PHYSICAL REVIEW D 99, 092007 (2019) Search for heavy charged long-lived particles in the pATLAS ffiffi detector in 36.1 fb − 1 of proton-proton collision data at s = 13 TeV M. Aaboud et al.* (ATLAS Collaboration) (Received 6 February 2019; published 28 May 2019) A search for heavy charged long-lived particles is performed using a data sample of 36.1 fb−1 of proton- pffiffiffi proton collisions at s ¼ 13 TeV collected by the ATLAS experiment at the Large Hadron Collider. The search is based on observables related to ionization energy loss and time of flight, which are sensitive to the velocity of heavy charged particles traveling significantly slower than the speed of light. Multiple search strategies for a wide range of lifetimes, corresponding to path lengths of a few meters, are defined as model independently as possible, by referencing several representative physics cases that yield long-lived particles within supersymmetric models, such as gluinos/squarks (R-hadrons), charginos and staus. No significant deviations from the expected Standard Model background are observed. Upper limits at 95% confidence level are provided on the production cross sections of long-lived R-hadrons as well as directly pair- produced staus and charginos. These results translate into lower limits on the masses of long-lived gluino, sbottom and stop R-hadrons, as well as staus and charginos of 2000, 1250, 1340, 430, and 1090 GeV, respectively. DOI: 10.1103/PhysRevD.99.092007 I. INTRODUCTION (SUSY) [5–10], which either violate [11–13] or conserve [4,14–19] R-parity, allow for the existence of charged The search for heavy charged long-lived particles pre- −1 long-lived sleptons (l̃), squarks (q̃), gluinos (g̃) and pffiffiffi sample of 36.1 fb sented in this paper is based on a data charginos ( χ̃  of proton-proton (pp) collisions at s ¼ 13 TeV collected 1 ). in 2015 and 2016. It utilizes observables related to large Colored LLPs (e.g., q̃ and g̃) would hadronize forming ionization energy loss (dE=dx) and time of flight (ToF), so-called R-hadrons [14], which are bound states composed which are signatures of heavy charged particles traveling of the LLP and light SM quarks or gluons, and may emerge significantly slower than the speed of light. The mass of from the collision as charged or neutral states. Through the particles is estimated using the dE=dx (mdE=dx ) or ToF hadronic interactions of the light-quark constituents with (mToF ) measurements together with the reconstructed the detector material, especially inside the calorimeters, momentum. The background is estimated in a purely R-hadrons can change to states with a different electric data-driven manner, and multiple signal regions are defined charge. Thus they might not be reconstructed as a con- to address the different possible signatures of heavy long- sistently charged track in the inner tracking detector (ID) lived particles (LLPs) that reach at least the ATLAS and in the muon spectrometer (MS), even if the lifetime is hadronic calorimeter, which corresponds to decay lengths long enough to traverse the entire detector. Searches for R- of a few meters. Previous searches for LLPs that are stable hadrons are performed following two different approaches: within the detector were performed by the CMS using all available detector information (“full-detector R- Collaboration using 2.5 fb−1 of data at 13 TeV [1], as hadron search”), or disregarding all information from the well as by the ATLAS Collaboration using 3.2 fb−1 of data muon spectrometer (“MS-agnostic R-hadron search”) to at 13 TeV [2] and 19.8 fb−1 of data at 8 TeV [3]. minimize the dependence on the modeling of R-hadron LLPs are predicted in a variety of theories that extend the interactions with the material of the detector. Long-lived Standard Model (SM) [4]. Theories with supersymmetry gluinos are motivated for example by split-SUSY models [18,19], in which high-mass squarks can lead to very long * Full author list given at the end of the article. gluino lifetimes. Long-lived squarks, in particular a light top squark (stop) as the next-to-lighest SUSY particle, is Published by the American Physical Society under the terms of motivated for example by electroweak baryogenesis the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to [20,21], where nonuniversal squark mass terms can lead the author(s) and the published article’s title, journal citation, to a small mass difference between the stop and the and DOI. Funded by SCOAP3. neutralino as the lightest supersymmetric particle (LSP), 2470-0010=2019=99(9)=092007(34) 092007-1 © 2019 CERN, for the ATLAS Collaboration M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) and the lightest chargino is heavy, leading to suppressed with each event. Several components are used to determine radiative decays and long stop lifetimes. either dE=dx or ToF in this search and are discussed in If the charged LLP does not interact hadronically, it would more detail below. predominantly lose energy via ionization as it passes through The innermost component of the ATLAS detector is the the ATLAS detector. Searches for long-lived charginos and pixel detector, consisting of four radial layers of pixel- sleptons (focusing on staus, as they are expected in most sensors in the barrel region and three disks on each side in models to be the lightest) identified in both the ID and MS the end cap region. The pixel detector measures the are therefore performed. The searches for staus are motivated ionization energy loss of charged particles traversing it by gauge-mediated SUSY breaking (GMSB) [15,22–27] via a time-over-threshold (ToT) technique [31]. assuming the LSP to be a gravitino and with the light stau (τ̃) The ATLAS calorimeter in the central detector region as an LLP, decaying to a τ-lepton and a gravitino with an consists of a liquid-argon electromagnetic calorimeter unconstrained lifetime. While essentially all events in the followed by a steel-absorber scintillator-tile sampling GMSB models that include long-lived staus involve cascade calorimeter. The latter serves as hadronic calorimeter decays that end in two LLPs, in this paper direct di-stau covering the region up to jηj ¼ 1.7. In the ϕ-direction production through a Drell-Yan process is taken as a the tile calorimeter is segmented into 64 wedges with a benchmark. Results for pair-produced charginos are moti- size of Δϕ ¼ 2π=64 ≈ 0.1. In the r-z plane it is formed by vated by a minimal anomaly-mediated supersymmetry three radial layers in the central barrel region and three in breaking (mAMSB) model, where often the supersymmetric an extended barrel on each side, where each layer is partners of the SM W-boson fields, the wino fermions, are further segmented into cells. The cells in the first and the lightest gaugino states. In this particular case, the lightest third layer in the barrel and in all layers in the extended of the charged mass eigenstates, a chargino, and the lightest barrel have a rectangular shape, while in the second layer of the neutral mass eigenstates, a neutralino, are both almost of the barrel they are composed of two shifted rectangles pure wino and nearly mass-degenerate, resulting in long- (see Fig. 1). Overall, the tile calorimeter consists of 73 lived charginos (see Refs. [28,29] for details). cells in 64 ϕ-segments resulting in 4672 individual cells. This paper is organized as follows. A brief description of The optimal filtering algorithm (OFA) [32] used for the the ATLAS detector is given in Sec. II with emphasis on the readout provides, besides a precise measurement of the parts relevant for this analysis, followed by details of the energy deposits of particles and jets, a timing measure- calibration of key observables in Sec. III. The dataset and ment. The resolution of the single-cell timing in the tile simulated event samples and the subsequent event selection calorimeter is 1.3–1.7 ns. are described in Secs. IV and V, respectively. Section VI The outermost part of the ATLAS detector is the MS. explains the method of background estimation and compares Immersed in toroidal magnetic fields, the MS provides these estimates with data. Section VII details the origin and particle tracking and momentum reconstruction for charged estimation of systematic uncertainties. The results including particles with jηj < 2.7, as well as triggering information in upper cross-section limits are shown in Sec. VIII, and finally the range jηj < 2.4. Three layers of muon detectors are the conclusions are summarized in Sec. IX. arranged in concentric shells at distances between 5 and 10 m from the interaction point (IP) in the barrel region, and II. ATLAS DETECTOR in wheels perpendicular to the beam axis at distances The ATLAS detector [30] is a multipurpose particle between 7.4 and 21.5 m in the end cap regions where detector consisting of the ID immersed in a 2 T solenoidal jηj > 1.05. Four different detector technologies are used in magnetic field, electromagnetic as well as hadronic calo- the MS. In the barrel region the muon trigger relies on rimeters and a MS based on three large air-core toroid resistive-plate chambers (RPCs), while thin-gap chambers superconducting magnets with eight coils each. The ID are employed in the end cap wheels. High-precision comprises a silicon pixel detector, a silicon microstrip tracking for the momentum measurements is performed detector (SCT) and a transition-radiation tracker. With by monitored drift tubes (MDTs), except for the innermost almost 4π coverage in solid angle,1 the ATLAS detector layer in the forward region of 2.0 < jηj < 2.7, where is sensitive to the missing transverse momentum associated cathode-strip chambers are installed. A muon traversing the detector in the barrel region typically has around 20 hits 1 ATLAS uses a right-handed coordinate system with its origin in the MDTs and 14 hits in the RPCs. Both systems exhibit at the nominal interaction point (IP) in the center of the detector a sufficiently precise single-hit timing resolution (MDTs and the z axis coinciding with the axis of the beam pipe. 3.2 ns, RPCs 1.8 ns) to distinguish relativistic muons The x axis points from the IP to the center of the LHC ring, traveling at almost the speed of light from slowly propa- and the y axis points upward. Cylindrical coordinates (r, ϕ) are gating stable massive particles. For the reconstruction of used in the transverse plane, ϕ being the azimuthal angle around the beam pipe. The pseudorapidity is defined in terms of the polar slow particles traversing the full detector, a dedicated angle θ as η ¼ − ln tanðθ=2Þ. Object ffidistances in the η–ϕ plane pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi tracking algorithm that treats the velocity β as a free are given by ΔR ¼ ðΔηÞ2 þ ðΔϕÞ2. parameter is used [33,34]. 092007-2 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) The ATLAS trigger system [35] consists of a hardware- which accounts for small remaining η-dependences of the based level-1 trigger followed by a software-based high- timing for the outer parts of the cells in data, and ensures level trigger, which runs reconstruction and calibration an η-independent timing measurement in simulation. software similar to the offline reconstruction, and reduces Furthermore, a calibration of the timing as a function of the event rate to about 1 kHz. the energy deposit per ϕ-projected cell (averaging cells of identical geometry over ϕ) is applied, which does not III. CALIBRATION OF MAIN OBSERVABLES exceed 0.2 ns. Additionally, calibration constants in data are estimated for each cell followed by a run-by-run To achieve optimal identification performance for heavy, correction of the overall timing. These calibrations account charged, LLPs, measurements of the specific ionization for differences between single-tile calorimeter cells and for energy loss and ToF have to be calibrated. misalignments of the ATLAS and LHC clocks. The cell- The pixel detector provides measurements of specific wise calibration factors are mostly well below 1 ns, while ionization energy losses. The dE=dx is corrected for η- for some cells they range up to 2 ns. The run-by-run dependence and on a run-by-run basis, to reduce the effect correction constants are between −0.6 and 0.2 ns. of the degradation of charge collection in the silicon sensor A smearing of the timing obtained in simulation is applied due to accumulated irradiation. Individual measurements to achieve the same resolution as observed in data. The resulting from a particle traversing the detector are com- width of a Gaussian parametrization of the t0 distribution bined in a truncated mean to reduce the effects of the serves as the uncertainty. The uncertainties are estimated as Landau tails on the estimate of the most probable value a function of the energy deposit per ϕ-projected cell. (MPV). Finally, a value of the βγ of the particle is estimated Finally, the uncertainties are adjusted to achieve a unit from the MPV and the momentum, using a three-parameter Gaussian width for the pull distribution, which gives a empirical function, calibrated using protons, kaons and correction of 1% to the uncertainty. The individual mea- pions with low transverse momentum (pT ). The expected resolution for βγ from the dE=dx and momentum meas- surements of βHIT TILE , with the ϕ-projected resolutions shown urement is about 14%, which is taken as the uncertainty in Fig. 1, are combined in a weighted average βTILE using in the measured values. A detailed description of the βγ the inverse squared uncertainties as weights. The final estimation using the pixel detector can be found resolution achieved for βTILE is σ βTILE ¼ 0.068.2 in Ref. [31]. For the MDTs and RPCs, each of the 323799 drift tubes The particle velocity, β, is determined via ToF measure- and 362262 RPC readout strips is calibrated individually by ments in the tile calorimeter, the MDTs and the RPCs. performing a Gaussian parametrization of the timing To ensure an optimal β resolution, a series of custom information, and correcting for the offset to the expected calibrations is performed. High-pT muons are used for the value for a particle traveling at the speed of light. The width calibration as, given the timing resolutions, they travel of the fitted distribution is taken as the uncertainty for the effectively at the speed of light. measurements in the respective tube/strip. The uncertainties For the tile calorimeter, only cells with a minimum are, in a manner similar to the tile calorimeter, adjusted to energy deposit of 500 MeV are used. The time difference give a unit Gaussian width for the pull distributions. The (t0 ) relative to a particle traveling at the speed of light from corrections to the uncertainties are 16% for the MDTs, less the IP to the cell center (cell distance) is not allowed to be than 1% for the RPC η-strips and 2% for the ϕ-strips. The larger than 25 ns to reduce the effect of out-of-time pileup. squared inverse of the uncertainty is used as a weight for As the first calibration step, a bias introduced by the OFA is the calculation of a weighted-average β. Time-dependent corrected. The signal simulation reproduces the OFA bias phase-shift variations between the ATLAS and LHC clocks reliably. The correction is very small for an in-time signal, are addressed similarly to the tile calorimeter in a separate while for late-arriving particles it ranges up to 10 ns. This is correction of timing information for each LHC run, and followed by a correction for the particle path in the cell. separately for MDTs, RPC readout strips measuring η and An effective spatial position corresponding to the timing RPC strips measuring ϕ. The calibration results in a β measurement is estimated using an extrapolation of the resolution of σ βMDT ¼ 0.026 for the MDTs and σ βRPC ¼ particle track from the production vertex to the respective 0.022 for the RPCs (with single-hit t0 resolutions of about cell in the tile calorimeter (effective distance). The differ- 3.2 and 1.8 ns, respectively). ence between the effective distance and the cell distance is Finally, the ToF-based β measurements in the different used as a correction for the timing calibrations, while the subsystems are combined into an overall βToF , which is effective distance is used for the estimation of the individ- estimated as a weighted average of the β measurements ual measurements of the velocity (βHIT TILE ). The correspond- from the different subsystems using the inverse squared ing correction is largest (3 ns) for the edge η regions of the uncertainties as weights. Furthermore, the combined largest cells in the tile calorimeter, which are located in the outermost layer of the extended barrel. This is followed by 2 The resolutions (σ x ) are determined by performing a Gaussian separate η-dependent corrections for data and simulation, fit to the core of the respective distributions. 092007-3 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) -1.3 -1.2 2 -1.1 -1.0 .0 -0.9 -0.8 -0.7 -0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 6 0.7 0.8 0.9 1.0 1.1 1. 1.2 1.3 -1.4 -1.5 1.4 -1.6 1.5 -1.7 7 1.6 1 η 1.7 1. ATLAS s = 13 TeV, 36.1 fb-1 0.0 0.05 0.1 0.15 0.2 0.25 σβ d [m] 6.0 5.0 4.0 3.0 2.0 1.0 FIG. 1. Resolution (σ β ) of the βHIT TILE measurement for the different tile-calorimeter cells, which are shown with their actual shape. The gray circles indicate, the distance, d, from the interaction point and the gray straight lines the direction in η. uncertainty and the probability of compatibility between produce final states containing R-hadrons. The other SUSY the measurements from the different subsystems are calcu- particle masses, except that of the lightest neutralino, were lated for each candidate. The final distributions of the β set to very high values to ensure negligible effects on gluino measurements are shown in Fig. 2 for muons from Z → μμ or squark pair-production. The fraction of gluino-balls, i.e., selected events in data and simulation. The final resolution bound states of a gluino and gluon, was conservatively set achieved for βToF is σ βToF ¼ 0.021. to 10% [4,39], in order to account for the possibility of other (neutral and hence invisible) final states than those IV. DATA AND SIMULATED EVENTS searched for. While the search is optimized for R-hadrons The analysis presented in this paper is based long-lived enough to reach at least the hadronic calorimeter, pffiffiffi on a data samples with gluino lifetimes of 10, 30 and 50 ns, where a sample of 36.1 fb−1 of pp collisions at s ¼ 13 TeV collected in 2015 and 2016, with a bunch spacing of 25 ns. significant fraction of the LLPs will decay before the Reconstructed Z → μμ events in data and simulation are calorimeter, are also investigated. used for timing resolution studies. Simulated signal events PYTHIA6 relies on a parton shower to add additional are used to study the expected signal behavior. high-pT partons to the event. To achieve a more accurate Pair production of gluinos (squarks), with masses description of QCD radiative effects, the PYTHIA6 events between 400 and 3000 GeV (600 and 1400 GeV), was were reweighted to match the transverse-momentum dis- simulated in PYTHIA6 [36] (version 6.427) with the tribution of the gluino–gluino or squark–squark system to AUET2B [37] tuned set of underlying event and hadroni- the distribution obtained in dedicated leading-order zation parameters (tune) and the CTEQ6L1 [38] PDF set, MG5_AMC@NLO (version 2.2.3) [41] simulations with incorporating specialized hadronization routines [39,40] to one additional parton in the matrix-element calculation. 0.1 0.1 0.09 ATLAS Data 0.09 ATLAS Data s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 Z→μμ simulation Z→μμ simulation 0.08 0.08 0.07 0.07 Fraction of muons Fraction of muons 0.06 0.06 0.05 0.05 0.04 0.04 0.03 0.03 0.02 0.02 0.01 0.01 0 0 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 β β TILE ToF FIG. 2. The β-distributions of muons for a Z → μμ selection in data and simulation, with β measured solely in the tile calorimeter (βTILE , left), and as a combined measurement from RPCs, MDTs and tile calorimeter (βToF , right). 092007-4 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) Pair production of staus in a GMSB scenario [mMessenger ¼ denoted by EmissT ) or signatures of single (isolated) high- 500 TeV, Cgrav ¼ 100000, tan β ¼ 10, signðμÞ ¼ 1] was momentum muons. Large Emiss T values are produced mainly simulated with two additional partons at leading order, using when QCD initial-state radiation (ISR) boosts the R-hadron MG5_AMC@NLO (version 2.3.3) in combination with system, resulting in an imbalance between ISR and R- PYTHIA8 [42] (version 8.212) and EvtGen [43] (version hadrons whose momenta are not fully accounted for in the 1.2.0) with the A14 [44] tune and NNPDF23LO [45] Emiss T calculation. The adopted triggers impose thresholds PDF set. The pair-produced lightest stau mass eigenstate is from 70 to 110 GeV on Emiss T and 20 to 26 GeV on single a mixture of the left-handed and right-handed superpartners muons, depending on the data-taking period. of the τ-lepton, although it is the partner of the right-handed The offline event selection requires all relevant detector lepton at the 99% level in the model considered here. components to be fully operational, a primary vertex (PV) Pair production of charginos in an mAMSB scenario built from at least two well-reconstructed charged-particle (m0 ¼ 5 TeV, tan β ¼ 5) was simulated with two addi- tracks, each with pT > 400 MeV, and at least one candi- tional partons at leading order, using MG5_AMC@NLO date track that meets the criteria specified below. (version 2.3.3) in combination with PYTHIA8 (version A “common track selection” is implemented for 8.212) and EvtGen (version 1.2.0) with the A14 tune candidates in all SRs and is described below. ID tracks and NNPDF23LO PDF set. (denoted by the superscript “trk”) are required to have a Samples of Z → μμ events, which are used for general minimum ptrk T of 50 GeV and a momentum measurement testing, calorimeter and MS timing calibrations as well as ptrk < 6.5 TeV. The candidate track is required to be the evaluation of systematic uncertainties, were simulated matched to the PV using ‘loose’ requirements on the using POWHEG-BOX [46] (r2856) in combination with transverse (d0 ) and longitudinal (z0 ) impact parameters PYTHIA8 (version 8.186) and EvtGen (version 1.2.0) with (jd0 j < 2 mm, jz0 sin θj < 3 mm).3 To ensure good track the AZNLO [47] tune and CTEQ6L1 PDF set. reconstruction, the candidate track must have at least seven All events were passed through a full detector simu- silicon > 6), no shared or split clusters in silicon clusters4 (N clusters lation [48] based on the GEANT4 framework [49]. For the the pixel detector (N shared pix þ N split pix ¼ 0) [55], and at least R-hadron simulations, hadronic interactions with matter were handled by dedicated GEANT4 [49] routines based 5 three clusters in the SCT (N SCT clustersþdead > 2). Mainly to on different scattering models: the model used to describe ensure a reliable timing measurement in the calorimeters, gluino (squark) R-hadron interactions is referred to as it is required that the sum of the track-pT in a cone of the generic (Regge) model [50]. The R-hadrons interact ΔR ¼ 0.2 around the candidate track is below 5 GeV. Jets only moderately with the detector material, as most of the reconstructed in the calorimeter are used to veto electrons R-hadron momentum is carried by the heavy gluino or and SM hadrons. Jets are reconstructed with the anti-kt squark, which has a small interaction cross section. clustering algorithm [56] with radius parameter R ¼ 0.4 Typically, the energy deposit in the calorimeters is less and using as inputs clusters of energy deposits in the than 10 GeV. calorimeter, calibrated such that the average response of an All simulated events included a modeling of contributions electron is unity. The jets are then calibrated using the from pileup by overlaying minimum-bias pp interactions method described in Ref. [57]. An electron veto is imposed from the same (in-time pileup) and nearby (out-of-time by rejecting any candidate track for which the nearest jet pileup) bunch crossings simulated in PYTHIA8 (version with pT > 20 GeV and within a ΔR ¼ 0.05 cone around 8.186) and EvtGen (version 1.2.0) with the A2 [51] tune the track has at least 95% of its energy deposited in the and MSTW2008LO [52] PDF set. The simulated events electromagnetic calorimeter. A veto against SM hadrons is were reconstructed using the same software used for imposed by rejecting any candidate track for which any collision data, and were reweighted so that the distribution associated jet within a ΔR ¼ 0.05 cone of the track has of the number of collisions per bunch crossing matched that an energy larger than the track momentum. Candidate of the data. tracks are required to have a cluster in the innermost 3 The transverse impact parameter is defined as the distance of V. EVENT SELECTION closest approach between a track and the beam-line in the Five dedicated signal regions (SRs), imposing require- transverse plane. The longitudinal impact parameter corresponds to the z-coordinate distance between the primary vertex and the ments on the entire event and on the individual candidate point along the track at which the transverse impact parameter is tracks, are defined in this section, addressing differences in defined. 4 topology and expected interactions with the detector for The charge released by a moving charged particle is rarely three different benchmark scenarios: staus, charginos and contained within just one pixel; neighboring pixels/strips regis- tering hits are joined together using a connected component R-hadrons. analysis [53,54] to form clusters. Events are selected by online triggers based on large 5 This count includes the number of nonfunctional/dead mod- missing transverse momentum ( ⃗pmiss T , with magnitude ules traversed by the particle/track. 092007-5 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) TABLE I. Summary of the five sets of SRs. The trigger as well as the track candidate selection and the number of candidates per event required for the respective SR are given. Also the final selection requirements together with the mass window (one- or two-dimensional) for the final counting are stated. SRs in one block (delimited by horizontal lines) are combined for the statistical interpretation of the results. For SR-Rhad-FullDet, the ID+CALO is used as a fallback only if no LOOSE candidates are found in the event; hence the two SRs are mutually exclusive. Final requirements Candidate Candidates p Signal region Trigger selection per event jηj [GeV] βToF ðβγÞdE=dx Mass SR-Rhad-MSagno Emiss T ID+CALO ≥1 ≤1.65 ≥200 ≤0.75 ≤1.0 ToF & dE=dx SR-Rhad-FullDet Emiss T =μ LOOSE ≥1 ≤1.65 ≥200 ≤0.75 ≤1.3 ToF & dE=dx SR-Rhad-FullDet Emiss T =μ ID+CALO ≥1 ≤1.65 ≥200 ≤0.75 ≤1.0 ToF & dE=dx SR-2Cand-FullDet Emiss T =μ LOOSE ¼2 ≤2.00 ≥100 ≤0.95  ToF SR-1Cand-FullDet Emiss T =μ TIGHT ¼1 ≤1.65 ≥200 ≤0.80  ToF pixel-detector layer (if expected) or a cluster in the second tile calorimeter or MS, and fulfilling the requirements of the layer (if the innermost is not expected, but the second above-mentioned common track selection for its ID track. layer is). A “cosmics veto” rejects candidate tracks that In addition, the candidate tracks need to have a large have an opposite-sign track/muon on the other side of the combined transverse momentum (pcand T > 70 GeV), a com- detector, satisfying ΔRcosmics < 0.04.6 A “Z veto” rejects bined momentum pcand < 6.5 TeV, jηj < 2, and hits in at each candidate track that together with the highest-pT least two MS stations. All ToF -based β measurements must muon in the event forms an invariant mass within 10 GeVof be consistent, i.e., for candidates with β measurements in the Z-boson mass. more than one ToF system (N systems > 1), the weighted Three different selection criteria for each track in an means of all systems have to be consistent to within 5σ; and event, hereafter referred to as ID+CALO, LOOSE and TIGHT, for candidates with only one system (N systems ¼ 1) the are defined. The ID+CALO selection, which does not use MS respective internal measurements have to be consistent to information, is designed for the R-hadron searches. The within 5σ. In cases where a dE=dx measurement from the LOOSE and TIGHT criteria are applied to ID–MS combined pixel detector exists, the β estimates based on dE=dx and tracks in the search using the full detector information, with ToF have to be consistent to within 5σ. The uncertainty in TIGHT providing stricter requirements. the final β, whether from a single system or a weighted An ID+CALO candidate selection starts from an ID track average of several systems, has to be below 0.025 that fulfills the requirements of the above-mentioned (σ βToF < 0.025) for the candidate to be accepted. At least common track selection, and which has at least one timing one system has to yield a β measurement and a final value measurement in the tile calorimeter. In addition, the for βToF between 0.2 and 2 is required. candidate tracks need to have jηj < 1.65, to ensure a A TIGHT candidate selection is identical to the LOOSE minimal sensitivity in the tile calorimeter. To obtain a selection, except for a tighter pseudorapidity requirement reliable dE=dx measurement in the pixel detector, the (jηj < 1.65), an additional requirement on the pixel dE=dx tracks are required to have at least two clusters used in measurement (1 < dE=dx < 20 MeVg−1 cm2 ), and requir- good dE=dx > 1), a dE=dx value the respective estimation (N clusters ing at least two systems to yield a β measurement. between 0 and 20 MeV g cm2 , as well as an estimate of −1 To target the three different benchmark scenarios this βγ (0.2 < ðβγÞdE=dx < 10). To ensure a reliable ToF meas- analysis uses five distinct selections, as shown in Table I. urement in the calorimeter, individual βHITTILE estimates and Signal regions are defined by imposing requirements on their individual uncertainties from calorimeter cells asso- estimated masses, in addition to the criteria in Table I. ciated with the track are combined using a χ 2 , and the The signal regions that are combined are designed to be resulting weighted average βTILE is required to be between orthogonal to allow for a combination in the statistical 0.2 and 2, with an uncertainty σ βTILE < 0.06 and a χ 2 interpretation of the results. probability Pð χ 2 ; NDFÞ > 0.01. The search for stable R-hadrons is performed in both an A LOOSE candidate selection starts from a combined MS-agnostic SR (SR-Rhad-MSagno) and a full-detector ID–MS track with at least one timing measurement in the SR (SR-Rhad-FullDet) approach. The former is much less dependent on the hadronic-interaction model for R- pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi hadrons. It is based on events solely selected through Emiss 6 ΔRcosmics ¼ ðη1 þ η2 Þ2 þ ðΔϕ − πÞ2 , with η1=2 being the T pseudorapidity of and Δϕ the azimuthal angle between the triggers and candidates stemming from ID tracks fulfilling particles in question. the ID+CALO selection plus the final selection requirements 092007-6 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) 1200 1200 ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 1000 1000 mToF SR-1Cand-FullDet 800 mdE/dx 800 SR-2Cand-FullDet mmin [GeV] mmin [GeV] 600 600 400 400 200 200 0 0 0 500 1000 1500 2000 2500 3000 0 500 1000 1500 mtruth [GeV] mtruth [GeV] FIG. 3. The lower mass requirement (mmin ) defining the final counting regions in the mToF –mdE=dx plane used in the R-hadron searches (left) and the mToF -distribution used in the chargino and stau searches (right) for the respective simulated mass of the signal at particle level (mtruth ). The larger markers indicate the lower mass requirements for the “discovery regions.” stated in Table I. The full-detector search, on the other The searches for pair-produced stable staus and chargi- hand, takes full advantage of the MS, both in terms of nos are performed using two orthogonal SRs. The region triggering events and in using additional ToF measurements SR-2Cand-FullDet contains events with exactly two in the MDTs and RPCs. candidates fulfilling the LOOSE selection and the corre- Candidates originate from combined ID–MS tracks sponding final selection requirements stated in Table I, fulfilling the LOOSE selection and passing the final require- while SR-1Cand-FullDet contains events with exactly ments states in Table I. If no LOOSE candidate is found in the one candidate, which in this case must satisfy the TIGHT event, then it is checked whether there is any candidate selection and the corresponding final selection require- satisfying the ID+CALO requirements with the additional ments stated in Table I. For the region SR-2Cand- selections of Table I. The two selections are therefore FullDet, which has precedence over SR-1Cand- mutually exclusive. In the rare case of events with more FullDet in the event categorization, the candidate with than one candidate, the candidate with the highest pT is the lower mToF is used to derive limits. chosen to improve background suppression. A set of 16 discovery regions (DRs) is defined for setting The masses are derived from m ¼ p=βγ using momen- model-independent upper limits on cross sections and stating tum and ToF measurements to give mToF , and, where p0 values. These DRs are indicated by larger markers in applicable, ionization measurements to give mdE=dx . Fig. 3. The resulting DRs are: four for SR-Rhad-MSagno, The final selection requirements on the masses are then four for SR-Rhad-FullDet (combined ID+CALO þ obtained by fitting the reconstructed mass distribution in LOOSE), as well as four each for exclusive SR-2Cand- signal events for each simulated mass hypothesis with a FullDet and SR-1Cand-FullDet regions. Gaussian function, and taking the mean minus twice the width as the lower requirement on the respective mass VI. BACKGROUND ESTIMATION hypothesis. The upper requirement on the mass is left open, and hence is constrained only by kinematics to be The background is estimated with a fully data-driven < 6.5 TeV. For the R-hadron SRs the lower requirements method. First, the probability density functions (pdfs) of the are evaluated in the two-dimensional mToF –mdE=dx -plane, key variables are determined from data, using sideband while for SRs SR-2Cand-FullDet and SR-1Cand- regions where possible. The key variables are momentum, FullDet only the mToF distribution is used. This choice βToF and ðβγÞdE=dx for the R-hadron SRs, and momentum is based on the fact that especially for low-mass candidates and βToF for the chargino and stau SRs. Distributions of a significant fraction of candidates have dE=dx < expected background in mToF (and mdE=dx ) are obtained 0.945 MeV g−1 cm2 , at which point there is essentially by randomly sampling the pdfs and using the equation no separation power between the various mass hypotheses. m ¼ p=βγ. The final lower requirements on the masses are shown For this procedure to be valid, βToF and ðβγÞdE=dx must in Fig. 3. not be correlated with momentum. In principle this is true, 092007-7 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) 5000 ATLAS 2.5 Est. bkg s = 13.0 TeV, 36.1 fb-1 ~ 2200 GeV) Exp. signal (g 4000 Data 2 SR-Rhad-MSagno CR mToF [GeV] 3000 Events 1.5 750 GeV 2000 400 1 200 1000 0.5 850 GeV 0 0 200 400 0 0 0 1000 2000 3000 4000 5000 mdE/dx [GeV] 103 103 ATLAS -1 Est. bkg + stat. unc. ATLAS -1 Est. bkg + stat. unc. s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g 2 2 10 Data 10 Data SR-Rhad-MSagno SR-Rhad-MSagno Events/50GeV Events/50GeV 10 10 1 1 10−1 10−1 10−2 10−2 200 400 600 800 200 400 600 Data/bkg Data/bkg 1.5 1.5 mToF [GeV] mdE/dx [GeV] 1 1 0.5 0.5 0 200 400 600 800 >850 0 200 400 600 >750 mToF [GeV] mdE/dx [GeV] FIG. 4. Background estimate for the MS-agnostic analysis targeting gluino R-hadrons [SR-Rhad-MSagno (ID+CALO)] in the mToF –mdE=dx plane (top), the mToF -projection (bottom left) and the mdE=dx -projection (bottom right). The last bin of each distribution includes the overflow. The dashed red lines in the upper figure indicate the lower bounds of the signal region for a representative signal choice, while the dotted gray lines illustrate the upper bound for the control region. The signal (2200 GeV gluino R-hadron) is indicated by green markers in the upper and green dash-dotted lines in the lower plots. The lower panels show the ratio of observed data to estimated background. The shaded gray area shows the statistical uncertainty of the background estimate. as the primary background contribution is from high- bins. A variable binning is used to account for the different momentum muons with mismeasured βToF and ðβγÞdE=dx , regions of the subsystems used. For the sampling of the but there can be an implicit correlation via η, in particular as background, η from the candidate is used to get the the pT requirement for reconstructing candidates translates corresponding pdfs. This is a safe procedure as effects from into a momentum requirement preq > 200 GeV even for signal contamination are negligible. jηj < 2.0. This means that momentum is correlated with η To derive the SR-Rhad-MSagno and SR-Rhad- for jηj > 1.75 due to the lack of low-momentum tracks. FullDet momentum pdfs, the final requirements on As βToF and ðβγÞdE=dx are correlated with η due to the βToF and ðβγÞdE=dx are inverted, while for the βToF and different resolutions in different detector regions, the result is ðβγÞdE=dx pdfs the final requirement on the momentum is some correlation of βToF and ðβγÞdE=dx with momentum. To inverted and a minimum momentum of 50 GeV is required. remove the effect of these correlations, the pdfs are estimated For the SR-2Cand-FullDet, the momentum pdf can in five (SR-Rhad-MSagno, SR-Rhad-FullDet, SR- be estimated from a sideband in βToF , but not the βToF 1Cand-FullDet) or six (SR-2Cand-FullDet) jηj pdf, because in the high-jηj region no candidates with 092007-8 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) 5000 ATLAS 2.2 Est. bkg s = 13.0 TeV, 36.1 fb-1 ~ 2200 GeV) Exp. signal (g 2 4000 Data 1.8 SR-Rhad-FullDetLOOSE CR 1.6 mToF [GeV] 3000 1.4 Events 1.2 750 GeV 2000 1 400 0.8 200 0.6 1000 850 GeV 0.4 0 0 200 400 0.2 0 0 0 1000 2000 3000 4000 5000 mdE/dx [GeV] 103 103 ATLAS -1 Est. bkg + stat. unc. ATLAS -1 Est. bkg + stat. unc. s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g 2 2 10 Data 10 Data SR-Rhad-FullDetLOOSE SR-Rhad-FullDetLOOSE Events/50GeV Events/50GeV 10 10 1 1 10−1 10−1 10−2 10−2 200 400 600 800 200 400 600 Data/bkg Data/bkg 1.5 1.5 mToF [GeV] mdE/dx [GeV] 1 1 0.5 0.5 0 200 400 600 800 >850 0 200 400 600 >750 mToF [GeV] mdE/dx [GeV] FIG. 5. Background estimate for the full-detector analysis (LOOSE part) targeting gluino R-hadrons (SR-Rhad-FullDet) in the mToF –mdE=dx plane (top), the mToF -projection (bottom left) and the mdE=dx -projection (bottom right). The last bin of each distribution includes the overflow. The dashed red lines in the upper figure indicate the lower bounds of the signal region for a representative signal choice, while the dotted gray lines illustrate the upper bound for the control region. The signal (2200 GeV gluino R-hadron) is indicated by green markers in the upper and green dash-dotted lines in the lower plots. The lower panels show the ratio of observed data to estimated background. The shaded gray area shows the statistical uncertainty of the background estimate. p < 100 GeV are left. SR-1Cand-FullDet instead minimum mass requirement is replaced by an upper limit uses sidebands for the momentum pdfs, since for the tight on mdE=dx and mToF , which both have to be below 300 GeV. candidates jηj < 1.65 is required and hence tracks with Similarly, in the chargino/stau search, the minimum mass p < 200 GeV for the full range are available. For the β pdf requirement on mToF is replaced by an upper limit of in SR-1Cand-FullDet and SR-2Cand-FullDet, a 150 GeV and 200 GeV for SR-2Cand-FullDet and minimum momentum of 70 GeV is required. The final SR-1Cand-FullDet, respectively. requirements are summarized in Table I. The background estimates overlaid with MC signal events The background yield is normalized to data using low- at the expected mass limit are shown in Figs. 4–7. The mass control regions (CRs). The number of estimated statistical uncertainty from the pdfs is propagated to the events is scaled, so that the number of events in the CR background estimate and shown as gray bands. For all SRs, matches the number observed in data. In the R-hadron agreement between data and estimated background in the searches, the CR is identical to the SR except that the low-mass regions is found. 092007-9 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) 5000 ATLAS 4 Est. bkg s = 13.0 TeV, 36.1 fb-1 ~ 2200 GeV) Exp. signal (g 4000 Data 3.5 SR-Rhad-FullDetID+CALO CR 3 mToF [GeV] 3000 2.5 Events 750 GeV 2 2000 400 1.5 200 1 1000 850 GeV 0 0.5 0 200 400 0 0 0 1000 2000 3000 4000 5000 mdE/dx [GeV] 103 103 ATLAS Est. bkg + stat. unc. ATLAS Est. bkg + stat. unc. -1 -1 s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g s = 13.0 TeV, 36.1 fb ~ 2200 GeV) Exp. signal (g 2 2 10 Data 10 Data SR-Rhad-FullDetID+CALO SR-Rhad-FullDetID+CALO Events/50GeV Events/50GeV 10 10 1 1 10−1 10−1 10−2 10−2 200 400 600 800 200 400 600 Data/bkg Data/bkg 1.5 1.5 mToF [GeV] mdE/dx [GeV] 1 1 0.5 0.5 0 200 400 600 800 >850 0 200 400 600 >750 mToF [GeV] mdE/dx [GeV] FIG. 6. Background estimate for the full-detector analysis (ID+CALO part) targeting gluino R-hadrons (SR-Rhad-FullDet) in the mToF –mdE=dx plane (top), the mToF -projection (bottom left) and the mdE=dx -projection (bottom right). The last bin of each distribution includes the overflow. The dashed red lines in the upper figure indicate the lower bounds of the signal region for a representative signal choice, while the dotted gray lines illustrate the upper bound for the control region. The signal (2200 GeV gluino R-hadron) is indicated by green markers in the upper and green dash-dotted lines in the lower plots. The lower panels show the ratio of observed data to estimated background. The shaded gray area shows the statistical uncertainty of the background estimate. VII. SYSTEMATIC UNCERTAINTIES next-to-leading-logarithm accuracy (NLO þ NLL) [58–62]. Stau and chargino signal cross sections are calculated to The two major uncertainties in the signal yields are from NLO in the strong coupling constant (NLO) using the theoretical cross section and the modeling of ISR, as PROSPINO2 [63]. The nominal cross section and the well as the dedicated full-detector track reconstruction and uncertainty is taken from an envelope of cross-section the ToF-based β measurement in the MS in some cases. All predictions using different PDF sets and factorization and individual contributions are outlined below and summa- renormalization scales, as described in Ref. [64]. This rized in Table II. prescription results in an uncertainty in the cross section of between 14% (at 600 GeV) and 57% (at 3000 GeV) for A. Theoretical cross sections gluino R-hadrons, and between 14% (at 600 GeV) and 23% R-hadron production cross sections are calculated to (at 1400 GeV) for squark R-hadrons. For direct pair- next-to-leading order (NLO) in the strong coupling con- production of staus and chargino pair-production the stant, adding the resummation of soft-gluon emission at uncertainty is between 6% (at 290 GeV) and 10% 092007-10 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) 103 103 ATLAS Est. bkg + stat. unc. ATLAS Est. bkg + stat. unc. s = 13.0 TeV, 36.1 fb-1 ∼± s = 13.0 TeV, 36.1 fb-1 ∼± Exp. signal (Χ 1 1200 GeV) Exp. signal (Χ 1 1200 GeV) 102 102 Data Data SR-1Cand-FullDet (875 GeV) SR-2Cand-FullDet (850 GeV) Events/25GeV Events/25GeV CR CR 10 10 1 1 10− 1 10− 1 10− 2 10− 2 200 400 600 800 200 400 600 800 Data/bkg Data/bkg 1.5 1.5 mToF [GeV] mToF [GeV] 1 1 0.5 0.5 0 200 400 600 800 >875 0 200 400 600 800 >850 mToF [GeV] mToF [GeV] FIG. 7. Background estimate for the analysis targeting pair-produced staus and charginos in the one-TIGHT -candidate SR (left) and the two-LOOSE -candidates SR (right). The last bin of each distribution includes the overflow. The dashed red lines indicate the lower bound of the signal region for a representative signal choice, while the dotted gray lines illustrate the upper bound for the control region. The signal (1200 GeV chargino) is indicated by green dash-dotted lines. The lower panels show the ratio of observed data to estimated background. The shaded gray area shows the statistical uncertainty of the background estimate. (at 910 GeV) and between 4% (at 200 GeV) and 10% (at systematic uncertainties. To evaluate the trigger efficiency, 1500 GeV), respectively. the trigger turn-on curve is obtained by fitting the measured efficiency as a function of Emiss T in Z → μμ events, in both B. Signal efficiency data and simulation. These efficiency turn-on curves are Missing-transverse-momentum triggers used in these then applied to the Emiss T spectrum from simulated events. searches rely solely on calorimeter-energy deposits to The total uncertainty is estimated from four contributions: calculate the transverse energy, and are thus largely blind the relative difference between the efficiencies obtained to muons, which can therefore be used for calibration and using the fitted threshold curves from Z → μμ in data and TABLE II. Summary of systematic uncertainties. Ranges indicate a dependence on the mass hypothesis. Relative uncertainty [%] Source MS-agnostic R-hadrons Full-detector R-hadrons Staus Charginos Theoretical inclusive cross section 14–57 14–57 6–10 4–10 Total uncertainty in signal efficiency 17–19 18–30 7–15 9–18 Trigger efficiency 1.6 1.9 4.5 3.9 Emiss T 1.6 1.6 2.0 2.5 Single-muon 1.0 4.0 3.0 Theoretical uncertainty (ISR/FSR) 15 15 4 7 Pileup 0.2–3.8 0.3–5.5 0.1–3.1 0.2–4.4 Full-detector track reconstruction  1.7–14.8 0.2–12.8 0.8–13.0 Track hit requirements 2 2 2 2 Pixel βγ measurement 6.0–11.6 6.0–13.0 0.5 0.5 ToF β measurement 0.5–3.6 9.8–21.9 1.0–3.6 2.0–12.0 Calorimeter β measurement 0.1–0.5 0.1–1.1 0.1–0.5 0.1–0.5 Calorimeter OFA correction 0.4–3.6 1.2–3.1 0.1–0.4 0.1–1.3 MS β measurement  9.7–21.7 1.0–3.5 2.0–12.0 Luminosity 2.1 2.1 2.1 2.1 Uncertainty in background estimate 33–34 27–53 9–31 9–34 092007-11 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) simulation, the differences in efficiency obtained from renormalizaton/factorization scale is evaluated by changing independent 1σ variations in fit parameters relative to the default scale by a factor of two in MG5_AMC@NLO. the unchanged turn-on-curve fit for both Z → μμ data and The uncertainty from the choice of CKKW-L merging simulation, and a 10% variation of the Emiss T to assess the [65,66] scale is evaluated by taking the maximum deviation scale uncertainty. The Emiss T trigger is estimated to contrib- from the nominal MC sample when varying it by a factor of ute a total uncertainty of 1.6% and 2% to the signal two. The uncertainty from the parton-shower generator efficiency for R-hadrons and staus/charginos, respectively. tuning is evaluated using PYTHIA8 tune variations. The To account for a possible mismodeling of the single- systematic uncertainty on the ISR/FSR is calculated by muon trigger timing in simulation, all simulated events adding all three components in quadrature. The uncertainties were reweighted, depending on the β and jηj of the are evaluated for three mass points of staus and charginos candidate, to match the data and to compute systematic and are estimated to be 4% and 5%, respectively. The latter uncertainties. Systematic uncertainties of 1%, 4% and 3% procedure was also implemented for the MG5_AMC@NLO are assigned to R-hadrons, staus and charginos, respec- gluino–gluino and squark–squark samples, and the resulting tively, by taking the difference in signal trigger efficiency uncertainties are similar to the nominal-vs-reweighted ones. between unweighted and reweighted events. The uncertainty in the pileup modeling in simulation is To address a possible mismodeling of ISR, and hence found to affect the signal efficiency by between 0.1% and Emiss in the signal events, half of the difference between the 5.5%, typically decreasing as a function of the simulated T selection efficiency for the nominal PYTHIA6 events and LLP mass and varying with benchmark model. those reweighted to match MG5_AMC@NLO predictions is An additional systematic uncertainty in the signal taken as an uncertainty in the expected signal yield, efficiency is estimated for the dedicated tracking algorithm and found to be below 15% in all cases. For staus to cover all discrepancies between data and simulation, and charginos, the uncertainties in the amount of ISR by randomly rejecting 10% of the reconstructed objects. (and FSR) are evaluated by varying generator parameters The effect on the final signal efficiency is found to be in the simulation. The uncertainty from the choice of between 0.2% and 14.8%. TABLE III. Expected signal yield (N exp ) and acceptance (a) × efficiency (ε), estimated background (N est ) and observed number of events in data (N obs ) for the full range of simulated masses in the MS-agnostic R-hadron search. SR-Rhad-MSagno (ID+CALO) R-hadron Simulated mass [GeV] N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs Gluino 400 160000  30000 0.044  0.003 8.0  3.0 8 600 28000  5000 0.086  0.004 3.0  1.0 7 800 6000  1000 0.106  0.005 1.8  0.6 4 1000 1300  200 0.114  0.005 1.0  0.3 2 1200 400  70 0.129  0.006 0.7  0.3 2 1400 140  30 0.148  0.007 0.6  0.2 2 1600 42  7 0.143  0.007 0.5  0.2 2 1800 13  2 0.134  0.007 0.4  0.1 2 2000 4.4  0.8 0.126  0.006 0.4  0.1 2 2200 1.5  0.3 0.114  0.004 0.4  0.1 2 2400 0.51  0.09 0.106  0.004 0.4  0.1 2 2600 0.18  0.03 0.101  0.004 0.4  0.1 2 2800 0.06  0.01 0.090  0.004 0.4  0.1 2 3000 0.023  0.004 0.090  0.004 0.4  0.1 2 Sbottom 600 400  80 0.063  0.003 3.0  1.0 7 800 80  20 0.083  0.004 1.8  0.6 4 1000 19  3 0.087  0.004 1.0  0.3 2 1200 5.4  0.9 0.093  0.004 0.7  0.3 2 1400 1.5  0.3 0.093  0.004 0.6  0.2 2 Stop 600 600  100 0.095  0.005 3.0  1.0 7 800 120  200 0.117  0.005 1.8  0.6 4 1000 28  5 0.128  0.005 1.0  0.3 2 1200 81 0.139  0.005 0.7  0.3 2 1400 2.4  0.4 0.146  0.005 0.6  0.2 2 092007-12 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) TABLE IV. Expected signal yield (N exp ) and acceptance (a) × efficiency (ε), estimated background (N est ) and observed number of events in data (N obs ) for the full range of simulated masses in the full-detector R-hadron search. SR-Rhad-FullDet (LOOSE) SR-Rhad-FullDet (ID+CALO) Simulated mass R-hadron [GeV] N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs Gluino 400 60000  20000 0.016  0.002 1.5  0.5 1 160000  3000 0.044  0.003 9.0  2.0 13 600 11000  4000 0.033  0.003 0.5  0.2 1 24000  4000 0.071  0.004 4.0  1.0 9 800 2400  600 0.044  0.003 0.3  0.1 1 4500  800 0.083  0.004 2.5  0.7 5 1000 500  100 0.045  0.003 0.14  0.05 0 1100  200 0.091  0.005 1.6  0.4 3 1200 160  40 0.053  0.004 0.10  0.04 0 300  50 0.096  0.005 1.3  0.4 2 1400 60  10 0.063  0.005 0.07  0.03 0 100  20 0.104  0.006 1.1  0.3 2 1600 17  4 0.057  0.004 0.06  0.03 0 30  6 0.104  0.006 1.0  0.3 2 1800 51 0.052  0.004 0.05  0.03 0 10  2 0.099  0.006 0.9  0.3 2 2000 1.9  0.4 0.053  0.003 0.05  0.02 0 2.9  0.6 0.083  0.004 0.9  0.2 2 2200 0.6  0.1 0.043  0.003 0.05  0.02 0 1.0  0.2 0.079  0.003 0.9  0.2 2 2400 0.18  0.04 0.037  0.002 0.05  0.02 0 0.38  0.07 0.079  0.004 0.9  0.2 2 2600 0.07  0.01 0.036  0.002 0.05  0.02 0 0.13  0.02 0.074  0.003 0.9  0.2 2 2800 0.019  0.004 0.027  0.002 0.05  0.02 0 0.049  0.009 0.071  0.003 0.9  0.2 2 3000 0.007  0.002 0.028  0.002 0.05  0.02 0 0.017  0.003 0.066  0.003 0.9  0.2 2 Sbottom 600 200  50 0.032  0.002 0.5  0.2 1 300  60 0.047  0.003 4.0  1.0 9 800 38  8 0.037  0.003 0.3  0.1 1 60  10 0.061  0.003 2.5  0.7 5 1000 92 0.040  0.003 0.14  0.05 0 14  3 0.064  0.003 1.6  0.4 3 1200 2.5  0.5 0.043  0.003 0.10  0.04 0 3.9  0.7 0.068  0.003 1.3  0.4 2 1400 0.7  0.1 0.042  0.003 0.07  0.03 0 1.1  0.2 0.069  0.003 1.1  0.3 2 Stop 600 390  70 0.062  0.004 0.5  0.2 1 370  70 0.059  0.004 41 9 800 80  20 0.075  0.004 0.3  0.1 1 80  20 0.077  0.004 2.5  0.7 5 1000 18  4 0.083  0.004 0.14  0.05 0 18  3 0.081  0.004 1.6  0.4 3 1200 51 0.088  0.004 0.10  0.04 0 4.9  0.9 0.085  0.004 1.3  0.4 2 1400 1.6  0.3 0.093  0.005 0.07  0.03 0 1.5  0.3 0.089  0.004 1.1  0.3 2 105 Data 104 ATLAS Background -1 s = 13 TeV, 36.1 fb Background unc. 103 102 Events 10 1 −1 10 10−2 10−3 CR 350 550 700 850 CR 35 55 70 85 CR 17 375 600 825 CR 15 350 575 FD 0 300 0 450 0 600 0 750 1C 5 2C 0 Significance [σ] MA 300 4 6 7 3 MA 50 MA 00 MA 50 MA FD FD FD FD 1C 1C 1C 1C 2C 2C 2C 2 1 0 350 300 550 450 700 600 850 750 350 300 550 450 700 600 850 750 mdE/dx, low CR CR CR CR mToF, low 175 375 600 825 150 350 575 800 [GeV] Rhad-MSagno Rhad-FullDet 1Cand-FullDet 2Cand-FullDet FIG. 8. Expected and observed events in the 16 discovery regions introduced in Sec. V and for the respective CRs, including the systematic uncertainties. For data the Poisson error is shown. The lower plot shows the significance for SRs with a surplus of events between observed and estimated. The bin contents of SRs with inclusive mass ranges are correlated. 092007-13 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) TABLE V. p0 values and model-independent upper limits on cross section (σ) × acceptance (a) × efficiency (ε) for the 16 discovery regions. Lower mass requirements mmin ToF mmin dE=dx Significance 95% C.L. upper Selection [GeV] [GeV] N est  σ N est N obs p0 [σ] limit σ × a × ε [fb] SR-Rhad-MSagno 350 300 8.0  3.0 8 0.5 0.25 550 450 1.8  0.6 4 0.056 1.59 0.20 700 600 0.7  0.3 2 0.11 1.24 0.17 850 750 0.4  0.1 2 0.028 1.92 0.17 SR-Rhad-FullDet 350 300 11  2 14 0.22 0.77 0.42 550 450 2.8  0.7 6 0.081 1.40 0.25 700 600 1.4  0.4 2 0.28 0.57 0.14 850 750 0.95  0.2 2 0.18 0.93 0.14 SR-1Cand-FullDet 175 240  20 227 0.5 1.26 375 17  2 16 0.5 0.24 600 2.2  0.2 1 0.5 0.10 825 0.48  0.07 0 0.5 0.08 SR-2Cand-FullDet 150 1.5  0.3 0 0.5 0.09 350 0.06  0.01 0 0.5 0.08 575 0.007  0.002 0 0.5 0.08 800 0.0017  0.0009 0 0.5 0.08 Uncertainties in the measurement of dE=dx in the pixel By comparing the signal efficiency with and without detector result in uncertainties in the signal yield ranging the correction for incorrectly modeled timing behavior in from 6% to 13% for R-hadrons and less than 0.5% for staus the RPCs, the overall uncertainty is found to be between and charginos. They account for both the shape difference 1.0% and 21.7%. between the ionization distribution in data and simulation, and the scale shift in data due to radiation damage. C. Integrated luminosity The systematic uncertainty in the calorimeter-based β The uncertainty in the combined 2015 þ 2016 integrated estimation is assessed by scaling the calorimeter-cell-time luminosity is 2.1%. It is derived, following a methodology smearing of simulated events by 5% and by varying similar to that detailed in Ref. [67], from a calibration of the the cell-time correction introduced to correct for the bias luminosity scale using x-y beam-separation scans per- due to the OFA by 50%, and is found to be below 2% in formed in August 2015 and May 2016. all cases. The systematic uncertainty in the MS-based β estima- D. Background estimation tion is derived by varying the MDT smearing constants To estimate the systematic uncertainty of the background by 10% to bracket the distribution seen in data. estimate, three main contributions are considered: the TABLE VI. Expected signal yield (N exp ) and acceptance (a) × efficiency (ε), estimated background (N est ) and observed number of events in data (N obs ) for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons. Gluino R-hadron SR-Rhad-MSagno (ID+CALO) Lifetime 10 ns 30 ns 50 ns Simulated mass [GeV] N exp  σ N exp a × ε  σ a×ε N exp  σ N exp a × ε  σ a×ε N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs 1000 800  100 0.065  0.004 1400  300 0.121  0.006 1500  300 0.125  0.005 1.0  0.3 2 1200 220  40 0.072  0.004 400  70 0.129  0.006 410  70 0.133  0.005 0.7  0.3 2 1400 70  10 0.079  0.004 120  20 0.132  0.005 140  30 0.149  0.006 0.6  0.2 2 1600 22  4 0.074  0.003 41  7 0.140  0.005 41  7 0.142  0.005 0.5  0.2 2 1800 81 0.077  0.003 14  2 0.139  0.005 14  2 0.142  0.005 0.4  0.1 2 2000 2.8  0.5 0.080  0.005 4.7  0.8 0.132  0.007 5.2  0.9 0.146  0.005 0.4  0.1 2 2200 1.0  0.2 0.075  0.004 1.7  0.3 0.132  0.005 1.7  0.3 0.130  0.004 0.4  0.1 2 2400 0.35  0.06 0.073  0.004 0.58  0.10 0.120  0.004 0.6  0.1 0.122  0.004 0.4  0.1 2 092007-14 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) TABLE VII. Expected signal yield (N exp ) and acceptance (a) × efficiency (ε), estimated background (N est ) and observed number of events in data (N obs ) for the full range of simulated masses in the full-detector direct-stau search. SR-2Cand-FullDet SR-1Cand-FullDet Simulated mass [GeV] N exp  σ N exp a × ε  σ a×ε N exp  σ N exp N obs N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs 287 13  1 0.167  0.005 0.33  0.06 0 5.1  0.6 0.068  0.003 80.0  7.0 74 318 91 0.179  0.007 0.22  0.04 0 3.6  0.4 0.073  0.004 56.0  5.0 52 349 6.1  0.7 0.181  0.005 0.15  0.03 0 2.5  0.2 0.076  0.003 41.0  4.0 36 380 4.3  0.6 0.184  0.006 0.11  0.02 0 2.1  0.2 0.089  0.005 30.0  3.0 24 411 3.2  0.4 0.196  0.005 0.08  0.02 0 1.5  0.1 0.093  0.004 23.0  2.0 20 442 2.4  0.3 0.198  0.007 0.06  0.01 0 1.2  0.2 0.096  0.005 17.0  2.0 16 473 1.8  0.3 0.204  0.005 0.045  0.009 0 0.92  0.09 0.105  0.004 13.0  1.0 15 504 1.4  0.2 0.210  0.005 0.035  0.007 0 0.68  0.06 0.105  0.004 10.1  1.0 11 536 1.0  0.1 0.208  0.005 0.027  0.006 0 0.55  0.06 0.111  0.004 7.9  0.8 7 567 0.84  0.10 0.224  0.006 0.027  0.006 0 0.43  0.04 0.113  0.004 6.3  0.6 4 598 0.65  0.09 0.227  0.006 0.022  0.005 0 0.34  0.03 0.118  0.004 5.0  0.5 3 629 0.50  0.07 0.227  0.006 0.017  0.004 0 0.27  0.02 0.124  0.004 5.0  0.5 3 660 0.40  0.05 0.234  0.006 0.014  0.003 0 0.22  0.02 0.125  0.005 4.0  0.4 3 692 0.30  0.05 0.224  0.008 0.011  0.003 0 0.17  0.02 0.125  0.005 3.2  0.3 2 723 0.24  0.03 0.229  0.007 0.009  0.002 0 0.13  0.01 0.120  0.005 2.6  0.3 1 754 0.19  0.02 0.224  0.006 0.008  0.002 0 0.112  0.009 0.132  0.004 2.2  0.2 1 785 0.15  0.02 0.222  0.006 0.007  0.002 0 0.091  0.007 0.135  0.005 1.8  0.2 0 817 0.12  0.01 0.219  0.006 0.007  0.002 0 0.073  0.006 0.134  0.004 1.5  0.1 0 848 0.09  0.01 0.215  0.005 0.006  0.001 0 0.061  0.005 0.138  0.004 1.3  0.1 0 879 0.08  0.01 0.212  0.005 0.005  0.001 0 0.052  0.005 0.146  0.005 1.3  0.1 0 911 0.065  0.007 0.225  0.006 0.004  0.001 0 0.041  0.003 0.144  0.005 1.1  0.1 0 TABLE VIII. Expected signal yield (N exp ) and acceptance (a) × efficiency (ε), estimated background (N est ) and observed number of events in data (N obs ) for the full range of simulated masses in the full-detector chargino search. SR-2Cand-FullDet SR-1Cand-FullDet Simulated mass [GeV] N exp  σ N exp a × ε  σ a×ε N est  σ N exp N obs N exp  σ N exp a × ε  σ a×ε N est  σ N est N obs 200 2600  400 0.083  0.003 1.5  0.3 0 1200  200 0.038  0.002 230  20 227 250 1200  200 0.091  0.003 0.51  0.10 0 800  100 0.062  0.003 110  10 109 300 690  100 0.102  0.004 0.33  0.06 0 490  50 0.073  0.003 79  7 74 350 360  50 0.101  0.004 0.15  0.03 0 280  30 0.078  0.003 41  4 36 400 220  30 0.107  0.004 0.08  0.02 0 180  20 0.089  0.004 23  2 20 450 140  20 0.113  0.004 0.06  0.01 0 120  10 0.100  0.004 17  2 16 500 90  10 0.115  0.004 0.034  0.007 0 77  8 0.100  0.004 10  1 11 550 59  8 0.119  0.004 0.027  0.006 0 52  5 0.105  0.004 7.9  0.8 7 600 42  6 0.129  0.004 0.021  0.004 0 36  4 0.110  0.004 5.0  0.5 3 650 27  4 0.123  0.004 0.014  0.003 0 24  2 0.107  0.004 4.0  0.4 3 700 18  3 0.122  0.004 0.011  0.003 0 17  2 0.113  0.004 3.2  0.3 2 750 12  2 0.113  0.004 0.008  0.002 0 13  1 0.118  0.004 2.1  0.2 1 800 91 0.120  0.004 0.007  0.002 0 9.2  0.9 0.123  0.004 1.8  0.2 0 850 6.0  0.8 0.112  0.005 0.006  0.001 0 6.1  0.6 0.114  0.005 1.3  0.1 0 900 4.2  0.6 0.108  0.004 0.004  0.001 0 4.7  0.5 0.121  0.004 1.1  0.1 0 950 3.2  0.5 0.112  0.004 0.003  0.001 0 3.3  0.3 0.118  0.004 1.0  0.1 0 1000 2.2  0.4 0.106  0.005 0.0029  0.0009 0 2.5  0.2 0.120  0.006 0.84  0.10 0 1100 1.2  0.2 0.105  0.004 0.0019  0.0007 0 1.5  0.2 0.131  0.004 0.54  0.07 0 1200 0.62  0.09 0.096  0.004 0.0015  0.0006 0 0.74  0.07 0.115  0.004 0.42  0.06 0 1300 0.32  0.04 0.087  0.003 0.0012  0.0006 0 0.44  0.05 0.118  0.004 0.33  0.05 0 1400 0.19  0.03 0.087  0.004 0.0009  0.0005 0 0.26  0.03 0.120  0.004 0.27  0.04 0 1500 0.10  0.02 0.077  0.003 0.0007  0.0005 0 0.16  0.01 0.121  0.004 0.21  0.04 0 092007-15 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) systematic uncertainty of the normalization as well as the estimated and half the maximal difference in the number influence of the jηj binning and the definition of the of background events in the SR is taken as a systematic sidebands. The normalization uncertainty, derived by uncertainty. To check for an influence of the sideband applying the relative statistical uncertainty in the number definition, the selection requirements are varied, the pdfs of data events in the CR to the estimated number of re-evaluated correspondingly, and half the maximal differ- background events in the SR, is the dominant contribution ence of background counts in the SR, using the nominal for most SRs. Only at very high masses do the other and varied pdfs, is taken as the systematic uncertainty. contributions become significant and eventually take over. To test the stability of the choice of jηj binning, the number VIII. RESULTS of jηj bins in the pdfs is varied from nominal five (six) to three (four) and six (nine) for SR-Rhad-MSagno, Mass distributions observed in data together with the SR-Rhad-FullDet and SR-1Cand-FullDet (SR- background estimate, its statistical uncertainty and a 2Cand-FullDet). For each pdf, the background is representative expected signal are shown in Figs. 4–7 for 102 ATLAS -1 s = 13 TeV, 36.1 fb Theory prediction Expected limit ± 1σ Observed limit 10 Cross section [fb] SR-Rhad-MSagno SR-Rhad-FullDet 1 Gluino −1 10 500 1000 1500 2000 2500 3000 m ~ g [GeV] 102 102 ATLAS ATLAS s = 13 TeV, 36.1 fb-1 s = 13 TeV, 36.1 fb-1 Theory prediction Theory prediction Expected limit ± 1σ Expected limit ± 1σ Observed limit Observed limit 10 10 Cross section [fb] Cross section [fb] SR-Rhad-MSagno SR-Rhad-MSagno SR-Rhad-FullDet SR-Rhad-FullDet 1 1 Sbottom Stop 10−1 10−1 600 800 1000 1200 1400 600 800 1000 1200 1400 ~ ~ m b [GeV] m t [GeV] FIG. 9. Expected (dashed lines) and observed (marked solid lines) upper cross-section limits in the gluino (top), sbottom (bottom left) and stop (bottom right) R-hadron searches, respectively, using two independent and not to be combined approaches based on SRs SR- Rhad-MSagno (light blue) and SR-Rhad-FullDet (red). The shaded light-blue/light-red bands represent the 1σ uncertainties in the expected limits. The result obtained using the former SR has a much reduced dependence on the modeling of R-hadron interaction with matter with respect to the other, therefore the two results must not combined. The theory prediction along with its 1σ uncertainty is shown as a white line and a dark-blue band, respectively. 092007-16 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) the MS-agnostic and full-detector R-hadron, stau and and is due to the change in production channel for gluino chargino searches, respectively. R-hadrons from gluon-initiated to quark-initiated with As can be seen in Tables III–VIII, no significant excess increasing mass. of observed data events above the expected background is For metastable gluino R-hadrons, the MS-agnostic found in the examined mass ranges and signal regions. The search yields expected lower limits on mass of 1980, yields are summarized for a subset of discovery regions 2080 and 2090 GeV for lifetimes of 10, 30 and 50 ns, (see Sec. V) in Fig. 8 and Table V, the latter also showing respectively. The corresponding observed lower limits are the p0 values. 1860, 1960 and 1980 GeV. The expected signal yield (N exp ) Upper limits at 95% confidence level (C.L.) are placed on and efficiency, estimated background (N est ) and observed the production cross sections for various benchmark models, number of events in data (N obs ) for the full range of as shown in Figs. 9 and 10. These limits are obtained from simulated masses can be found in Table VI. As additional the expected signal and the estimated background in signal Emiss T can arise from one of the gluino R-hadrons decaying region SR-Rhad-MSagno (SR-Rhad-FullDet or before the calorimeters, the sensitivity increases for mass SR-1Cand-FullDet/SR-2Cand-FullDet) using a regions that have limited trigger efficiency (low and high one-bin (two-bin) counting experiment applying the CLs masses). With decreasing lifetime, and thereby increasing prescription [68]. Model-independent upper limits defined as probability for both gluino R-hadrons to decay before the cross section × acceptance × efficiency for the above- calorimeters, the signal efficiency drops, as does the mentioned discovery regions are shown in Table V. Given sensitivity of the search optimized for R-hadrons long- the predicted theoretical cross sections, also shown in Figs. 9 lived enough to exit the detector. However, the expected and 10, the cross-section limits are translated into lower lower limits on mass at lifetimes of 50 and 30 ns remain limits on masses for the various benchmark models. more stringent than those of the search targeting low- The MS-agnostic search yields expected lower limits at lifetime metastable gluino R-hadrons [31]. Expected and 95% C.L. on the R-hadron masses of 2060, 1270 and observed lower limits on mass as a function of lifetime for 1345 GeV for the production of long-lived gluino, sbottom both the MS-agnostic and full-detector searches for gluino and stop R-hadrons, respectively. The corresponding R-hadrons are shown in Fig. 11. observed lower limits on the masses are 1950, 1190 and Using the full-detector search, the expected (observed) 1265 GeV. The expected signal yield (N exp ) and efficiency, lower limits on the mass are 2050 GeV (2000 GeV), estimated background (N est ) and observed number of 1280 GeV (1250 GeV) and 1370 GeV (1340 GeV) for the events in data (N obs ) for the full range of simulated masses production of long-lived gluino, sbottom and stop R- can be found in Table III. The sensitivity first increases and hadrons, respectively. The expected signal yield (N exp ) then decreases with increasing R-hadron mass. The same and efficiency, estimated background (N est ) and observed effect is visible in the total efficiency of the Emiss T trigger, number of events in data (N obs ) for the full range of 3 3 10 10 ATLAS ATLAS -1 s = 13 TeV, 36.1 fb s = 13 TeV, 36.1 fb-1 Theory prediction Theory prediction Expected ± 1σ Expected ± 1σ 10 2 10 2 Expected ± 2σ Expected ± 2σ Cross section [fb] Cross section [fb] Observed limit Observed limit SR-2Cand-FullDet SR-2Cand-FullDet SR-1Cand-FullDet SR-1Cand-FullDet 10 10 1 1 10 −1 Stau 10 −1 Chargino 400 600 800 500 1000 1500 m ∼τ [GeV] ∼± m Χ1 [GeV] FIG. 10. Expected (dashed red line) and observed (marked solid red line) upper cross-section limits using combined two- and one- candidate SRs for stau pair production (left) and chargino pair production (right). The shaded dark-red (light-red) bands represent the 1σ (2σ) uncertainties in the expected limits. The theory prediction along with its 1σ uncertainty is shown as a white line and a blue band, respectively. 092007-17 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) 3000 slower than the speed of light. No significant deviations ATLAS from the expected background are observed. Upper limits s = 13 TeV, 36.1 fb-1 at 95% confidence level are provided on the production 2500 Expected SR-Rhad-MSagno cross sections of long-lived R-hadrons, as well as directly Lower limit on m~g [GeV] Observed SR-Rhad-FullDet pair-produced staus and charginos. These results translate into lower limits on the masses of long-lived gluino, 2000 sbottom and stop R-hadrons, as well as staus and charginos of 2000, 1250, 1340, 430 and 1090 GeV, respectively. 1500 ACKNOWLEDGMENTS stable We thank CERN for the very successful operation of the 1000 LHC, as well as the support staff from our institutions 10 20 30 40 50 without whom ATLAS could not be operated efficiently. η=0 βγ =1 Calorimeter Muon Spectrometer τ [ns] We acknowledge the support of ANPCyT, Argentina; 3 4 5 6 7 8 9 10 YerPhI, Armenia; ARC, Australia; BMWFW and FWF, cτ [m] Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; FIG. 11. Expected (dashed blue line) and observed (solid blue CONICYT, Chile; CAS, MOST and NSFC, China; line) lower mass limits at the 95% C.L. level for gluino R-hadrons COLCIENCIAS, Colombia; MSMT CR, MPO CR and with different mean lifetimes derived using the MS-agnostic analysis (SR-Rhad-MSagno). Expected (empty circles) and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; observed (filled circles) limits on stable gluino R-hadrons are IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, shown for both the MS-agnostic (SR-Rhad-MSagno) and the Georgia; BMBF, HGF, and MPG, Germany; GSRT, full-detector analysis (SR-Rhad-FullDet). Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, simulated masses can be found in Table IV. The sensitivity Norway; MNiSW and NCN, Poland; FCT, Portugal; of the R-hadron full-detector search in mass regions with MNE/IFA, Romania; MES of Russia and NRC KI, noticeable background yields is slightly better than that of Russian Federation; JINR; MESTD, Serbia; MSSR, the MS-agnostic search, due mainly to the increased signal Slovakia; ARRS and MIZŚ, Slovenia; DST/NRF, South efficiency when including the single-muon trigger and an Africa; MINECO, Spain; SRC and Wallenberg Foundation, improved β-resolution when using full-detector candidates. Sweden; SERI, SNSF and Cantons of Bern and Geneva, However, this specific search is consequently slightly more Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, model-dependent, especially on the modeling of hadronic United Kingdom; DOE and NSF, United States of interactions. America. In addition, individual groups and members Expected (observed) lower limits on mass for direct have received support from BCKDF, CANARIE, CRC production of staus and charginos are set at 420 GeV and Compute Canada, Canada; COST, ERC, ERDF, (430 GeV) and 1070 GeV (1090 GeV), respectively. The Horizon 2020, and Marie Skłodowska-Curie Actions, expected signal yield (N exp ) and efficiency, estimated European Union; Investissements d’ Avenir Labex and background (N est ) and observed number of events in data Idex, ANR, France; DFG and AvH Foundation, Germany; (N obs ) for the full range of simulated masses can be found Herakleitos, Thales and Aristeia programmes co-financed in Tables VII and VIII. by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, IX. CONCLUSION Spain; The Royal Society and Leverhulme Trust, United A search for heavy, charged, long-lived particles is Kingdom. The crucial computing support from all WLCG −1 ffiffiffi sample of 36.1 fb of proton- performed using a p data partners is acknowledged gratefully, in particular from proton collisions at s ¼ 13 TeV collected by the ATLAS CERN, the ATLAS Tier-1 facilities at TRIUMF experiment at the Large Hadron Collider at CERN. The (Canada), NDGF (Denmark, Norway, Sweden), CC- search is based on observables related to large ionization IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF losses, measured in the innermost tracking detector, and (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC slow propagation velocities, measured in the tile calorim- (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities eter and muon spectrometer. Both observables are signa- worldwide and large non-WLCG resource providers. Major tures of heavy charged particles traveling significantly contributors of computing resources are listed in Ref. [69]. 092007-18 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. 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M. Farina,68a,68b T. Farooque,104 S. Farrell,18 S. M. Farrington,175 P. Farthouat,35 F. Fassi,34e P. Fassnacht,35 D. Fassouliotis,9 M. Faucci Giannelli,48 W. J. Fawcett,31 L. Fayard,129 O. L. Fedin,135,s W. Fedorko,172 M. Feickert,41 S. Feigl,131 L. Feligioni,99 C. Feng,58b E. J. Feng,35 M. Feng,47 M. J. Fenton,55 A. B. Fenyuk,121 J. Ferrando,44 A. Ferrari,169 P. Ferrari,118 R. Ferrari,68a D. E. Ferreira de Lima,59b A. Ferrer,171 D. Ferrere,52 C. Ferretti,103 F. Fiedler,97 A. Filipčič,89 F. Filthaut,117 K. D. Finelli,25 M. C. N. Fiolhais,137a,137c,t L. Fiorini,171 C. Fischer,14 W. C. Fisher,104 N. Flaschel,44 I. Fleck,148 P. Fleischmann,103 R. R. M. Fletcher,134 T. Flick,179 B. M. Flierl,112 L. M. Flores,134 L. R. Flores Castillo,61a 092007-22 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) F. M. Follega,73a,73b N. Fomin,17 G. T. Forcolin,73a,73b A. Formica,142 F. A. Förster,14 A. C. Forti,98 A. G. Foster,21 D. Fournier,129 H. Fox,87 S. Fracchia,146 P. Francavilla,69a,69b M. Franchini,23b,23a S. Franchino,59a D. Francis,35 L. Franconi,143 M. Franklin,57 M. Frate,168 A. N. Fray,90 D. Freeborn,92 B. Freund,107 W. S. Freund,78b E. M. Freundlich,45 D. C. Frizzell,125 D. Froidevaux,35 J. A. Frost,132 C. Fukunaga,161 E. Fullana Torregrosa,171 E. Fumagalli,53b,53a T. Fusayasu,114 J. Fuster,171 O. Gabizon,157 A. Gabrielli,23b,23a A. Gabrielli,18 G. P. Gach,81a S. Gadatsch,52 P. Gadow,113 G. Gagliardi,53b,53a L. G. Gagnon,107 C. Galea,27b B. Galhardo,137a,137c E. J. Gallas,132 B. J. Gallop,141 P. Gallus,139 G. Galster,39 R. Gamboa Goni,90 K. K. Gan,123 S. Ganguly,177 J. Gao,58a Y. Gao,88 Y. S. Gao,150,u C. García,171 J. E. García Navarro,171 J. A. García Pascual,15a C. Garcia-Argos,50 M. Garcia-Sciveres,18 R. W. Gardner,36 N. Garelli,150 S. Gargiulo,50 V. Garonne,131 K. Gasnikova,44 A. Gaudiello,53b,53a G. Gaudio,68a I. L. Gavrilenko,108 A. Gavrilyuk,109 C. Gay,172 G. Gaycken,24 E. N. Gazis,10 C. N. P. Gee,141 J. Geisen,51 M. Geisen,97 M. P. Geisler,59a C. Gemme,53b M. H. Genest,56 C. Geng,103 S. Gentile,70a,70b S. George,91 D. Gerbaudo,14 G. Gessner,45 S. Ghasemi,148 M. Ghasemi Bostanabad,173 M. Ghneimat,24 B. Giacobbe,23b S. Giagu,70a,70b N. Giangiacomi,23b,23a P. Giannetti,69a A. Giannini,67a,67b S. M. Gibson,91 M. Gignac,143 D. Gillberg,33 G. Gilles,179 D. M. Gingrich,3,f M. P. Giordani,64a,64c F. M. Giorgi,23b P. F. Giraud,142 P. Giromini,57 G. Giugliarelli,64a,64c D. Giugni,66a F. Giuli,132 M. Giulini,59b S. Gkaitatzis,159 I. Gkialas,9,v E. L. Gkougkousis,14 P. Gkountoumis,10 L. K. Gladilin,111 C. Glasman,96 J. Glatzer,14 P. C. F. Glaysher,44 A. Glazov,44 M. Goblirsch-Kolb,26 J. Godlewski,82 S. Goldfarb,102 T. Golling,52 D. Golubkov,121 A. Gomes,137a,137b R. Goncalves Gama,51 R. Gonçalo,137a G. Gonella,50 L. Gonella,21 A. Gongadze,77 F. Gonnella,21 J. L. Gonski,57 S. González de la Hoz,171 S. Gonzalez-Sevilla,52 L. Goossens,35 P. A. Gorbounov,109 H. A. Gordon,29 B. Gorini,35 E. Gorini,65a,65b A. Gorišek,89 A. T. Goshaw,47 C. Gössling,45 M. I. Gostkin,77 C. A. Gottardo,24 C. R. Goudet,129 D. Goujdami,34c A. G. Goussiou,145 N. Govender,32b,w C. Goy,5 E. Gozani,157 I. Grabowska-Bold,81a P. O. J. Gradin,169 E. C. Graham,88 J. Gramling,168 E. Gramstad,131 S. Grancagnolo,19 V. Gratchev,135 P. M. Gravila,27f F. G. Gravili,65a,65b C. Gray,55 H. M. Gray,18 Z. D. Greenwood,93,x C. Grefe,24 K. Gregersen,94 I. M. Gregor,44 P. Grenier,150 K. Grevtsov,44 N. A. Grieser,125 J. Griffiths,8 A. A. Grillo,143 K. Grimm,150,y S. Grinstein,14,z Ph. Gris,37 J.-F. Grivaz,129 S. Groh,97 E. Gross,177 J. Grosse-Knetter,51 G. C. Grossi,93 Z. J. Grout,92 C. Grud,103 A. Grummer,116 L. Guan,103 W. Guan,178 J. Guenther,35 A. Guerguichon,129 F. Guescini,165a D. Guest,168 R. Gugel,50 B. Gui,123 T. Guillemin,5 S. Guindon,35 U. Gul,55 J. Guo,58c W. Guo,103 Y. Guo,58a,aa Z. Guo,99 R. Gupta,44 S. Gurbuz,12c G. Gustavino,125 P. Gutierrez,125 C. Gutschow,92 C. Guyot,142 M. P. Guzik,81a C. Gwenlan,132 C. B. Gwilliam,88 A. Haas,122 C. Haber,18 H. K. Hadavand,8 N. Haddad,34e A. Hadef,58a S. Hageböck,24 M. Hagihara,166 M. Haleem,174 J. Haley,126 G. Halladjian,104 G. D. Hallewell,99 K. Hamacher,179 P. Hamal,127 K. Hamano,173 A. Hamilton,32a G. N. Hamity,146 K. Han,58a,bb L. Han,58a S. Han,15d K. Hanagaki,79,cc M. Hance,143 D. M. Handl,112 B. Haney,134 R. Hankache,133 P. Hanke,59a E. Hansen,94 J. B. Hansen,39 J. D. Hansen,39 M. C. Hansen,24 P. H. Hansen,39 E. C. Hanson,98 K. Hara,166 A. S. Hard,178 T. Harenberg,179 S. Harkusha,105 P. F. Harrison,175 N. M. Hartmann,112 Y. Hasegawa,147 A. Hasib,48 S. Hassani,142 S. Haug,20 R. Hauser,104 L. Hauswald,46 L. B. Havener,38 M. Havranek,139 C. M. Hawkes,21 R. J. Hawkings,35 D. Hayden,104 C. Hayes,152 C. P. Hays,132 J. M. Hays,90 H. S. Hayward,88 S. J. Haywood,141 F. He,58a M. P. Heath,48 V. Hedberg,94 L. Heelan,8 S. Heer,24 K. K. Heidegger,50 J. Heilman,33 S. Heim,44 T. Heim,18 B. Heinemann,44,dd J. J. Heinrich,112 L. Heinrich,122 C. Heinz,54 J. Hejbal,138 L. Helary,35 A. Held,172 S. Hellesund,131 C. M. Helling,143 S. Hellman,43a,43b C. Helsens,35 R. C. W. Henderson,87 Y. Heng,178 S. Henkelmann,172 A. M. Henriques Correia,35 G. H. Herbert,19 H. Herde,26 V. Herget,174 Y. Hernández Jiménez,32c H. Herr,97 M. G. Herrmann,112 T. Herrmann,46 G. Herten,50 R. Hertenberger,112 L. Hervas,35 T. C. Herwig,134 G. G. Hesketh,92 N. P. Hessey,165a A. Higashida,160 S. Higashino,79 E. Higón-Rodriguez,171 K. Hildebrand,36 E. Hill,173 J. C. Hill,31 K. K. Hill,29 K. H. Hiller,44 S. J. Hillier,21 M. Hils,46 I. Hinchliffe,18 F. Hinterkeuser,24 M. Hirose,130 D. Hirschbuehl,179 B. Hiti,89 O. Hladik,138 D. R. Hlaluku,32c X. Hoad,48 J. Hobbs,152 N. Hod,165a M. C. Hodgkinson,146 A. Hoecker,35 M. R. Hoeferkamp,116 F. Hoenig,112 D. Hohn,50 D. Hohov,129 T. R. Holmes,36 M. Holzbock,112 M. Homann,45 B. H. Hommels,31 S. Honda,166 T. Honda,79 T. M. Hong,136 A. Hönle,113 B. H. Hooberman,170 W. H. Hopkins,128 Y. Horii,115 P. Horn,46 A. J. Horton,149 L. A. Horyn,36 J-Y. Hostachy,56 A. Hostiuc,145 S. Hou,155 A. Hoummada,34a J. Howarth,98 J. Hoya,86 M. Hrabovsky,127 J. Hrdinka,35 I. Hristova,19 J. Hrivnac,129 A. Hrynevich,106 T. Hryn’ova,5 P. J. Hsu,62 S.-C. Hsu,145 Q. Hu,29 S. Hu,58c Y. Huang,15a Z. Hubacek,139 F. Hubaut,99 M. Huebner,24 F. Huegging,24 T. B. Huffman,132 M. Huhtinen,35 R. F. H. Hunter,33 P. Huo,152 A. M. Hupe,33 N. Huseynov,77,e J. Huston,104 J. Huth,57 R. Hyneman,103 G. Iacobucci,52 G. Iakovidis,29 I. Ibragimov,148 L. Iconomidou-Fayard,129 Z. Idrissi,34e P. Iengo,35 R. Ignazzi,39 O. Igonkina,118,ee R. Iguchi,160 T. Iizawa,52 Y. Ikegami,79 092007-23 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) M. Ikeno,79 D. Iliadis,159 N. Ilic,117 F. Iltzsche,46 G. Introzzi,68a,68b M. Iodice,72a K. Iordanidou,38 V. Ippolito,70a,70b M. F. Isacson,169 N. Ishijima,130 M. Ishino,160 M. Ishitsuka,162 W. Islam,126 C. Issever,132 S. Istin,157 F. Ito,166 J. M. Iturbe Ponce,61a R. Iuppa,73a,73b A. Ivina,177 H. Iwasaki,79 J. M. Izen,42 V. Izzo,67a P. Jacka,138 P. Jackson,1 R. M. Jacobs,24 V. Jain,2 G. Jäkel,179 K. B. Jakobi,97 K. Jakobs,50 S. Jakobsen,74 T. Jakoubek,138 D. O. Jamin,126 R. Jansky,52 J. Janssen,24 M. Janus,51 P. A. Janus,81a G. Jarlskog,94 N. Javadov,77,e T. Javůrek,35 M. Javurkova,50 F. Jeanneau,142 L. Jeanty,18 J. Jejelava,156a,ff A. Jelinskas,175 P. Jenni,50,gg J. Jeong,44 N. Jeong,44 S. Jézéquel,5 H. Ji,178 J. Jia,152 H. Jiang,76 Y. Jiang,58a Z. Jiang,150,hh S. Jiggins,50 F. A. Jimenez Morales,37 J. Jimenez Pena,171 S. Jin,15c A. Jinaru,27b O. Jinnouchi,162 H. Jivan,32c P. Johansson,146 K. A. Johns,7 C. A. Johnson,63 K. Jon-And,43a,43b R. W. L. Jones,87 S. D. Jones,153 S. Jones,7 T. J. Jones,88 J. Jongmanns,59a P. M. Jorge,137a,137b J. Jovicevic,165a X. Ju,18 J. J. Junggeburth,113 A. Juste Rozas,14,z A. Kaczmarska,82 M. Kado,129 H. Kagan,123 M. Kagan,150 T. Kaji,176 E. Kajomovitz,157 C. W. Kalderon,94 A. Kaluza,97 S. Kama,41 A. Kamenshchikov,121 L. Kanjir,89 Y. Kano,160 V. A. Kantserov,110 J. Kanzaki,79 L. S. Kaplan,178 D. Kar,32c M. J. Kareem,165b E. Karentzos,10 S. N. Karpov,77 Z. M. Karpova,77 V. Kartvelishvili,87 A. N. Karyukhin,121 L. Kashif,178 R. D. Kass,123 A. Kastanas,43a,43b Y. Kataoka,160 C. Kato,58d,58c J. Katzy,44 K. Kawade,80 K. Kawagoe,85 T. Kawaguchi,115 T. Kawamoto,160 G. Kawamura,51 E. F. Kay,88 V. F. Kazanin,120b,120a R. Keeler,173 R. Kehoe,41 J. S. Keller,33 E. Kellermann,94 J. J. Kempster,21 J. Kendrick,21 O. Kepka,138 S. Kersten,179 B. P. Kerševan,89 S. Ketabchi Haghighat,164 R. A. Keyes,101 M. Khader,170 F. Khalil-Zada,13 A. Khanov,126 A. G. Kharlamov,120b,120a T. Kharlamova,120b,120a E. E. Khoda,172 A. Khodinov,163 T. J. Khoo,52 E. Khramov,77 J. Khubua,156b S. Kido,80 M. Kiehn,52 C. R. Kilby,91 Y. K. Kim,36 N. Kimura,64a,64c O. M. Kind,19 B. T. King,88 D. Kirchmeier,46 J. Kirk,141 A. E. Kiryunin,113 T. Kishimoto,160 D. Kisielewska,81a V. Kitali,44 O. Kivernyk,5 E. Kladiva,28b,a T. Klapdor-Kleingrothaus,50 M. H. Klein,103 M. Klein,88 U. Klein,88 K. Kleinknecht,97 P. Klimek,119 A. Klimentov,29 T. Klingl,24 T. Klioutchnikova,35 F. F. Klitzner,112 P. Kluit,118 S. Kluth,113 E. Kneringer,74 E. B. F. G. Knoops,99 A. Knue,50 A. Kobayashi,160 D. Kobayashi,85 T. Kobayashi,160 M. Kobel,46 M. Kocian,150 P. Kodys,140 P. T. Koenig,24 T. Koffas,33 E. Koffeman,118 N. M. Köhler,113 T. Koi,150 M. Kolb,59b I. Koletsou,5 T. Kondo,79 N. Kondrashova,58c K. Köneke,50 A. C. König,117 T. Kono,79 R. Konoplich,122,ii V. Konstantinides,92 N. Konstantinidis,92 B. Konya,94 R. Kopeliansky,63 S. Koperny,81a K. Korcyl,82 K. Kordas,159 G. Koren,158 A. Korn,92 I. Korolkov,14 E. V. Korolkova,146 N. Korotkova,111 O. Kortner,113 S. Kortner,113 T. Kosek,140 V. V. Kostyukhin,24 A. Kotwal,47 A. Koulouris,10 A. Kourkoumeli-Charalampidi,68a,68b C. Kourkoumelis,9 E. Kourlitis,146 V. Kouskoura,29 A. B. Kowalewska,82 R. Kowalewski,173 T. Z. Kowalski,81a C. Kozakai,160 W. Kozanecki,142 A. S. Kozhin,121 V. A. Kramarenko,111 G. Kramberger,89 D. Krasnopevtsev,58a M. W. Krasny,133 A. Krasznahorkay,35 D. Krauss,113 J. A. Kremer,81a J. Kretzschmar,88 P. Krieger,164 K. Krizka,18 K. Kroeninger,45 H. Kroha,113 J. Kroll,138 J. Kroll,134 J. Krstic,16 U. Kruchonak,77 H. Krüger,24 N. Krumnack,76 M. C. Kruse,47 T. Kubota,102 S. Kuday,4b J. T. Kuechler,179 S. Kuehn,35 A. Kugel,59a T. Kuhl,44 V. Kukhtin,77 R. Kukla,99 Y. Kulchitsky,105,jj S. Kuleshov,144b Y. P. Kulinich,170 M. Kuna,56 T. Kunigo,83 A. Kupco,138 T. Kupfer,45 O. Kuprash,158 H. Kurashige,80 L. L. Kurchaninov,165a Y. A. Kurochkin,105 A. Kurova,110 M. G. Kurth,15d E. S. Kuwertz,35 M. Kuze,162 J. Kvita,127 T. Kwan,101 A. La Rosa,113 J. L. La Rosa Navarro,78d L. La Rotonda,40b,40a F. La Ruffa,40b,40a C. Lacasta,171 F. Lacava,70a,70b J. Lacey,44 D. P. J. Lack,98 H. Lacker,19 D. Lacour,133 E. Ladygin,77 R. Lafaye,5 B. Laforge,133 T. Lagouri,32c S. Lai,51 S. Lammers,63 W. Lampl,7 E. Lançon,29 U. Landgraf,50 M. P. J. Landon,90 M. C. Lanfermann,52 V. S. Lang,44 J. C. Lange,51 R. J. Langenberg,35 A. J. Lankford,168 F. Lanni,29 K. Lantzsch,24 A. Lanza,68a A. Lapertosa,53b,53a S. Laplace,133 J. F. Laporte,142 T. Lari,66a F. Lasagni Manghi,23b,23a M. Lassnig,35 T. S. Lau,61a A. Laudrain,129 M. Lavorgna,67a,67b M. Lazzaroni,66a,66b B. Le,102 O. Le Dortz,133 E. Le Guirriec,99 E. P. Le Quilleuc,142 M. LeBlanc,7 T. LeCompte,6 F. Ledroit-Guillon,56 C. A. Lee,29 G. R. Lee,144a L. Lee,57 S. C. Lee,155 B. Lefebvre,101 M. Lefebvre,173 F. Legger,112 C. Leggett,18 K. Lehmann,149 N. Lehmann,179 G. Lehmann Miotto,35 W. A. Leight,44 A. Leisos,159,kk M. A. L. Leite,78d R. Leitner,140 D. Lellouch,177 K. J. C. Leney,92 T. Lenz,24 B. Lenzi,35 R. Leone,7 S. Leone,69a C. Leonidopoulos,48 G. Lerner,153 C. Leroy,107 R. Les,164 A. A. J. Lesage,142 C. G. Lester,31 M. Levchenko,135 J. Levêque,5 D. Levin,103 L. J. Levinson,177 D. Lewis,90 B. Li,15b B. Li,103 C-Q. Li,58a,ll H. Li,58a H. Li,58b K. Li,150 L. Li,58c M. Li,15a Q. Li,15d Q. Y. Li,58a S. Li,58d,58c X. Li,58c Y. Li,148 Z. Liang,15a B. Liberti,71a A. Liblong,164 K. Lie,61c S. Liem,118 A. Limosani,154 C. Y. Lin,31 K. Lin,104 T. H. Lin,97 R. A. Linck,63 J. H. Lindon,21 B. E. Lindquist,152 A. L. Lionti,52 E. Lipeles,134 A. Lipniacka,17 M. Lisovyi,59b T. M. Liss,170,mm A. Lister,172 A. M. Litke,143 J. D. Little,8 B. Liu,76 B. L Liu,6 H. B. Liu,29 H. Liu,103 J. B. Liu,58a J. K. K. Liu,132 K. Liu,133 M. Liu,58a P. Liu,18 Y. Liu,15a Y. L. Liu,58a Y. W. Liu,58a M. Livan,68a,68b A. Lleres,56 J. Llorente Merino,15a S. L. Lloyd,90 C. Y. Lo,61b F. Lo Sterzo,41 E. M. Lobodzinska,44 P. Loch,7 T. Lohse,19 092007-24 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) K. Lohwasser,146 M. Lokajicek,138 J. D. Long,170 R. E. Long,87 L. Longo,65a,65b K. A. Looper,123 J. A. Lopez,144b I. Lopez Paz,98 A. Lopez Solis,146 J. Lorenz,112 N. Lorenzo Martinez,5 M. Losada,22 P. J. Lösel,112 A. Lösle,50 X. Lou,44 X. Lou,15a A. Lounis,129 J. Love,6 P. A. Love,87 J. J. Lozano Bahilo,171 H. Lu,61a M. Lu,58a Y. J. Lu,62 H. J. Lubatti,145 C. Luci,70a,70b A. Lucotte,56 C. Luedtke,50 F. Luehring,63 I. Luise,133 L. Luminari,70a B. Lund-Jensen,151 M. S. Lutz,100 P. M. Luzi,133 D. Lynn,29 R. Lysak,138 E. Lytken,94 F. Lyu,15a V. Lyubushkin,77 T. Lyubushkina,77 H. Ma,29 L. L. Ma,58b Y. Ma,58b G. Maccarrone,49 A. Macchiolo,113 C. M. Macdonald,146 J. Machado Miguens,134,137b D. Madaffari,171 R. Madar,37 W. F. Mader,46 N. Madysa,46 J. Maeda,80 K. Maekawa,160 S. Maeland,17 T. Maeno,29 M. Maerker,46 A. S. Maevskiy,111 V. Magerl,50 D. J. Mahon,38 C. Maidantchik,78b T. Maier,112 A. Maio,137a,137b,137d O. Majersky,28a S. Majewski,128 Y. Makida,79 N. Makovec,129 B. Malaescu,133 Pa. Malecki,82 V. P. Maleev,135 F. Malek,56 U. Mallik,75 D. Malon,6 C. Malone,31 S. Maltezos,10 S. Malyukov,35 J. Mamuzic,171 G. Mancini,49 I. Mandić,89 J. Maneira,137a L. Manhaes de Andrade Filho,78a J. Manjarres Ramos,46 K. H. Mankinen,94 A. Mann,112 A. Manousos,74 B. Mansoulie,142 S. Manzoni,66a,66b A. Marantis,159 G. Marceca,30 L. March,52 L. Marchese,132 G. Marchiori,133 M. Marcisovsky,138 C. Marcon,94 C. A. Marin Tobon,35 M. Marjanovic,37 F. Marroquim,78b Z. Marshall,18 M. U. F Martensson,169 S. Marti-Garcia,171 C. B. Martin,123 T. A. Martin,175 V. J. Martin,48 B. Martin dit Latour,17 M. Martinez,14,z V. I. Martinez Outschoorn,100 S. Martin-Haugh,141 V. S. Martoiu,27b A. C. Martyniuk,92 A. Marzin,35 L. Masetti,97 T. Mashimo,160 R. Mashinistov,108 J. Masik,98 A. L. Maslennikov,120b,120a L. H. Mason,102 L. Massa,71a,71b P. Massarotti,67a,67b P. Mastrandrea,152 A. Mastroberardino,40b,40a T. Masubuchi,160 P. Mättig,24 J. Maurer,27b B. Maček,89 S. J. Maxfield,88 D. A. Maximov,120b,120a R. Mazini,155 I. Maznas,159 S. M. Mazza,143 S. P. Mc Kee,103 A. McCarn,41 T. G. McCarthy,113 L. I. McClymont,92 W. P. McCormack,18 E. F. McDonald,102 J. A. Mcfayden,35 G. Mchedlidze,51 M. A. McKay,41 K. D. McLean,173 S. J. McMahon,141 P. C. McNamara,102 C. J. McNicol,175 R. A. McPherson,173,o J. E. Mdhluli,32c Z. A. Meadows,100 S. Meehan,145 T. M. Megy,50 S. Mehlhase,112 A. Mehta,88 T. Meideck,56 B. Meirose,42 D. Melini,171,nn B. R. Mellado Garcia,32c J. D. Mellenthin,51 M. Melo,28a F. Meloni,44 A. Melzer,24 S. B. Menary,98 E. D. Mendes Gouveia,137a L. Meng,88 X. T. Meng,103 S. Menke,113 E. Meoni,40b,40a S. Mergelmeyer,19 S. A. M. Merkt,136 C. Merlassino,20 P. Mermod,52 L. Merola,67a,67b C. Meroni,66a F. S. Merritt,36 A. Messina,70a,70b J. Metcalfe,6 A. S. Mete,168 C. Meyer,63 J. Meyer,157 J-P. Meyer,142 H. Meyer Zu Theenhausen,59a F. Miano,153 R. P. Middleton,141 L. Mijović,48 G. Mikenberg,177 M. Mikestikova,138 M. Mikuž,89 M. Milesi,102 A. Milic,164 D. A. Millar,90 D. W. Miller,36 A. Milov,177 D. A. Milstead,43a,43b R. A. Mina,150,hh A. A. Minaenko,121 M. Miñano Moya,171 I. A. Minashvili,156b A. I. Mincer,122 B. Mindur,81a M. Mineev,77 Y. Minegishi,160 Y. Ming,178 L. M. Mir,14 A. Mirto,65a,65b K. P. Mistry,134 T. Mitani,176 J. Mitrevski,112 V. A. Mitsou,171 M. Mittal,58c A. Miucci,20 P. S. Miyagawa,146 A. Mizukami,79 J. U. Mjörnmark,94 T. Mkrtchyan,181 M. Mlynarikova,140 T. Moa,43a,43b K. Mochizuki,107 P. Mogg,50 S. Mohapatra,38 S. Molander,43a,43b R. Moles-Valls,24 M. C. Mondragon,104 K. Mönig,44 J. Monk,39 E. Monnier,99 A. Montalbano,149 J. Montejo Berlingen,35 F. Monticelli,86 S. Monzani,66a N. Morange,129 D. Moreno,22 M. Moreno Llácer,35 P. Morettini,53b M. Morgenstern,118 S. Morgenstern,46 D. Mori,149 M. Morii,57 M. Morinaga,176 V. Morisbak,131 A. K. Morley,35 G. Mornacchi,35 A. P. Morris,92 J. D. Morris,90 L. Morvaj,152 P. Moschovakos,10 M. Mosidze,156b H. J. Moss,146 J. Moss,150,oo K. Motohashi,162 R. Mount,150 E. Mountricha,35 E. J. W. Moyse,100 S. Muanza,99 F. Mueller,113 J. Mueller,136 R. S. P. Mueller,112 D. Muenstermann,87 G. A. Mullier,94 F. J. Munoz Sanchez,98 P. Murin,28b W. J. Murray,175,141 A. Murrone,66a,66b M. Muškinja,89 C. Mwewa,32a A. G. Myagkov,121,pp J. Myers,128 M. Myska,139 B. P. Nachman,18 O. Nackenhorst,45 K. Nagai,132 K. Nagano,79 Y. Nagasaka,60 M. Nagel,50 E. Nagy,99 A. M. Nairz,35 Y. Nakahama,115 K. Nakamura,79 T. Nakamura,160 I. Nakano,124 H. Nanjo,130 F. Napolitano,59a R. F. Naranjo Garcia,44 R. Narayan,11 D. I. Narrias Villar,59a I. Naryshkin,135 T. Naumann,44 G. Navarro,22 R. Nayyar,7 H. A. Neal,103,a P. Y. Nechaeva,108 T. J. Neep,142 A. Negri,68a,68b M. Negrini,23b S. Nektarijevic,117 C. Nellist,51 M. E. Nelson,132 S. Nemecek,138 P. Nemethy,122 M. Nessi,35,qq M. S. Neubauer,170 M. Neumann,179 P. R. Newman,21 T. Y. Ng,61c Y. S. Ng,19 Y. W. Y. Ng,168 H. D. N. Nguyen,99 T. Nguyen Manh,107 E. Nibigira,37 R. B. Nickerson,132 R. Nicolaidou,142 D. S. Nielsen,39 J. Nielsen,143 N. Nikiforou,11 V. Nikolaenko,121,pp I. Nikolic-Audit,133 K. Nikolopoulos,21 P. Nilsson,29 H. R. Nindhito,52 Y. Ninomiya,79 A. Nisati,70a N. Nishu,58c R. Nisius,113 I. Nitsche,45 T. Nitta,176 T. Nobe,160 Y. Noguchi,83 M. Nomachi,130 I. Nomidis,133 M. A. Nomura,29 T. Nooney,90 M. Nordberg,35 N. Norjoharuddeen,132 T. Novak,89 O. Novgorodova,46 R. Novotny,139 L. Nozka,127 K. Ntekas,168 E. Nurse,92 F. Nuti,102 F. G. Oakham,33,f H. Oberlack,113 J. Ocariz,133 A. Ochi,80 I. Ochoa,38 J. P. Ochoa-Ricoux,144a K. O’Connor,26 S. Oda,85 S. Odaka,79 S. Oerdek,51 A. Oh,98 S. H. Oh,47 C. C. Ohm,151 H. Oide,53b,53a M. L. Ojeda,164 H. Okawa,166 Y. Okazaki,83 Y. Okumura,160 T. Okuyama,79 A. Olariu,27b L. F. Oleiro Seabra,137a S. A. Olivares Pino,144a D. Oliveira Damazio,29 092007-25 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) J. L. Oliver,1 M. J. R. Olsson,36 A. Olszewski,82 J. Olszowska,82 D. C. O’Neil,149 A. Onofre,137a,137e K. Onogi,115 P. U. E. Onyisi,11 H. Oppen,131 M. J. Oreglia,36 G. E. Orellana,86 Y. Oren,158 D. Orestano,72a,72b N. Orlando,61b A. A. O’Rourke,44 R. S. Orr,164 B. Osculati,53b,53a,a V. O’Shea,55 R. Ospanov,58a G. Otero y Garzon,30 H. Otono,85 M. Ouchrif,34d F. Ould-Saada,131 A. Ouraou,142 Q. Ouyang,15a M. Owen,55 R. E. Owen,21 V. E. Ozcan,12c N. Ozturk,8 J. Pacalt,127 H. A. Pacey,31 K. Pachal,149 A. Pacheco Pages,14 L. Pacheco Rodriguez,142 C. Padilla Aranda,14 S. Pagan Griso,18 M. Paganini,180 G. Palacino,63 S. Palazzo,48 S. Palestini,35 M. Palka,81b D. Pallin,37 I. Panagoulias,10 C. E. Pandini,35 J. G. Panduro Vazquez,91 P. Pani,35 G. Panizzo,64a,64c L. Paolozzi,52 T. D. Papadopoulou,10 K. Papageorgiou,9,v A. Paramonov,6 D. Paredes Hernandez,61b S. R. Paredes Saenz,132 B. Parida,163 T. H. Park,33 A. J. Parker,87 K. A. Parker,44 M. A. Parker,31 F. Parodi,53b,53a J. A. Parsons,38 U. Parzefall,50 V. R. Pascuzzi,164 J. M. P. Pasner,143 E. Pasqualucci,70a S. Passaggio,53b F. Pastore,91 P. Pasuwan,43a,43b S. Pataraia,97 J. R. Pater,98 A. Pathak,178,g T. Pauly,35 B. Pearson,113 M. Pedersen,131 L. Pedraza Diaz,117 R. Pedro,137a,137b S. V. Peleganchuk,120b,120a O. Penc,138 C. Peng,15d H. Peng,58a B. S. Peralva,78a M. M. Perego,129 A. P. Pereira Peixoto,137a D. V. Perepelitsa,29 F. Peri,19 L. Perini,66a,66b H. Pernegger,35 S. Perrella,67a,67b V. D. Peshekhonov,77,a K. Peters,44 R. F. Y. Peters,98 B. A. Petersen,35 T. C. Petersen,39 E. Petit,56 A. Petridis,1 C. Petridou,159 P. Petroff,129 M. Petrov,132 F. Petrucci,72a,72b M. Pettee,180 N. E. Pettersson,100 A. Peyaud,142 R. Pezoa,144b T. Pham,102 F. H. Phillips,104 P. W. Phillips,141 M. W. Phipps,170 G. Piacquadio,152 E. Pianori,18 A. Picazio,100 R. H. Pickles,98 R. Piegaia,30 J. E. Pilcher,36 A. D. Pilkington,98 M. Pinamonti,71a,71b J. L. Pinfold,3 M. Pitt,177 L. Pizzimento,71a,71b M.-A. Pleier,29 V. Pleskot,140 E. Plotnikova,77 D. Pluth,76 P. Podberezko,120b,120a R. Poettgen,94 R. Poggi,52 L. Poggioli,129 I. Pogrebnyak,104 D. Pohl,24 I. Pokharel,51 G. Polesello,68a A. Poley,18 A. Policicchio,70a,70b R. Polifka,35 A. Polini,23b C. S. Pollard,44 V. Polychronakos,29 D. Ponomarenko,110 L. Pontecorvo,35 G. A. Popeneciu,27d D. M. Portillo Quintero,133 S. Pospisil,139 K. Potamianos,44 I. N. Potrap,77 C. J. Potter,31 H. Potti,11 T. Poulsen,94 J. Poveda,35 T. D. Powell,146 M. E. Pozo Astigarraga,35 P. Pralavorio,99 S. Prell,76 D. Price,98 M. Primavera,65a S. Prince,101 M. L. Proffitt,145 N. Proklova,110 K. Prokofiev,61c F. Prokoshin,144b S. Protopopescu,29 J. Proudfoot,6 M. Przybycien,81a A. Puri,170 P. Puzo,129 J. Qian,103 Y. Qin,98 A. Quadt,51 M. Queitsch-Maitland,44 A. Qureshi,1 P. Rados,102 F. Ragusa,66a,66b G. Rahal,95 J. A. Raine,52 S. Rajagopalan,29 A. Ramirez Morales,90 K. Ran,15a T. Rashid,129 S. Raspopov,5 M. G. Ratti,66a,66b D. M. Rauch,44 F. Rauscher,112 S. Rave,97 B. Ravina,146 I. Ravinovich,177 J. H. Rawling,98 M. Raymond,35 A. L. Read,131 N. P. Readioff,56 M. Reale,65a,65b D. M. Rebuzzi,68a,68b A. Redelbach,174 G. Redlinger,29 R. Reece,143 R. G. Reed,32c K. Reeves,42 L. Rehnisch,19 J. Reichert,134 D. Reikher,158 A. Reiss,97 A. Rej,148 C. Rembser,35 H. Ren,15d M. Rescigno,70a S. Resconi,66a E. D. Resseguie,134 S. Rettie,172 E. Reynolds,21 O. L. Rezanova,120b,120a P. Reznicek,140 E. Ricci,73a,73b R. Richter,113 S. Richter,44 E. Richter-Was,81b O. Ricken,24 M. Ridel,133 P. Rieck,113 C. J. Riegel,179 O. Rifki,44 M. Rijssenbeek,152 A. Rimoldi,68a,68b M. Rimoldi,20 L. Rinaldi,23b G. Ripellino,151 B. Ristić,87 E. Ritsch,35 I. Riu,14 J. C. Rivera Vergara,144a F. Rizatdinova,126 E. Rizvi,90 C. Rizzi,14 R. T. Roberts,98 S. H. Robertson,101,o D. Robinson,31 J. E. M. Robinson,44 A. Robson,55 E. Rocco,97 C. Roda,69a,69b Y. Rodina,99 S. Rodriguez Bosca,171 A. Rodriguez Perez,14 D. Rodriguez Rodriguez,171 A. M. Rodríguez Vera,165b S. Roe,35 C. S. Rogan,57 O. Røhne,131 R. Röhrig,113 C. P. A. Roland,63 J. Roloff,57 A. Romaniouk,110 M. Romano,23b,23a N. Rompotis,88 M. Ronzani,122 L. Roos,133 S. Rosati,70a K. Rosbach,50 N-A. Rosien,51 B. J. Rosser,134 E. Rossi,44 E. Rossi,72a,72b E. Rossi,67a,67b L. P. Rossi,53b L. Rossini,66a,66b J. H. N. Rosten,31 R. Rosten,14 M. Rotaru,27b J. Rothberg,145 D. Rousseau,129 D. Roy,32c A. Rozanov,99 Y. Rozen,157 X. Ruan,32c F. Rubbo,150 F. Rühr,50 A. Ruiz-Martinez,171 Z. Rurikova,50 N. A. Rusakovich,77 H. L. Russell,101 J. P. Rutherfoord,7 E. M. Rüttinger,44,rr Y. F. Ryabov,135 M. Rybar,38 G. Rybkin,129 S. Ryu,6 A. Ryzhov,121 G. F. Rzehorz,51 P. Sabatini,51 G. Sabato,118 S. Sacerdoti,129 H. F-W. Sadrozinski,143 R. Sadykov,77 F. Safai Tehrani,70a P. Saha,119 M. Sahinsoy,59a A. Sahu,179 M. Saimpert,44 M. Saito,160 T. Saito,160 H. Sakamoto,160 A. Sakharov,122,ii D. Salamani,52 G. Salamanna,72a,72b J. E. Salazar Loyola,144b P. H. Sales De Bruin,169 D. Salihagic,113,a A. Salnikov,150 J. Salt,171 D. Salvatore,40b,40a F. Salvatore,153 A. Salvucci,61a,61b,61c A. Salzburger,35 J. Samarati,35 D. Sammel,50 D. Sampsonidis,159 D. Sampsonidou,159 J. Sánchez,171 A. Sanchez Pineda,64a,64c H. Sandaker,131 C. O. Sander,44 M. Sandhoff,179 C. Sandoval,22 D. P. C. Sankey,141 M. Sannino,53b,53a Y. Sano,115 A. Sansoni,49 C. Santoni,37 H. Santos,137a I. Santoyo Castillo,153 A. Santra,171 A. Sapronov,77 J. G. Saraiva,137a,137d O. Sasaki,79 K. Sato,166 E. Sauvan,5 P. Savard,164,f N. Savic,113 R. Sawada,160 C. Sawyer,141 L. Sawyer,93,x C. Sbarra,23b A. Sbrizzi,23a T. Scanlon,92 J. Schaarschmidt,145 P. Schacht,113 B. M. Schachtner,112 D. Schaefer,36 L. Schaefer,134 J. Schaeffer,97 S. Schaepe,35 U. Schäfer,97 A. C. Schaffer,129 D. Schaile,112 R. D. Schamberger,152 N. Scharmberg,98 V. A. Schegelsky,135 D. Scheirich,140 F. Schenck,19 M. Schernau,168 092007-26 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) C. Schiavi,53b,53a S. Schier,143 L. K. Schildgen,24 Z. M. Schillaci,26 E. J. Schioppa,35 M. Schioppa,40b,40a K. E. Schleicher,50 S. Schlenker,35 K. R. Schmidt-Sommerfeld,113 K. Schmieden,35 C. Schmitt,97 S. Schmitt,44 S. Schmitz,97 J. C. Schmoeckel,44 U. Schnoor,50 L. Schoeffel,142 A. Schoening,59b E. Schopf,132 M. Schott,97 J. F. P. Schouwenberg,117 J. Schovancova,35 S. Schramm,52 A. Schulte,97 H-C. Schultz-Coulon,59a M. Schumacher,50 B. A. Schumm,143 Ph. Schune,142 A. Schwartzman,150 T. A. Schwarz,103 Ph. Schwemling,142 R. Schwienhorst,104 A. Sciandra,24 G. Sciolla,26 M. Scornajenghi,40b,40a F. Scuri,69a F. Scutti,102 L. M. Scyboz,113 C. D. Sebastiani,70a,70b P. Seema,19 S. C. Seidel,116 A. Seiden,143 T. Seiss,36 J. M. Seixas,78b G. Sekhniaidze,67a K. Sekhon,103 S. J. Sekula,41 N. Semprini-Cesari,23b,23a S. Sen,47 S. Senkin,37 C. Serfon,131 L. Serin,129 L. Serkin,64a,64b M. Sessa,58a H. Severini,125 F. Sforza,167 A. Sfyrla,52 E. Shabalina,51 J. D. Shahinian,143 N. W. Shaikh,43a,43b D. Shaked Renous,177 L. Y. Shan,15a R. Shang,170 J. T. Shank,25 M. Shapiro,18 A. S. Sharma,1 A. Sharma,132 P. B. Shatalov,109 K. Shaw,153 S. M. Shaw,98 A. Shcherbakova,135 Y. Shen,125 N. Sherafati,33 A. D. Sherman,25 P. Sherwood,92 L. Shi,155,ss S. Shimizu,79 C. O. Shimmin,180 Y. Shimogama,176 M. Shimojima,114 I. P. J. Shipsey,132 S. Shirabe,85 M. Shiyakova,77 J. Shlomi,177 A. Shmeleva,108 D. Shoaleh Saadi,107 M. J. Shochet,36 S. Shojaii,102 D. R. Shope,125 S. Shrestha,123 E. Shulga,110 P. Sicho,138 A. M. Sickles,170 P. E. Sidebo,151 E. Sideras Haddad,32c O. Sidiropoulou,35 A. Sidoti,23b,23a F. Siegert,46 Dj. Sijacki,16 J. Silva,137a M. Silva Jr.,178 M. V. Silva Oliveira,78a S. B. Silverstein,43a S. Simion,129 E. Simioni,97 M. Simon,97 R. Simoniello,97 P. Sinervo,164 N. B. Sinev,128 M. Sioli,23b,23a I. Siral,103 S. Yu. Sivoklokov,111 J. Sjölin,43a,43b P. Skubic,125 M. Slater,21 T. Slavicek,139 M. Slawinska,82 K. Sliwa,167 R. Slovak,140 V. Smakhtin,177 B. H. Smart,5 J. Smiesko,28a N. Smirnov,110 S. Yu. Smirnov,110 Y. Smirnov,110 L. N. Smirnova,111 O. Smirnova,94 J. W. Smith,51 M. Smizanska,87 K. Smolek,139 A. Smykiewicz,82 A. A. Snesarev,108 I. M. Snyder,128 S. Snyder,29 R. Sobie,173,o A. M. Soffa,168 A. Soffer,158 A. Søgaard,48 F. Sohns,51 G. Sokhrannyi,89 C. A. Solans Sanchez,35 M. Solar,139 E. Yu. Soldatov,110 U. Soldevila,171 A. A. Solodkov,121 A. Soloshenko,77 O. V. Solovyanov,121 V. Solovyev,135 P. Sommer,146 H. Son,167 W. Song,141 W. Y. Song,165b A. Sopczak,139 F. Sopkova,28b C. L. Sotiropoulou,69a,69b S. Sottocornola,68a,68b R. Soualah,64a,64c,tt A. M. Soukharev,120b,120a D. 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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, Genova, Italy 54 II. Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 55 SUPA—School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 56 LPSC, Université Grenoble Alpes, CNRS/IN2P3, Grenoble INP, Grenoble, France 57 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, Massachusetts, USA 58a Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics, University of Science and Technology of China, Hefei, China 58b Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao, China 58c School of Physics and Astronomy, Shanghai Jiao Tong University, KLPPAC-MoE, SKLPPC, Shanghai, China 58d Tsung-Dao Lee Institute, Shanghai, China 59a Kirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 59b Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 60 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 61a Department of Physics, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China 61b Department of Physics, University of Hong Kong, Hong Kong, China 61c Department of Physics and Institute for Advanced Study, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China 62 Department of Physics, National Tsing Hua University, Hsinchu, Taiwan 63 Department of Physics, Indiana University, Bloomington, Indiana, USA 64a INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine, Italy 64b ICTP, Trieste, Italy 64c Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Udine, Italy 65a INFN Sezione di Lecce, Lecce, Italy 65b Dipartimento di Matematica e Fisica, Università del Salento, Lecce, Italy 66a INFN Sezione di Milano, Milano, Italy 66b Dipartimento di Fisica, Università di Milano, Milano, Italy 67a INFN Sezione di Napoli, Napoli, Italy 67b Dipartimento di Fisica, Università di Napoli, Napoli, Italy 68a INFN Sezione di Pavia, Pavia, Italy 68b Dipartimento di Fisica, Università di Pavia, Pavia, Italy 69a INFN Sezione di Pisa, Pisa, Italy 69b Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 70a INFN Sezione di Roma, Roma, Italy 70b Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy 71a INFN Sezione di Roma Tor Vergata, Roma, Italy 71b Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy 72a INFN Sezione di Roma Tre, Roma, Italy 72b Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy 73a INFN-TIFPA, Trento, 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 092007-30 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) 76 Department of Physics and Astronomy, Iowa State University, Ames, Iowa, USA 77 Joint Institute for Nuclear Research, Dubna, Russia 78a Departamento de Engenharia Elétrica, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, Brazil 78b Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro, Brazil 78c Universidade Federal de São João del Rei (UFSJ), São João del Rei, Brazil 78d Instituto de Física, Universidade de São Paulo, São Paulo, Brazil 79 KEK, High Energy Accelerator Research Organization, Tsukuba, Japan 80 Graduate School of Science, Kobe University, Kobe, Japan 81a AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, Krakow, Poland 81b Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland 82 Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland 83 Faculty of Science, Kyoto University, Kyoto, Japan 84 Kyoto University of Education, Kyoto, Japan 85 Research Center for Advanced Particle Physics and Department of Physics, Kyushu University, Fukuoka, Japan 86 Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina 87 Physics Department, Lancaster University, Lancaster, United Kingdom 88 Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom 89 Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics, University of Ljubljana, Ljubljana, Slovenia 90 School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom 91 Department of Physics, Royal Holloway University of London, Egham, United Kingdom 92 Department of Physics and Astronomy, University College London, London, United Kingdom 93 Louisiana Tech University, Ruston, 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, Québec, 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, Québec, Canada 108 P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 109 Institute for Theoretical and Experimental Physics of the National Research Centre Kurchatov Institute, 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 and NSU, SB RAS, Novosibirsk, Russia 120b Novosibirsk State University Novosibirsk, Novosibirsk, Russia 121 Institute for High Energy Physics of the National Research Centre Kurchatov Institute, Protvino, Russia 122 Department of Physics, New York University, New York, New York, USA 092007-31 M. 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Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, Oklahoma, USA 126 Department of Physics, Oklahoma State University, Stillwater, Oklahoma, USA 127 Palacký University, RCPTM, Joint Laboratory of Optics, Olomouc, Czech Republic 128 Center for High Energy Physics, University of Oregon, Eugene, Oregon, USA 129 LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France 130 Graduate School of Science, Osaka University, Osaka, Japan 131 Department of Physics, University of Oslo, Oslo, Norway 132 Department of Physics, Oxford University, Oxford, United Kingdom 133 LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France 134 Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania, USA 135 Konstantinov Nuclear Physics Institute of National Research Centre “Kurchatov Institute”, PNPI, St. Petersburg, Russia 136 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA 137a Laboratório de Instrumentação e Física Experimental de Partículas—LIP, Portugal 137b Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal 137c Departamento de Física, Universidade de Coimbra, Coimbra, Portugal 137d Centro de Física Nuclear da Universidade de Lisboa, Lisboa, Portugal 137e Departamento de Física, Universidade do Minho, Braga, Portugal 137f Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain 137g Dep Física and CEFITEC of Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 138 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic 139 Czech Technical University in Prague, Prague, Czech Republic 140 Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic 141 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 142 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France 143 Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz, California, USA 144a Departamento de Física, Pontificia Universidad Católica de Chile, Santiago, Chile 144b Departamento de Física, Universidad Técnica Federico Santa María, Valparaíso, Chile 145 Department of Physics, University of Washington, Seattle, Washington, USA 146 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom 147 Department of Physics, Shinshu University, Nagano, Japan 148 Department Physik, Universität Siegen, Siegen, Germany 149 Department of Physics, Simon Fraser University, Burnaby, 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 092007-32 SEARCH FOR HEAVY CHARGED LONG-LIVED PARTICLES … PHYS. REV. D 99, 092007 (2019) 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 Instituto de Física Teórica de la Universidad Autónoma de Madrid, Spain. e Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan. f Also at TRIUMF, Vancouver, British Columbia, Canada. g Also at Department of Physics and Astronomy, University of Louisville, Louisville, Kentucky, USA. h Also at Department of Physics, University of Fribourg, Fribourg, Switzerland. i Also at Physics Department, University of South Africa, Pretoria, South Africa. j Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain. k Also at Tomsk State University, Tomsk, and Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. l Also at The Collaborative Innovation Center of Quantum Matter (CICQM), Beijing, China. m Also at Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal. n Also at Universita di Napoli Parthenope, Napoli, Italy. o Also at Institute of Particle Physics (IPP), Canada. p Also at II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany. q Also at Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania. r Also at CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France. s Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia. t Also at Borough of Manhattan Community College, City University of New York, New York, USA. u Also at Department of Physics, California State University, Fresno, California, USA. v Also at Department of Financial and Management Engineering, University of the Aegean, Chios, Greece. w Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa. x Also at Louisiana Tech University, Ruston, Louisiana, USA. y Also at California State University, East Bay, Hayward, California, USA. z Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain. aa Also at Department of Physics, University of Michigan, Ann Arbor, Michigan, USA. bb Also at LAL, Université Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France. cc Also at Graduate School of Science, Osaka University, Osaka, Japan. dd Also at Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany. ee Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen/Nikhef, Nijmegen, Netherlands. ff Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia. gg Also at CERN, Geneva, Switzerland. hh Also at Department of Physics, Stanford University, Stanford, California, USA. ii Also at Manhattan College, New York, New York, USA. jj Also at Joint Institute for Nuclear Research, Dubna, Russia. kk Also at Hellenic Open University, Patras, Greece. ll Also at LPNHE, Sorbonne Université, Paris Diderot Sorbonne Paris Cité, CNRS/IN2P3, Paris, France. mm Also at The City College of New York, New York, New York, USA. nn Also at Departamento de Física Teorica y del Cosmos, Universidad de Granada, Granada (Spain), Spain. oo Also at Department of Physics, California State University, Sacramento, California, USA. pp Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia. qq Also at Département de Physique Nucléaire et Corpusculaire, Université de Genève, Genève, Switzerland. 092007-33 M. AABOUD et al. PHYS. REV. D 99, 092007 (2019) rr Also at Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom. ss Also at School of Physics, Sun Yat-sen University, Guangzhou, China. tt Also at Department of Applied Physics and Astronomy, University of Sharjah, Sharjah, United Arab Emirates. uu Also at Institut für Experimentalphysik, Universität Hamburg, Hamburg, Germany. vv Also at National Research Nuclear University MEPhI, Moscow, Russia. ww Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary. xx Also at Giresun University, Faculty of Engineering, Giresun, Turkey. yy Also at Institute of Physics, Academia Sinica, Taipei, Taiwan. 092007-34