MS tracks are effectively eliminated by requiring ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi background estimates. Within each event, all possible pairs of muon candidates, ðΣηÞ2 þ ðπ − ΔϕÞ2 > 0.1. both MScomb and MSonly, are formed. For each pair, the Backgrounds that contribute to the preselection sample muon candidate with the largest pT is designated the include SM proton-proton collision processes as well as “leading” muon, while the other is designated the “sub- events with muons that are not associated with the pp leading” muon. An algorithm which assumes a straight-line collision (e.g., cosmic-ray muons). The dominant contri- extrapolation of the muon trajectory from the MS inner butions to the former are low-mass Drell-Yan and Z þ jets surface towards the IP is used to determine whether or not processes, collectively referred to simply as DY. At small the two muons are consistent with originating from a values of mμμ , dimuon vertices from multijet processes are common vertex. The midpoint between the points of closest also substantial. Dimuon vertices reconstructed in tt̄ and approach along the trajectories of the two muon candidates single-top events make small contributions, while W þ jets is taken to be the three-dimensional location of the vertex. and diboson processes are found to be negligibly small This simple approach is sufficient for the purposes of this backgrounds. analysis, as the location of the putative dimuon vertex is Distributions of mμμ and signed rvtx for opposite-charge only used in defining the geometrical acceptance of the and same-charge (SS) dimuon vertices satisfying the analysis. The decay length Lvtx and projections onto the x-y preselection criteria are shown in Fig. 2. Also shown are plane and z axis, rvtx and zvtx respectively, are measured the expected contributions from the background processes relative to the IP. It is convenient to sign the vertex radius discussed above. Due to the limited number of simulated rvtx according to the following definition. If the angle multijet events, this source of background is not included in between the projections in the x-y plane of the vertex the MC distributions. Its relative contribution is expected to momentum vector (the dimuon momentum vector) and the be dominant for SS pairs and most pronounced for OS ones “flight direction” (the vector connecting the IP with the at small values of mμμ , as determined from studies of events displaced dimuon vertex) is less than π=2 then it is assigned where the muon-jet overlap and muon isolation require- a positive value, otherwise it is assigned a negative value. ments are inverted, and this is the dominant source of When the LLP decays exclusively into a pair of muons or difference between the data and MC distributions in those there is a small mass difference between the LLP and the regions of Fig. 2. The fraction of events in the data with dimuon state, the two vectors are typically closely aligned multiple dimuon vertices passing the preselection criteria and the signed rvtx more often has a positive value. is 0.065%. Examples are the dark-sector model and the GGM model The preselected dimuon vertices are divided into two for cases where there is a relatively small mass difference regions to be used in searches for low- and high-mass signal between the χ̃ 01 and the Z boson. In all cases, LLPs are models, which are summarized in Table VI. To further distinguished by relatively large values of the magnitude of suppress the DY background in the high-mass region, signed rvtx . where Z þ jets production dominates, and improve the Vertices are selected as follows. To reduce combinatorial search sensitivity, the transverse boost of the dimuon pair, background from random track crossings, the distance of defined as the ratio of the transverse momentum of the closest approach between the two straight-line extrapola- dimuon system to its invariant mass, is required to be larger tions is required to be less than 20 cm. As the vertex than 2. This reduces the DY background by approximately position is poorly measured for tracks that are nearly a factor of 20, with a small reduction in the signal parallel to each other, vertices for which the opening angle efficiencies, where the decay of a heavy BSM particle of the muon pair is less than 0.1 are rejected. Vertices are produces the dimuon state (a Z boson in the GGM model) required to be within the cylindrical fiducial volume with a relatively large boost. jrvtx j < 400 cm and jzvtx j < 600 cm. Background from The next sections describe the SR and CR selection muons with relatively low momentum in multijet events, criteria based on the designation of muon candidates as as well as ϒ decays to dimuons, is reduced by requiring that MScomb or MSonly. 012001-7 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) 107 Drell-Yan 107 Drell-Yan 6 ATLAS ATLAS 10 106 s = 13 TeV 32.9 fb-1 tt s = 13 TeV 32.9 fb-1 tt 105 μ+μ− Single top quark 105 μ+μ− Single top quark Vertices / 2 GeV Vertices / 10 cm 104 Data 104 Data 3 10 103 102 2 10 10 10 1 20 40 60 80 100 120 140 160 180 200 −400 −300 −200 −100 0 100 200 300 400 mμμ [GeV] Signed rvtx [cm] (a) (b) ATLAS Drell-Yan 104 ATLAS Drell-Yan 103 -1 -1 s = 13 TeV 32.9 fb tt s = 13 TeV 32.9 fb tt μ+μ+, μ-μ- Single top quark 103 μ+μ+, μ-μ- Single top quark Vertices / 10 cm Vertices / 2 GeV 102 Data Data 102 10 10 1 1 20 40 60 80 100 120 140 160 180 200 −400 −300 −200 −100 0 100 200 300 400 mμμ [GeV] Signed rvtx [cm] (c) (d) FIG. 2. Distributions of (a) dimuon invariant mass mμμ and (b) signed vertex radius rvtx for opposite-charge dimuon vertices satisfying the preselection requirements described in the text; (c) mμμ and (d) signed rvtx for same-charge dimuon vertices satisfying the preselection requirements described in the text. The stacked histograms represent the expected contributions from various SM background processes and are derived from MC simulations scaled to an integrated luminosity of 32.9 fb−1 . Multijet processes are not included in the background due to the limited number of simulated events. The contributions from these processes are most substantial at small values of mμμ . The shaded bands represent the statistical uncertainties in the simulated background. The observed distributions for data are given by the points with error bars. D. Signal regions and signal efficiency Signal is characterized by vertices where both muon candidates are MSonly. This requirement unavoidably TABLE VI. Selection criteria for low- and high-mass regions, leads to a reduction in efficiency for decays close to the in addition to the preselection requirements described in the text. IP. Displaced-vertex analyses that make use of ID tracks The definitions of the low- and high-mass signal regions are also [22] effectively recover such signal events. Two orthogonal given. signal regions are used to increase the sensitivity to low- and high-mass signal models, SRlow and SRhigh , respec- Selection Low mass High mass tively. The two regions are summarized in Table VI. For pμT[GeV] > 10 > 20 both SRs, the muons are required to have opposite charge. mμμ [GeV] 15–60 > 60 The product of acceptance and reconstruction efficiency Dimuon transverse boost  >2 determined from simulated signal events is shown in Fig. 3 SRlow SRhigh as a function of generated Lvtx and leading muon d0 , for the Muon candidates Both MSonly Both MSonly GGM model and for the dark-sector model. The lower Muon candidate charge Opposite charge Opposite charge efficiency observed for small Lvtx or small jd0 j (more apparent in the ZD models) is due to the veto on MScomb 012001-8 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) 0.15 ATLAS Simulation m∼χ0 = 300 GeV ATLAS Simulation m∼χ0 = 300 GeV 1 1 0.15 s = 13 TeV m∼χ0 = 700 GeV s = 13 TeV m∼χ0 = 700 GeV 1 1 SRhigh mχ∼0 = 1000 GeV SRhigh mχ∼0 = 1000 GeV Vertex efficiency Vertex efficiency 1 1 0.1 0.1 0.05 0.05 0 0 0 100 200 300 400 500 600 0 50 100 150 200 250 Lvtx [cm] Leading muon d [cm] 0 (a) (b) ATLAS Simulation mZD= 20 GeV 0.1 ATLAS Simulation mZD= 20 GeV s = 13 TeV mZD= 40 GeV s = 13 TeV mZD= 40 GeV SRlow mZD= 60 GeV SRlow mZD= 60 GeV Vertex efficiency Vertex efficiency 0.1 0.05 0.05 0 0 0 100 200 300 400 500 600 0 50 100 150 200 250 Lvtx [cm] Leading muon d [cm] 0 (c) (d) FIG. 3. The efficiency for selecting a displaced dimuon vertex that satisfies the requirements of SRhigh and SRlow as function of (a) and (c) generated decay length Lvtx , and (b) and (d) generated transverse impact parameter d0 of the leading muon. These efficiencies are calculated relative to all generated signal vertices and include geometrical acceptance and reconstruction effects. The distributions in (a) and (b) are derived from signal events with a long-lived neutralino, χ̃ 01 , decaying to a Z boson (with Z → μþ μ− ) and a gravitino. The distributions in (c) and (d) are derived from signal events with a long-lived dark photon, ZD , that decays to μþ μ− . The shaded bands represent the statistical uncertainties in the efficiencies. muons, while the loss at large values reflects the lower MS parameters of the reconstructed MS tracks and the distri- reconstruction efficiency for tracks with trajectories that do butions are normalized to the expected yields in the signal not extrapolate back to a region close to the IP. The value regions. of Lvtx where maximum efficiency is achieved is different for each choice of ZD mass due to the large differences E. Control regions and background estimation in boost. Dimuon vertices are categorized as described in Table VII. The total event-level efficiencies, including trigger and The observed yields of same-charge dimuon vertices in all offline selection criteria, as functions of the lifetime of the LLP, are shown in Fig. 4 and maximum values are in the cτ four regions A, B, C, and D are used to estimate the region 20–50 cm. The reweighted samples, as described in background yields in the SRs due to muons produced more Sec. III, are used to estimate the efficiencies for values of than about a centimeter from the IP, referred to as nonprompt the lifetime which were not used in generating the muons. The observed yields in the opposite-charge B, C, and simulated samples. This event-level efficiency is defined D CRs are used to predict the background yield from SM as the fraction of generated events that are selected and processes that produce prompt muons (those produced have at least one dimuon DV. within about a centimeter of the IP) in the SRs (opposite- Distributions of mμμ and signed rvtx for signal vertices in charge dimuon vertices in region A). Muons from decays of simulated events, for both SRhigh and SRlow , are displayed hadrons containing b and c quarks are, within the context of in Fig. 5. The vertex properties are computed using the this analysis, considered to be prompt muons. 012001-9 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) ATLAS Simulation mχ∼0 = 300 GeV ATLAS Simulation mZD= 20 GeV 1 s = 13 TeV mχ∼0 = 700 GeV s = 13 TeV mZD= 40 GeV 1 0.1 SRhigh mχ∼0 = 1000 GeV 0.05 SRlow mZD= 60 GeV Total efficiency 1 Total efficiency 0.05 0 0 10−1 1 10 102 103 104 105 106 107 10−1 1 10 102 103 104 105 106 107 cτ [cm] cτ [cm] (a) (b) FIG. 4. Overall event-level efficiencies after the signal-region selections (combining trigger and offline selection), as a function of the lifetime of the long-lived BSM particle, for (a) the GGM model and (b) the dark-sector model. The shaded bands represent the statistical uncertainties only. m∼χ0 = 300 GeV, cτ = 1 m m∼χ0 = 300 GeV, cτ = 1 m 7 ATLAS Simulation 1 102 ATLAS Simulation 1 -1 mχ∼0 = 700 GeV, cτ = 1 m -1 mχ∼0 = 700 GeV, cτ = 1 m 6 s = 13 TeV 32.9 fb s = 13 TeV 32.9 fb 1 1 Vertices / 2 GeV Vertices / 10 cm 5 SRhigh mχ∼0 = 1000 GeV, cτ = 1 m 10 SRhigh mχ∼0 = 1000 GeV, cτ = 1 m 1 1 4 3 1 2 1 10−1 0 20 40 60 80 100 120 140 160 180 200 −400 −300 −200 −100 0 100 200 300 400 mμμ [GeV] Signed rvtx [cm] (a) (b) 1400 104 ATLAS Simulation mZ = 20 GeV, cτ = 0.5 m ATLAS Simulation mZ = 20 GeV, cτ = 0.5 m D D 1200 -1 -1 s = 13 TeV 32.9 fb mZ = 40 GeV, cτ = 0.5 m s = 13 TeV 32.9 fb mZ = 40 GeV, cτ = 0.5 m D 103 D Vertices / 2 GeV 1000 Vertices / 10 cm SRlow mZ = 60 GeV, cτ = 0.5 m SRlow mZ = 60 GeV, cτ = 0.5 m D D 800 2 10 600 400 10 200 1 0 20 30 40 50 60 70 80 −400 −300 −200 −100 0 100 200 300 400 mμμ [GeV] Signed rvtx [cm] (c) (d) FIG. 5. Distributions derived from MC simulations of (a) dimuon invariant mass mμμ and (b) vertex radius rvtx for signal vertices in SRhigh with a long-lived neutralino, χ̃ 01 (mχ̃ 01 ¼ 300, 700, and 1000 GeV and cτχ̃ 01 ¼ 100 cm) decaying to a Z boson (with Z → μþ μ− ) and a gravitino; (c) mμμ and (d) rvtx for signal vertices in SRlow with a long-lived dark photon, ZD (mZD ¼ 20, 40, and 60 GeV; and cτZD ¼ 50 cm), that decays to μþ μ− . The shaded bands represent the statistical uncertainties. The distributions are normalized to the expected yields in the signal regions for mg̃ ¼ 1100 GeV, σðpp → g̃ g̃Þ ¼ 0.1635 pb, Bðχ̃ 01 → ZG̃Þ ¼ 1.0, and BðZ → μþ μ− Þ ¼ 0.03366; and mH ¼ 125 GeV, mHD ¼ 300 GeV, σðpp → HÞ ¼ 44.1 pb, BðH → ZD ZD Þ ¼ 100%, and the value of BðZD → μþ μ− Þ varying between 0.1475 and 0.1066 for the range mZD ¼ 20–60 GeV. 012001-10 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) TABLE VII. Description of four regions used in estimating TABLE VIII. Observed number of SS vertices N SS , charge ratio background yields. The ordering of the muon candidates in the Rq;SR and predicted yields of nonprompt dimuon vertices description of the dimuon vertex is leading muon first, then N nonprompt SR in each signal region. The uncertainty in N nonprompt SR subleading muon. combines in quadrature the statistical uncertainty, derived from the observed number of SS vertices, and the uncertainty in the Region name Muon candidates in vertex charge ratio. The statistical uncertainty on N SS for the case where A MSonly-MSonly the central value is measured to be zero is taken to be the 68% B MSonly-MScomb one-sided Poisson confidence-level interval: þ1.14. C MScomb-MSonly D MScomb-MScomb Region N SS Rq;SR N nonprompt SR SRlow 11 1.24  0.24 13.6  4.9 þ1.4 SRhigh 0 1.24  0.24 0.0−0.0 F. Nonprompt muon vertices Nonprompt muons are those for which no matching ID track is expected. Examples of such sources of background depending on the region (A, B, C, or D). As no statistical nonprompt muons are cosmic-ray muons, BIB muons, fake difference in Rπ=K q is observed for the low- and high-mass MS tracks generated from random hit combinations, and regions, a single value is used for both regions. For those arising from pion or kaon decay. dimuon vertices composed of BIB or cosmic-ray muons, Cosmic-ray and BIB muons will usually not produce ID the muon charges are assumed to be entirely uncorrelated: tracks, as they rarely pass close enough to the IP to produce Rcos q =BIB ¼ 1.0. an ID track that satisfies the track reconstruction criteria, in Since the relative composition of the nonprompt dimuon particular the jd0 j < 1 cm requirement. As a result, they background is unknown, the average of Rπ=K q and Rcos q =BIB produce mostly MSonly muon candidates. As described in is assumed as the nominal value, Rq , with an uncertainty Sec. IV B, dimuon vertices reconstructed from a single cosmic-ray or BIB muon that generates two MS tracks are that is half the difference between the two values; this is shown in Table VIII (Rq ¼ 1.24  0.24 for the SRs). effectively eliminated in the preselection by taking advan- tage of the fact that the angle between the two tracks will be The numbers of OS nonprompt vertices in the regions A, nearly 180°. On the other hand, vertices formed when a B, C, and D are predicted using the number of SS vertices single MS track from a cosmic-ray or BIB muon is paired in each region and the appropriate Rq , as described above: with an unrelated muon candidate produced from the pp N nonprompt i ¼ Rq;i N SS i , where N i SS is the number of SS collision will satisfy these selection criteria and more vertices observed in region i (i ¼ A, B, C, or D) and readily contribute to the background. Rq;i is the charge ratio for region i. Pions and kaons have relatively large lifetimes and The predicted yields of nonprompt dimuon vertices for feature large branching fractions to final states with one both SRs are given in Table VIII, where the uncertainty in muon. Such decays often result in either no ID track being Rq is treated as a systematic uncertainty added in quad- reconstructed, due to the requirement of at least a minimum rature to the statistical uncertainties. number of ID hits, or the ID track of the pion/kaon failing to be matched to the muon MS track. In both of these two G. Prompt muon vertices cases, a MSonly muon candidate will be produced. The number of dimuon vertices in each of the SRs arising Vertices that contain one or more nonprompt muons are from prompt muon processes is estimated from the referred to as “nonprompt vertices." If the vertex contains a observed yields in the OS low-mass and high-mass B, C, cosmic-ray or BIB muon paired with an unrelated muon and D control regions. Sources of such background in candidate, the charges of the two MS tracks will be largely the SRs include SM processes that produce prompt muons uncorrelated. However, some charge correlation is expected that are reconstructed as MSonly due to detector or in vertices containing muons from pion/kaon decay, reconstruction effects, such as ID inefficiencies, or poorly because the pion/kaon is produced from the same pp reconstructed combined muons, collectively described as collision that produces the other muon in the vertex. For the failed combined muon reconstruction. latter, the charge correlation is studied by measuring the To avoid double-counting of dimuons from nonprompt ratio of OS to SS dimuon vertices, Rπ=K q , in the data. As processes, the estimated number of nonprompt OS vertices muons from pion/kaon decay are not expected to be in each region is subtracted: isolated from jets, the quantity Rπ=K q is measured in a sample of dimuon vertices where the selection criteria are N prompt i ¼ N OS nonprompt i − Ni ; i ¼ B; C; D; those of the preselection, except that the jet-muon overlap and isolation requirements are removed for both muons. where N OS i is the number of OS vertices in region i, nonprompt The value ranges from 1.39  0.09 to 1.55  0.03, Ni is the number of OS nonprompt vertices in region 012001-11 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) i (described in Sec. IV F) and N prompt i is the estimated and the transfer factors and predictions of N prompt in the SRs number of opposite-charge vertices from prompt processes are recomputed. For both the low-mass and high-mass in region i. The quantity N prompt (N prompt ) is the estimated selection, the sum over the predicted prompt background B C number of OS vertices from prompt processes with leading yields in each bin is consistent with the nominal value. (subleading) muons that fail the combined reconstruction and are identified as MSonly, while the other muon H. Total background candidate is identified as being MScomb. The quantity The predicted number of nonprompt muon vertices is N prompt D is the estimated number of OS vertices from prompt summed with the predicted number of prompt muon processes with muon candidates that pass the combined vertices from SM background processes to give the reconstruction and are both identified as being MScomb. predicted total number of background vertices in each of With these definitions, the leading and subleading “transfer the SRs: 13.8  4.9 and 0.50þ1.41 −0.07 for SRlow and SRhigh , factors” are defined as follows: respectively, where the uncertainties include the statistical components and the systematic uncertainty in Rq . f L ¼ N prompt B =N prompt D ; The reliability of the background estimation method is f S ¼ N prompt C =N prompt D : validated by applying it to both the sum of the simulated background samples and to a high-mass validation region The leading transfer factor multiplied by N prompt C , or, in the data. The predicted number of dimuon vertices in the alternatively, the subleading transfer factor multiplied by simulated sample agrees with the number of observed N prompt , thus gives for prompt muon processes the predicted vertices, to within the statistical precision, in both the low- B number of OS vertices in region A, the SRs in this case: and high-mass signal regions. As the simulated samples do not include multijet processes or cosmic muon back- N prompt ¼ f L · N prompt ¼ f S · N prompt : grounds, this is primarily a validation of the technique to A C B estimate the background from prompt dimuon vertices. The The yields in the various regions are summarized in validation region in data comprises dimuon vertices that Table IX. The vertices in all CRs are used to verify that the satisfy all of the selection criteria of the high-mass region, designation of one of the MS tracks in the vertex as with the exception that the requirement on the transverse MScomb or MSonly is independent of the designation of boost of the dimuon system is inverted: it is required to the other as MScomb or MSonly (the measured correlation have a value less than two, which ensures that there is is negligibly small, < 0.0015). The predicted number of negligible contribution from signal processes. The results vertices from prompt background processes in the low- and are given in Table X. These two studies validate the method high-mass SRs are 0.14  0.22 and 0.504  0.070, respec- within the statistical precision. tively, where the uncertainties are statistical only. As a cross-check, the B, C, and D control regions are V. SYSTEMATIC UNCERTAINTIES subdivided into bins of either muon pT or muon η and ϕ, The systematic uncertainties are described in detail below. They include those in the integrated luminosity, TABLE IX. The number of opposite-charge vertices, N OS , the used in converting signal yields to cross sections; the number of same-charge vertices, N SS , the estimated ratio of background estimate, derived entirely from the data; and opposite-charge to same-charge nonprompt dimuon vertices, Rq the signal efficiency, determined from MC simulations. All and the estimated number of prompt dimuon vertices N prompt in systematic uncertainties are treated as uncorrelated. each of the control regions B, C, and D. The values of N prompt are obtained by subtracting the product of N SS and Rq from N OS . The quoted uncertainties in N prompt include the statistical component and the systematic uncertainty in Rq . TABLE X. Predicted nonprompt N nonprompt VR , prompt N prompt VR , bkgd and total N VR background yields and number of observed Region N OS N SS Rq N prompt vertices N obs VR in data in the high-mass validation region. The Low-mass region uncertainty in N prompt VR includes the statistical component and the B 124 63 1.28  0.28 43  23 systematic uncertainty in Rq . C 451 335 1.20  0.20 49þ74 −49 D 19599 3220 1.20  0.20 15700  660 Yield High-mass validation region þ2.3 High-mass region N nonprompt VR 2.5−1.6 N prompt 7.20  0.25 B 120 0 1.28  0.28 120  11 VR þ2.3 C 92 0 1.20  0.20 92  10 N bkgd VR 9.7−1.6 D 21940 24 1.20  0.20 21900  150 N obs VR 13 012001-12 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) The uncertainty in the 2016 integrated luminosity is TABLE XI. Predicted nonprompt N nonprompt , prompt N prompt , 2.2%. It is derived, following a methodology similar to that and total N bkgd background yields and number of observed detailed in Ref. [94], and using the LUCID-2 detector for vertices N obs in data in SRlow and SRhigh . The uncertainties in the baseline luminosity measurements [95], from calibra- the predicted background yields are statistical uncertainties and tion of the luminosity scale using x-y beam-separation systematic uncertainties added in quadrature. scans. Yield SRlow SRhigh Sources of systematic uncertainties in the signal effi- N nonprompt 13.6  4.9 0.0þ1.4 −0.0 ciencies include possible mismodeling of the trigger and þ0.2 MS efficiencies and pileup effects in the MC simulation. N prompt 0.1−0.1 0.50  0.07 For the high-mass SR, the uncertainty associated with N bkgd 13.8  4.9 0.50þ1.42 −0.07 N obs 15 2 trigger and MS track reconstruction efficiency is deter- mined by comparing the observed yields in the data with MC simulation of Z þ jets events, using the selection criteria of the OS B, C, and D control regions and the VI. RESULTS additional requirement 70 < mμμ < 110 GeV. The differ- The predicted number of nonprompt muon vertices is ence between the yields in data and the simulated back- summed with the predicted number of prompt muon ground samples is used to assign a systematic uncertainty vertices from SM background processes to give the of 1% to the combined trigger and MS track-reconstruction predicted total number of background vertices, N bkgd , in efficiency. For the low-mass SR, the efficiency of the each SR. The predicted background yields, along with the trigger and MS track reconstruction is compared between number of observed vertices in the data, are summarized in MC simulation and data for J=ψ → μμ events, using a tag- Table XI. The distributions of mμμ and rvtx are shown in and-probe technique. The efficiency is measured as a Fig. 6 for the observed vertices in the two signal regions. function of the angular separation between the two muons, Each dimuon vertex is in a separate event, and therefore the and a maximum deviation of 6% is observed. This differ- number of events observed is equivalent to the number ence is taken as an uncertainty in the signal efficiency. The of vertices. The dimuon vertex with the highest mass agreement between data and MC simulation for the has mμμ ¼ 381 GeV, rvtx ¼ −220 cm, and zvtx ¼ 99 cm. reconstruction efficiency for MS tracks with large impact Close inspection of the event reveals characteristics of parameters was studied by comparing a cosmic-ray muon being cosmic in origin. The observation of one such simulation to cosmic-ray muon candidates in data [22]. dimuon vertex in SRhigh is consistent, within the uncer- Comparing the ratio of the muon candidate d0 distributions tainties, with the nonprompt background estimate of in the two samples yields a d0 -dependent efficiency N nonprompt ¼ 0.0þ1.4 −0.0 . The other vertex in SRhigh has a mass correction that is between 1% and 2.5%, with an average compatible with the decay of the SM Z. The dimuon vertex value of 1.5%. The systematic uncertainty on MS track with the largest value of rvtx is in SRlow and has reconstruction associated with this procedure is taken from mμμ ¼ 46 GeV, rvtx ¼ 223 cm, and zvtx ¼ 56 cm. The the statistical uncertainty, and is 2% per track in the vertex is formed by an MS track passing through the vertices. top of the detector combined with another MS track The systematic uncertainty from pileup effects is deter- passing through the bottom of the detector, with an angle mined by varying the pileup reweighting of simulated of nearly 180° between them. This vertex is likely a cosmic- signal events in a manner that spans the expected uncer- ray muon that narrowly survived the cosmic-ray veto tainty. This results in a systematic uncertainty of 0.2% in criteria described in Sec. IV C. the signal efficiency. As no significant excess of vertices over the SM back- The methods used to estimate the background are ground expectation is observed, 95% confidence-level entirely data-driven, with statistical uncertainties arising (C.L.) upper limits on the signal event yields and produc- from the numbers of events in the CRs. The nonprompt- tion cross sections are calculated for various values of the vertex background estimate for both signal regions has a proper decay distance cτ of the long-lived particle in each systematic uncertainty of 19% associated with knowledge of the two BSM scenarios considered.4 The limits are of the charge correlation Rq , as described in Sec. IV F. calculated using the CLS prescription [96] with a Poisson Systematic uncertainties in the estimate of the prompt likelihood used as the test statistic. Uncertainties in the background are determined by varying the quantity that signal efficiency and background expectation are included distinguishes MScomb from MSonly muons, the angular distance between the MS track and nearest combined-muon 4 track, by 50% and repeating the ABCD technique For events that are selected exclusively by the trimuon trigger the observed signal yield will have a quadratic dependence on described in Sec. IV G. A 9% difference in the prompt BðZD → μþ μ− Þ. The collimated-dimuon trigger efficiency domi- background estimate is observed, and this is taken as a nates over the trimuon trigger efficiency for the values of mZD systematic uncertainty. considered in this paper. 012001-13 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) 7 8 ATLAS ATLAS 6 7 s = 13 TeV 32.9 fb-1 s = 13 TeV 32.9 fb-1 data, SRlow 6 data, SRlow 5 Vertices / 5 GeV Vertices / 10 cm 5 4 data, SR data, SR high high 4 3 3 2 2 1 1 0 0 50 100 150 200 250 300 350 400 −300 −200 −100 0 100 200 300 mμμ [GeV] Signed rvtx [cm] (a) (b) FIG. 6. Distributions of (a) dimuon invariant mass mμμ and (b) vertex radius rvtx for displaced dimuon vertices in the low-mass (black circles) and high-mass (red squares) signal regions. 102 102 ATLAS ATLAS 95% CL upper limit σxB [pb] s = 13 TeV 32.9 fb-1 95% CL upper limit σxB [pb] s = 13 TeV 32.9 fb-1 10 10 mχ∼0 = 300 GeV mχ∼0 = 700 GeV 1 1 Observed Observed 1 Expected 1 Expected ±1σ ±1σ ±2 σ ±2 σ 10−1 B (∼ ~ χ0 → Z G) = 1 10−1 B (∼ ~ χ0 → Z G) = 1 1 1 σg~(1100 GeV) = 0.163 pb σg~(1100 GeV) = 0.163 pb 10−2 10−2 10−3 10−3 10−4 −1 10−4 −1 10 1 10 102 103 104 105 106 107 10 1 10 102 103 104 105 106 107 cτ [cm] cτ [cm] (a) (b) 102 ATLAS 95% CL upper limit σxB [pb] 10 s = 13 TeV 32.9 fb-1 mχ∼0 = 1000 GeV 1 Observed 1 Expected ±1σ ±2 σ 10−1 B (∼ ~ χ0 → Z G) = 1 1 σg~(1100 GeV) = 0.163 pb −2 10 10−3 10−4 −1 10 1 10 102 103 104 105 106 107 cτ [cm] (c) FIG. 7. The observed and expected 95% C.L. upper limits on the product of cross section and branching ratios for pair production of gluinos, leading to a final state of μþ μ− þ X, in the GGM model, as a function of the χ̃ 01 lifetime, for mg̃ ¼ 1100 GeV and three different choices of mχ̃ 01 : (a) 300 GeV, (b) 700 GeV, and (c) 1000 GeV. The shaded green (yellow) bands represent the 1σ (2σ) uncertainties in the expected limits. The dashed horizontal line represents the value of the cross section times branching fractions predicted from simulation, with mg̃ ¼ 1100 GeV, σðpp → g̃ g̃Þ ¼ 0.1635 pb, Bðχ̃ 01 → ZG̃Þ ¼ 1.0, and BðZ → μþ μ− Þ ¼ 0.03366. 012001-14 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) 103 103 ATLAS ATLAS 95% CL upper limit σxB [pb] 95% CL upper limit σxB [pb] 10 2 s = 13 TeV 32.9 fb-1 10 2 s = 13 TeV 32.9 fb-1 mZD = 20 GeV mZD = 40 GeV Observed Observed 10 Expected 10 Expected ±1σ ±1σ ±2 σ B (Z → μ μ) = 0.148 ±2 σ B (Z → μ μ) = 0.137 D D 1 B (H → ZD ZD) = 0.1 1 B (H → ZD ZD) = 0.1 10−1 B (H → ZD ZD) = 0.01 10−1 B (H → ZD ZD) = 0.01 10−2 10−2 10−3 10−3 −1 10 1 10 10 2 10 10 3 4 10 5 10 6 107 10−1 1 10 102 103 104 105 106 107 cτ [cm] cτ [cm] (a) (b) 3 10 ATLAS 95% CL upper limit σxB [pb] 102 s = 13 TeV 32.9 fb-1 mZD = 60 GeV Observed 10 Expected ±1σ ±2 σ B (Z → μ μ) = 0.107 D 1 B (H → ZD ZD) = 0.1 10−1 B (H → ZD ZD) = 0.01 10−2 10−3 10−1 1 10 102 103 104 105 106 107 cτ [cm] (c) FIG. 8. The observed and expected 95% C.L. upper limits on the product of cross section and branching ratios, σ × B ¼ σðpp → HÞ × BðH → ZD ZD Þ × BðZD → μþ μ− Þ, in the dark-sector model, as a function of the ZD lifetime, for three different choices of mZD : (a) 20 GeV, (b) 40 GeV, and (c) 60 GeV. The shaded green (yellow) bands represent the 1σ (2σ) uncertainties in the expected limits. The dashed horizontal lines represent the values of the cross section times branching fractions predicted by simulation, with mH ¼ 125 GeV, mHD ¼ 300 GeV, σðpp → HÞ ¼ 44.1 pb and assuming BðH → ZD ZD Þ ¼ 10% or 1%. The value of BðZD → μþ μ− Þ varies between 0.1475 and 0.1066 for the range mZD ¼ 20–60 GeV. 10−4 ATLAS as nuisance parameters, and the CLS values are calculated by generating ensembles of pseudoexperiments corre- 10−5 Excluded at 95% CL, B (H→ ZDZD) = 10% s = 13 TeV sponding to the background-only and signal-plus-back- 32.9 fb-1 Excluded at 95% CL, B (H→ ZDZD) = 1% ground hypotheses. Both the expected and observed limits 10−6 are shown in Fig. 7 for the GGM model, and in Fig. 8 for the dark-sector model, where SRhigh is used for the GGM 10−7 model and SRlow is used for the dark-sector model. In the GGM model with a gluino mass of 1100 GeV and χ̃ 01 10−8 masses of 300, 700, and 1000 GeV, cτχ̃ 01 values are 10−9 excluded in the ranges 3.1–1000 cm, 2.6–1500 cm, and 2.9–1800 cm, respectively. The observed limits are about 10−10 1.5σ weaker than the expected limits because of the small 20 25 30 35 40 45 50 55 60 excess of events observed in SRhigh . In the dark-sector mZ [GeV] D model with a dark-Higgs-boson mass of 300 GeV, BðH → ZD ZD Þ ¼ 10% and ZD masses of 20, 40, and FIG. 9. The observed 95% C.L. excluded regions in the plane of 60 GeV, cτZD values are excluded in the ranges 0.3– ZD -Z kinetic mixing parameter, ϵ, versus ZD mass, for values of BðH → ZD ZD Þ ¼ 1% or 10%, and mHD ¼ 300 GeV. The value 2000 cm, 0.9–2400 cm, and 2.1–1100 cm, respectively. of BðZD → μþ μ− Þ varies between 0.1475 and 0.1066 for the These limits are translated into 95% exclusion contours in range mZD ¼ 20–60 GeV. the plane of the ZD -Z kinetic mixing parameter, ϵ, and the 012001-15 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) ZD mass, and are shown in Fig. 9. Values of ϵ of the order Colombia; MSMT CR, MPO CR and VSC CR, Czech 10−8 are excluded for 20 < mZD < 60 GeV. Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, VII. CONCLUSION and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; This article reports on a search for BSM long-lived INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; particles decaying into two muons of opposite-sign electric NWO, Netherlands; RCN, Norway; MNiSW and NCN, charge in a sample of pp collisions recorded by the ATLASpffiffiffi Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia detector at the LHC with a center-of-mass energy of s ¼ and NRC KI, Russian Federation; JINR; MESTD, Serbia; 13 TeV and an integrated luminosity of 32.9 fb−1 . The MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, search is performed by identifying dimuon vertices with South Africa; MINECO, Spain; SRC and Wallenberg displacements from the pp interaction point in the range of Foundation, Sweden; SERI, SNSF and Cantons of Bern 1–400 cm and having invariant mass mμμ within one of two and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; signal regions: 20–60 GeV or > 60 GeV. In neither signal STFC, United Kingdom; DOE and NSF, United States of region is a significant excess observed in the number of America. In addition, individual groups and members have vertices relative to the predicted background. Hence upper received support from BCKDF, the Canada Council, limits at 95% confidence level on the product of cross CANARIE, CRC, Compute Canada, FQRNT, and the section and branching fraction are calculated, as a function Ontario Innovation Trust, Canada; EPLANET, ERC, of lifetime, for production of long-lived particles in either a ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie dark-sector model with dark-photon masses in the range Actions, European Union; Investissements d’Avenir Labex 20–60 GeV, produced from decays of the Higgs boson, or and Idex, ANR, Région Auvergne and Fondation Partager le in a general gauge-mediated supersymmetric model with a Savoir, France; DFG and AvH Foundation, Germany; gluino mass of 1100 GeV and neutralino masses in the Herakleitos, Thales and Aristeia programmes co-financed range 300–1000 GeV. For the models considered, the lower by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, and upper lifetime limits are set from 1 to 2400 cm in cτ, Israel; BRF, Norway; CERCA Programme Generalitat de respectively, depending on the targeted model’s parameters. Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. The crucial com- ACKNOWLEDGMENTS puting support from all WLCG partners is acknowledged We thank CERN for the very successful operation of the gratefully, in particular from CERN, the ATLAS Tier-1 LHC, as well as the support staff from our institutions facilities at TRIUMF (Canada), NDGF (Denmark, Norway, without whom ATLAS could not be operated efficiently. 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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,129 I. Nomidis,132 M. A. Nomura,29 T. Nooney,90 M. Nordberg,35 N. Norjoharuddeen,131 T. Novak,89 O. Novgorodova,46 R. Novotny,138 M. Nozaki,79 L. Nozka,126 K. Ntekas,168 E. Nurse,92 F. Nuti,102 F. G. Oakham,33,e H. Oberlack,113 T. Obermann,24 J. Ocariz,132 A. Ochi,80 I. Ochoa,38 J. P. Ochoa-Ricoux,144a K. O’Connor,26 S. Oda,85 S. Odaka,79 A. Oh,98 S. H. Oh,47 C. C. Ohm,151 H. Oide,53b,53a H. Okawa,166 Y. Okazaki,83 Y. Okumura,160 T. Okuyama,79 A. Olariu,27b L. F. Oleiro Seabra,136a 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,136a,136e K. Onogi,115 P. U. E. Onyisi,11 H. Oppen,130 M. J. Oreglia,36 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. 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Wengler,35 S. Wenig,35 N. Wermes,24 M. D. Werner,76 P. Werner,35 M. Wessels,59a T. D. Weston,20 K. Whalen,127 N. L. Whallon,145 A. M. Wharton,87 A. S. White,103 A. White,8 M. J. White,1 R. White,144b D. Whiteson,168 B. W. Whitmore,87 F. J. Wickens,141 W. Wiedenmann,178 M. Wielers,141 C. Wiglesworth,39 L. A. M. Wiik-Fuchs,50 A. Wildauer,113 F. Wilk,98 H. G. Wilkens,35 L. J. Wilkins,91 H. H. Williams,133 S. Williams,31 C. Willis,104 S. Willocq,100 J. A. Wilson,21 I. Wingerter-Seez,5 E. Winkels,153 F. Winklmeier,127 O. J. Winston,153 B. T. Winter,24 M. Wittgen,150 M. Wobisch,93 A. Wolf,97 T. M. H. Wolf,118 R. Wolff,99 M. W. Wolter,82 H. Wolters,136a,136c V. W. S. Wong,172 N. L. Woods,143 S. D. Worm,21 B. K. Wosiek,82 K. W. Woźniak,82 K. Wraight,55 M. Wu,36 S. L. Wu,178 X. Wu,52 Y. Wu,58a T. R. Wyatt,98 B. M. Wynne,48 S. Xella,39 Z. Xi,103 L. Xia,175 D. Xu,15a H. Xu,58a L. Xu,29 T. Xu,142 W. Xu,103 B. Yabsley,154 S. Yacoob,32a K. Yajima,129 D. P. Yallup,92 D. Yamaguchi,162 Y. Yamaguchi,162 A. Yamamoto,79 T. Yamanaka,160 F. Yamane,80 M. Yamatani,160 T. Yamazaki,160 Y. Yamazaki,80 Z. Yan,25 H. J. Yang,58c,58d H. T. Yang,18 S. Yang,75 Y. Yang,160 Z. Yang,17 W-M. Yao,18 Y. C. Yap,44 Y. Yasu,79 E. Yatsenko,58c,58d J. Ye,41 S. Ye,29 I. Yeletskikh,77 E. Yigitbasi,25 E. Yildirim,97 K. Yorita,176 K. Yoshihara,133 C. J. S. Young,35 C. Young,150 J. Yu,8 J. Yu,76 X. Yue,59a S. P. Y. Yuen,24 I. Yusuff,31,ww B. Zabinski,82 G. Zacharis,10 E. Zaffaroni,52 R. Zaidan,14 A. M. Zaitsev,140,ll N. Zakharchuk,44 J. Zalieckas,17 S. Zambito,57 D. Zanzi,35 D. R. Zaripovas,55 S. V. Zeißner,45 C. Zeitnitz,179 G. Zemaityte,131 J. C. Zeng,170 Q. Zeng,150 O. Zenin,140 T. Ženiš,28a D. Zerwas,128 M. Zgubič,131 D. F. Zhang,58b D. Zhang,103 F. Zhang,178 G. Zhang,58a,vv H. Zhang,15c J. Zhang,6 L. Zhang,50 L. Zhang,58a M. Zhang,170 P. Zhang,15c R. Zhang,58a,q R. Zhang,24 X. Zhang,58b Y. Zhang,15d Z. Zhang,128 P. Zhao,47 X. Zhao,41 Y. Zhao,58b,128,y Z. Zhao,58a A. Zhemchugov,77 B. Zhou,103 C. 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Zwalinski35 (ATLAS Collaboration) 1 Department of Physics, University of Adelaide, Adelaide, Australia 2 Physics Department, SUNY Albany, Albany, New York, USA 3 Department of Physics, University of Alberta, Edmonton, Alberta, Canada 4a Department of Physics, Ankara University, Ankara, Turkey 4b Istanbul Aydin University, Istanbul, Turkey 4c Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5 LAPP, Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS/IN2P3, Annecy, France 6 High Energy Physics Division, Argonne National Laboratory, Argonne, Illinois, USA 7 Department of Physics, University of Arizona, Tucson, Arizona, USA 8 Department of Physics, University of Texas at Arlington, Arlington, Texas, USA 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, University of Texas at Austin, Austin, Texas, USA 12a Bahcesehir University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 12b Istanbul Bilgi University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey 12c Department of Physics, Bogazici University, Istanbul, Turkey 12d Department of Physics Engineering, Gaziantep University, Gaziantep, Turkey 13 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan 14 Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, Barcelona, Spain 15a Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China 15b Physics Department, Tsinghua University, Beijing, China 15c Department of Physics, Nanjing University, Nanjing, China 15d University of Chinese Academy of Science (UCAS), Beijing, China 16 Institute of Physics, University of Belgrade, Belgrade, Serbia 17 Department for Physics and Technology, University of Bergen, Bergen, Norway 18 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley, California, USA 19 Institut für Physik, Humboldt Universität zu Berlin, Berlin, Germany 20 Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, University of Bern, Bern, Switzerland 012001-27 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) 21 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 22 Centro de Investigaciónes, Universidad Antonio Nariño, Bogota, Colombia 23a Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy 23b INFN Sezione di Bologna, Italy 24 Physikalisches Institut, Universität Bonn, Bonn, Germany 25 Department of Physics, Boston University, Boston, Massachusetts, USA 26 Department of Physics, Brandeis University, Waltham, Massachusetts, USA 27a Transilvania University of Brasov, Brasov, Romania 27b Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania 27c Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania 27d National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj-Napoca, Romania 27e University Politehnica Bucharest, Bucharest, Romania 27f West University in Timisoara, Timisoara, Romania 28a Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovak Republic 28b Department of Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 29 Physics Department, Brookhaven National Laboratory, Upton, New York, USA 30 Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina 31 Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom 32a Department of Physics, University of Cape Town, Cape Town, South Africa 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, Ontario, 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 012001-28 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) 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 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 012001-29 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) 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, Louisiana, 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, Quebec, 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, Quebec, 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 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, SB RAS, Novosibirsk, Russia 120b Novosibirsk State University Novosibirsk, Russia 121 Department of Physics, New York University, New York, New York, USA 122 The Ohio State University, Columbus, Ohio, USA 123 Faculty of Science, Okayama University, Okayama, Japan 124 Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, Oklahoma, USA 125 Department of Physics, Oklahoma State University, Stillwater, Oklahoma, USA 126 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 127 Center for High Energy Physics, University of Oregon, Eugene, Oregon, USA 128 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 129 Graduate School of Science, Osaka University, Osaka, Japan 130 Department of Physics, University of Oslo, Oslo, Norway 131 Department of Physics, Oxford University, Oxford, United Kingdom 132 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 133 Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania, USA 134 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 135 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA 136a Laboratório de Instrumentação e Física Experimental de Partículas - LIP, Portugal 136b Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal 136c Departamento de Física, Universidade de Coimbra, Coimbra, Portugal 136d Centro de Física Nuclear da Universidade de Lisboa, Lisboa, Portugal 136e Departamento de Física, Universidade do Minho, Braga, Portugal 136f Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain 136g Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 137 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 012001-30 SEARCH FOR LONG-LIVED PARTICLES IN FINAL … PHYS. REV. D 99, 012001 (2019) 138 Czech Technical University in Prague, Prague, Czech Republic 139 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 140 State Research Center Institute for High Energy Physics, NRC KI, Protvino, Russia 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, British Columbia, 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 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, Ontario, Canada 165a TRIUMF, Vancouver, British Columbia, Canada 165b Department of Physics and Astronomy, York University, Toronto, Ontario, 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, British Columbia, Canada 173 Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia, 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, Department of Physics, Istanbul, Turkey. d Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan. e Also at TRIUMF, Vancouver, British Columbia, Canada. f Also at Department of Physics and Astronomy, University of Louisville, Louisville, Kentucky, USA. g Also at Department of Physics, California State University, Fresno, Stanford, California, USA. h Also at Department of Physics, University of Fribourg, Fribourg, Switzerland. 012001-31 M. AABOUD et al. PHYS. REV. D 99, 012001 (2019) i Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany. 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 Universita di Napoli Parthenope, Napoli, Italy. n Also at Institute of Particle Physics (IPP), Canada. o Also at Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy. p Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania. q Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France. r Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia. s Also at Borough of Manhattan Community College, City University of New York, New York, USA. t Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece. u Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa. v Also at Louisiana Tech University, Ruston, Louisiana, USA. w Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain. x Also at Department of Physics, University of Michigan, Ann Arbor, Michigan, USA. y Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France. z Also at Graduate School of Science, Osaka University, Osaka, Japan. aa Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. bb Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands. cc Also at Near East University, Nicosia, North Cyprus, Mersin, Turkey. dd Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia. ee Also at CERN, Geneva, Switzerland. ff Also at Department of Physics, Stanford University, USA. gg Also at Manhattan College, New York, New York, USA. hh Also at Hellenic Open University, Patras, Greece. ii Also at The City College of New York, New York, New York, USA. jj Also at Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain. kk Also at Department of Physics, California State University, Sacramento, Stanford, California, USA. ll Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. mm Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland. nn Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom. oo Also at School of Physics, Sun Yat-sen University, Guangzhou, China. pp Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates. qq Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany. rr Also at National Research Nuclear University MEPhI, Moscow, Russia. ss Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary. tt Also at Giresun University, Faculty of Engineering, Giresun, Turkey. uu Also at Department of Physics, Nanjing University, Nanjing, China. vv Also at Institute of Physics, Academia Sinica, Taipei, Taiwan. ww Also at Department of Physics, University of Malaya, Kuala Lumpur, Malaysia. 012001-32