Muon reconstruction performance of the ATLAS detector in proton–proton collision data at √s=13 TeV

Eur. Phys. J. C (2016) 76:292 DOI 10.1140/epjc/s10052-016-4120-y Regular Article - Experimental Physics Muon reconstruction performance of the ATLAS detector in proton–proton collision data at √s=13 TeV ATLAS Collaboration CERN, 1211 Geneva 23, Switzerland Received: 18 March 2016 / Accepted: 29 April 2016 / Published online: 23 May 2016 © CERN for the benefit of the ATLAS collaboration 2016. This article is published with open access at Springerlink.com Abstract This article documents the performance of the ATLAS muon identification and reconstruction using the LHC dataset recorded at √s=13 TeV in 2015. Using a large sample of J/ψ →μμ and Z→μμ decays from 3.2 fb−1 of pp collision data, measurements of the reconstruction efficiency, as well as of the momentum scale and resolution, are presented and compared to Monte Carlo simulations. The reconstruction efficiency is measured to be close to 99 % over most of the covered phase space (|η|<2.5 and 5<pT<100 GeV). The isolation efficiency varies between 93 and 100 % depending on the selection applied and on the momentum of the muon. Both efficiencies are well reproduced in simulation. In the central region of the detector, the momentum resolution is measured to be 1.7%(2.3%) for muons from J/ψ →μμ (Z→μμ) decays, and the momentum scale is known with an uncertainty of 0.05 %. In the region |η|>2.2, the pTresolution for muons from Z→μμ decays is 2.9 % while the precision of the momentum scale for low-pTmuons from J/ψ →μμ decays is about 0.2%. 1 Introduction Muons are key to some of the most important physics results published by the ATLAS experiment [1] at the LHC. These results include the discovery of the Higgs boson [2] and the measurementofitsproperties[3–5],theprecisemeasurement of Standard Model processes [6,7], and searches for physics beyond the Standard Model [8–11]. The performance of the ATLAS muon reconstruction during the LHC run at √s= 7–8 TeV has been documented in recent publications [12,13]. During the 2013–2015 shutdown, the LHC was upgraded to increase the centre-of-mass energy from 8 to 13 TeV and the ATLAS detector was equipped with additional muon chambers and a new innermost Pixel layer, the Insertable B-Layer, providing measure- e-mail: [email protected] ments closer to the interaction point. Moreover, the muon reconstruction software was updated and improved. After introducing the ATLAS muon reconstruction and identification algorithms, this article describes the performanceofthemuonreconstructioninthefirstdatasetcollected at √s=13 TeV. Measurements of the muon reconstruction and isolation efficiencies and of the momentum scale and resolution are presented. The comparison between data and Monte Carlo (MC) simulation and the determination of the correctionsto thesimulationusedinphysicsanalysesarealso discussed. The results are based on the analysis of a large sample of J/ψ →μμ and Z→μμ decays reconstructed in 3.2 fb−1of pp collisions recorded in 2015. This article is structured as follows: Sect. 2describes the ATLAS subdetectors that are most relevant to this work; Sects. 3and 5describe the muon reconstruction and identification in ATLAS, respectively; Sect. 4describes the data samples used in the analysis; the reconstruction and isolation efficiencies are described in Sects. 6and 7, respectively, while the momentum scale and resolution are described in Sect. 8. Finally, conclusions are given in Sect. 9. 2 ATLAS detector A detailed description of the ATLAS detector can be found in Ref. [1]. Information primarily from the inner detector (ID) and the muon spectrometer (MS), supplemented by information from the calorimeters, is used to identify and precisely reconstruct muons produced in pp collisions. The ID consists of three subdetectors: the silicon pixels (Pixel) and the semiconductor tracker (SCT) with a pseudorapidity1coverage up to |η|= 2.5, and the transition radi1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r,φ) are used in the transverse plane, φbeing the azimuthal angle around the beam pipe. The pseudorapidity and the transverse momentum are defined in terms of the polar angle θas η=−ln tan(θ/2)and pT= 123 292 Page 2 of 30 Eur. Phys. J. C (2016) 76 :292 ation tracker (TRT) with a pseudorapidity coverage up to |η|= 2.0. The ID measures the muon track close to the interaction point, providing accurate measurements of the track parameters inside an axial magnetic field of 2 T. The MS is the outermost ATLAS subdetector. It is designed to detect muons in the pseudorapidity region up to |η|=2.7, and to provide momentum measurements with a relative resolution better than 3 % over a wide pTrange and up to 10 % at pT≈1 TeV. The MS consists of one barrel (|η|<1.05) and two endcap sections (1.05 <|η|<2.7). A system of three large superconducting air-core toroidal magnets, each with eight coils, provides a magnetic field with a bending integral of about 2.5 Tm in the barrel and up to 6 Tm in the endcaps. Resistive plate chambers (RPC, three doublet layers for |η|<1.05) and thin gap chambers (TGC, one triplet layer followed by two doublets for 1.0<|η|<2.4) provide triggering capability to the detector as well as (η,φ) position measurements with typical spatial resolution of 5–10 mm. A precise momentum measurement for muons with pseudorapidity up to |η|=2.7 is provided by three layers of monitored drift tube chambers (MDT), with each chamber providing six to eight ηmeasurements along the muon trajectory. For |η|>2, the inner layer is instrumented with a quadruplet of cathode strip chambers (CSC) instead of MDTs. The single-hit resolution in the bending plane for the MDT and the CSC is about 80 and 60 µm, respectively. The muon chambers are aligned with a precision between 30 and 60 µm. During the shutdown preceding the LHC Run 2, the MS was completed to its initial design [14] by adding the last missing chambers in the transition region between the barrel and the endcaps (1.0<|η|<1.4). Four RPC-equipped MDT chambers were also installed inside two elevator shafts to improve the acceptance in that region compared to Run 1. Some of the new MDT chambers are made of tubes with a smaller radius compared to the ones used in the rest of the detector, allowing the detector to cope with higher rates. The material between the interaction point (IP) and the MS ranges approximately from 100 to 190 radiation lengths, depending on η, and consists mostly of calorimeters. The lead/liquid-argon electromagnetic calorimeter covers |η|<3.2. It is surrounded by hadronic calorimeters made of steel and scintillator tiles for |η|<1.7, and copper or tungsten and liquid argon for |η|>1.7. 3 Muon reconstruction Muon reconstruction is first performed independently in the ID and MS. The information from individual subdetectors is then combined to form the muon tracks that are used in psin θ, respectively. The η–φdistance between two particles is defined as R=(η)2+(φ)2. physics analyses. In the ID, muons are reconstructed like any other charged particles as described in Refs. [15,16]. This section focuses on the description of the muon reconstruction in the MS (Sect. 3.1) and on the combined muon reconstruction (Sect. 3.2). 3.1 Muon reconstruction in the MS Muon reconstruction in the MS starts with a search for hit patternsinsideeachmuonchambertoformsegments.Ineach MDT chamber and nearby trigger chamber, a Hough transform [17] is used to search for hits aligned on a trajectory in the bending plane of the detector. The MDT segments are reconstructed by performing a straight-line fit to the hits found in each layer. The RPC or TGC hits measure the coordinate orthogonal to the bending plane. Segments in the CSC detectors are built using a separate combinatorial search in the ηand φdetector planes. The search algorithm includes a loose requirement on the compatibility of the track with the luminous region. Muontrackcandidatesarethenbuiltbyfittingtogetherhits from segments in different layers. The algorithm used for this task performs a segment-seeded combinatorial search that starts by using as seeds the segments generated in the middle layers of the detector where more trigger hits are available. The search is then extended to use the segments from the outer and inner layers as seeds. The segments are selected using criteria based on hit multiplicity and fit quality and are matched using their relative positions and angles. At least two matching segments are required to build a track, except in the barrel–endcap transition region where a single highquality segment with ηand φinformation can be used to build a track. The same segment can initially be used to build several track candidates. Later, an overlap removal algorithm selects thebestassignmenttoasingletrack,orallowsforthesegment tobesharedbetweentwotracks. To ensure high efficiencyfor close-by muons, all tracks with segments in three different layers of the spectrometer are kept when they are identical in two out of three layers but share no hits in the outermost layer. The hits associated with each track candidate are fitted using a global χ2fit. A track candidate is accepted if the χ2of the fit satisfies the selection criteria. Hits providing large contributions to the χ2are removed and the track fit is repeated. A hit recovery procedure is also performed looking for additional hits consistent with the candidate trajectory. The track candidate is refit if additional hits are found. 3.2 Combined reconstruction The combined ID–MS muon reconstruction is performed according to various algorithms based on the information 123 Eur. Phys. J. C (2016) 76 :292 Page 3 of 30 292 provided by the ID, MS, and calorimeters. Four muon types are defined depending on which subdetectors are used in reconstruction: •Combined (CB) muon: track reconstruction is performed independently in the ID and MS, and a combined track is formed with a global refit that uses the hits from both the ID and MS subdetectors. During the global fit procedure, MS hits may be added to or removed from the track to improve the fit quality. Most muons are reconstructed following an outside-in pattern recognition, in which the muons are first reconstructed in the MS and then extrapolated inward and matched to an ID track. An inside-out combined reconstruction, in which ID tracks are extrapolated outward and matched to MS tracks, is used as a complementary approach. •Segment-tagged (ST) muons: a track in the ID is classified as a muon if, once extrapolated to the MS, it is associated with at least one local track segment in the MDT or CSC chambers. ST muons are used when muons cross only one layer of MS chambers, either because of their low pTor because they fall in regions with reduced MS acceptance. •Calorimeter-tagged (CT) muons: a track in the ID is identified as a muon if it can be matched to an energy deposit in the calorimeter compatible with a minimum-ionizing particle. This type has the lowest purity of all the muon types but it recovers acceptance in the region where the ATLASmuonspectrometerisonlypartiallyinstrumented to allow for cabling and services to the calorimeters and inner detector. The identification criteria for CT muons are optimised for that region (|η|<0.1) and a momentum range of 15 <pT<100 GeV. •Extrapolated (ME) muons: the muon trajectory is reconstructed based only on the MS track and a loose requirement on compatibility with originating from the IP. The parameters of the muon track are defined at the interaction point, taking into account the estimated energy loss of the muon in the calorimeters. In general, the muon is required to traverse at least two layers of MS chambers to provide a track measurement, but three layers are required in the forward region. ME muons are mainly used to extend the acceptance for muon reconstruction into the region 2.5<|η|<2.7, which is not covered by the ID. Overlaps between different muon types are resolved before producing the collection of muons used in physics analyses. When two muon types share the same ID track, preference is given to CB muons, then to ST, and finally to CT muons. The overlap with ME muons in the muon system is resolved by analyzing the track hit content and selecting the track with better fit quality and larger number of hits. The muon reconstruction used in this work evolved from the algorithms defined as Chain 3 in Ref. [12]. These algorithms were improved in several ways. The use of a Hough transform to identify the hit patterns for seeding the segmentfinding algorithm makes the reconstruction faster and more robust against misidentification of hadrons, thus providing better background rejection early in the pattern recognition process. The calculation of the energy loss in the calorimeter was also improved. An analytic parameterization of the average energy loss is derived from a detailed description of the detector geometry. The final estimate of the energy loss is obtained by combining the analytic parameterization with the energy measured in the calorimeter. This method yields a precision on the mean energy loss of about 30 MeV for 50GeV muons. 4 Data and Monte Carlo samples The efficiency measurements presented in this article are obtained from the analysis of 3.2 fb−1of pp collision data recorded at √s=13 TeV at the LHC in 2015 during the data-taking period with 25 ns spacing between bunch crossings. About 1.5M Z→μμ and 3.5M J/ψ →μμ events are reconstructed and used for the analysis. For the study of the momentum calibration, 2.7 fb−1of data were used, rejecting the runs in which the longitudinal position of the beam spot was displaced by about 3 cm with respect to the centre of the detector. Events are accepted only if the ID, the MS, and the calorimeters were operational and the solenoid and toroid magnet systems were both active. The online event selection wasperformed by a two-leveltrigger system derived from the one described in Ref. [18]. The Z→μμ candidates are triggered by the presence of at least one muon candidate with a transverse momentum, pT, of at least 20 GeV. For the reconstruction efficiency and momentum calibration studies, the muon firing the trigger is required to be isolated (see Sect. 7). The J/ψ →μμ candidates used for the momentum calibration are triggered by a dedicated dimuon trigger that requires two opposite-charge muons, each with pT>4 GeV, compatible with the same vertex, and with a dimuon invariant mass in the range 2.5–4.5 GeV. The J/ψ →μμ sample used for the efficiency measurement is selected using a combination of single-muon triggers and triggers requiring one muon with transverse momentum of at least 4 GeV and an ID track such that the invariant mass of the muon+track pair, under a muon mass hypothesis, is compatible with the mass of the J/ψ. Monte Carlo samples for the process pp →(Z/γ ∗)X→μμXare generated using the POWHEG BOX [19] interfaced to PYTHIA8 [20] and the CT10 [21] parton distribution functions. The PHOTOS [22] package is used to simulate final-state photon radiation in Z 123 292 Page 4 of 30 Eur. Phys. J. C (2016) 76 :292 boson decays. Samples of prompt J/ψ →μμ decays are generated using PYTHIA8 complemented with PHOTOS to simulate the effects of final-state radiation. A requirement on the minimum transverse momentum of each muon (pT>4GeV) is applied at the generator level. The samples used for the simulation of the backgrounds to Z→μμ include: Z→ττ,W→μν, and W→τν, generated with POWHEG BOX; WW,ZZ, and WZ generated with SHERPA [23]; t¯ tsamples generated with POWHEG BOX +PYTHIA8; and b¯ band c¯csamples generated with PYTHIA8. All the generated samples are passed through the simulation of the ATLAS detector based on GEANT4 [24,25] and are reconstructed with the same programs used for the data. The ID and the MS are simulated with an ideal geometry assuming no misalignment. The effect of multiple pp interactions per bunch crossing (“pile-up”) is modelled by overlaying simulated minimumbias events onto the original hard-scattering event. Monte Carlo events are then reweighted so that the distribution of the average number of interactions per event agrees with the data. 5 Muon identification Muonidentificationisperformedbyapplyingqualityrequirements that suppress background, mainly from pion and kaon decays, while selecting prompt muons with high efficiency and/or guaranteeing a robust momentum measurement. Muon candidates originating from in-flight decays of charged hadrons in the ID are often characterized by the presence of a distinctive “kink” topology in the reconstructed track. As a consequence, it is expected that the fit quality of the resulting combined track will be poor and that the momentum measured in the ID and MS may not be compatible. Several variables offering good discrimination between prompt muons and background muon candidates are studied insimulated t¯ tevents.Muons from Wdecaysare categorized as signal muons while muon candidates from light-hadron decays are categorized as background. For CB tracks, the variables used in muon identification are: •q/p significance, defined as the absolute value of the difference between the ratio of the charge and momentum of the muons measured in the ID and MS divided by the sum in quadrature of the corresponding uncertainties; •ρ,defined astheabsolutevalueofthe differencebetween the transverse momentum measurements in the ID and MS divided by the pTof the combined track; •normalised χ2of the combined track fit. To guarantee a robust momentum measurement, specific requirements on the number of hits in the ID and MS are used. For the ID, the quality cuts require at least one Pixel hit,at least fiveSCT hits, fewerthan threePixelor SCT holes, and that at least 10 % of the TRT hits originally assigned to the track are included in the final fit; the last requirement is only employed for |η|between 0.1 and 1.9, in the region of full TRT acceptance. A hole is defined as an active sensor traversed by the track but containing no hits. A missing hit is considered a hole only when it fallsbetween hits successfully assigned to a given track. If some inefficiency is expected for a given sensor, the requirements on the number of Pixel and SCT hits are reduced accordingly. Four muon identification selections (Medium,Loose, Tight,andHigh-pT)areprovidedtoaddressthespecificneeds of different physics analyses. Loose,Medium, and Tight are inclusive categories in that muons identified with tighter requirements are also included in the looser categories. Medium muons The Medium identification criteria provide the default selection for muons in ATLAS. This selection minimises the systematic uncertainties associated with muon reconstruction and calibration. Only CB and ME tracks are used. The former are required to have ≥3 hits in at least two MDT layers, except for tracks in the |η|<0.1 region, where tracks with at least one MDT layer but no more than one MDT hole layer are allowed. The latter are required to have at least three MDT/CSC layers, and are employed only in the 2.5<|η|<2.7 region to extend the acceptance outside the ID geometrical coverage. A loose selection on the compatibility between ID and MS momentum measurements is applied to suppress the contamination due to hadrons misidentified as muons. Specifically, the q/p significance is required to be less than seven. In the pseudorapidity region |η|<2.5, about 0.5 % of the muons classified as Medium originate from the inside-out combined reconstruction strategy. Loose muons The Loose identification criteria are designed to maximise the reconstruction efficiency while providing good-quality muon tracks. They are specifically optimised for reconstructing Higgs boson candidates in the four-lepton final state [5]. All muon types are used. All CB and ME muons satisfying the Medium requirements are included in the Loose selection. CT and ST muons are restricted to the |η|<0.1 region. In the region |η|<2.5, about 97.5 % of the Loose muons are combined muons, approximately 1.5 % are CT, and the remaining 1 % are reconstructed as ST muons. Tight muons Tight muonsareselectedtomaximisethepurity of muons at the cost of some efficiency. Only CB muons with hits in at least two stations of the MS and satisfying the Medium selection criteria are considered. The normalised χ2of the combined track fit is required to be <8 to remove pathological tracks. A two-dimensional cut in the ρand q/p significance variables is performed as a function of the muon 123 Eur. Phys. J. C (2016) 76 :292 Page 5 of 30 292 Table 1 Efficiency for prompt muons from Wdecays and hadrons decaying in-flight and misidentified as prompt muons computed using at¯ tMC sample. The results are shown for the four identification selection criteria separating low (4 <pT<20 GeV) and high (20 <pT<100 GeV) momentum muons for candidates with |η|<2.5. The statistical uncertainties are negligible Selection 4 <pT<20 GeV 20 <pT<100 GeV MC μ[%] MC Hadrons [%] MC μ[%] MC Hadrons [%] Loose 96.7 0.53 98.1 0.76 Medium 95.5 0.38 96.1 0.17 Tight 89.9 0.19 91.8 0.11 High-pT78.1 0.26 80.4 0.13 pTto ensure stronger background rejection for momenta below 20 GeV where the misidentification probability is higher. High-pTmuons The High-pTselection aims to maximise the momentum resolution for tracks with transverse momentum above 100 GeV. The selection is optimised for searches for high-mass Zand Wresonances [8,9]. CB muons passing the Medium selection and having at least three hits in three MS stations are selected. Specific regions of the MS where the alignment is suboptimal are vetoed as a precaution. Requiring three MS stations, while reducing the reconstruction efficiency by about 20 %, improves the pTresolution of muons above 1.5 TeV by approximately 30 %. The reconstruction efficiencies for signal and background obtained from ttsimulation are reported in Table 1.The results are shown for the four identification selection criteria separating low (4 <pT<20 GeV) and high (20 <pT<100 GeV) transverse momentum muon candidates. No isolation requirement is applied in the selection shown in the table. When isolation requirements are applied, the misidentification rates are reduced by more than an order of magnitude. It should be noted that the higher misidentificationrateobservedfor Loose withrespectto Medium muons is mainly due to CT muons in the region |η|<0.1. The misidentification probability estimated with the MC simulation is validated in data by measuring the probability that pions are reconstructed as muons. An unbiased sample of pions from K0 S→π+π−decays is collected with calorimeter-based (photon, electron, jet) triggers. Good agreement between data and simulation is observed independent of the pT,η, and impact parameter of the track. 6 Reconstruction efficiency AsthemuonreconstructionintheID and MS detectors is performed independently, a precise determination of the muon reconstruction efficiency in the region |η|<2.5 is obtained with the tag-and-probe method, as described in the Sect. 6.1. A different methodology, described in Sect. 6.2,isusedin the region 2.5<|η|<2.7 where muons are reconstructed using only the MS detector. 6.1 Efficiency measurement in the region |η|<2.5 The tag-and-probe method is employed to measure the efficiency of the muon identification selections within the acceptance of the ID (|η|<2.5). The method is based on the selection of an almost pure muon sample from J/ψ →μμ or Z→μμ events, requiring one leg of the decay (tag) to be identified as a Medium muon that fires the trigger and the second leg (probe) to be reconstructed by a system independent of the one being studied. A selection based on the event topology is used to reduce the background contamination. Three kinds of probes are used to measure muon efficiencies. ID tracks and CT muons both allow a measurement of the efficiency in the MS, while MS tracks are used to determine the complementary efficiency of the muon reconstruction in the ID. Compared to ID tracks, CT muons offer a more powerful rejection of backgrounds, especially at low transverse momenta, and are therefore the preferred probe type for this part of the measurement. ID tracks are used as a cross-check and for measurements not directly accessible to CT muons. A direct measurement of the CT muon reconstruction efficiency is possible using MS tracks. The efficiency measurement for Medium,Tight, and High-pTmuons consists of two stages. First, the efficiency (X|CT)(X =Medium/Tight/High-pT) of reconstructing these muons assuming a reconstructed ID track is measured using a CT muon as probe. Then, this result is corrected by the efficiency (ID|MS)of the ID track reconstruction, measured using MS probes: (X)=(X|ID)·(ID)=(X|CT)·(ID|MS) (X=Medium/Tight/High-pT). (1) A similar approach is used when using ID probe tracks for cross-checks. This approach is valid if two assumptions are satisfied: •theIDtrackreconstructionefficiencyisindependentfrom the muon spectrometer track reconstruction ((ID)= (ID|MS)). •theuseofaCTmuonasaprobeinsteadofanIDtrackdoes not affect the probability for Medium,Tight,orHigh-pT reconstruction ((X|ID)=(X|CT)). Both assumptions have been tested using generator-level information from simulation and small differences are taken into account in the systematic uncertainties. The muons selected by the Loose identification requirements are decomposed into two samples: CT muons within 123 292 Page 6 of 30 Eur. Phys. J. C (2016) 76 :292 |η|<0.1 and all other muons. The CT muon efficiency is measured using MS probe tracks, while the efficiency of other muons is evaluated using CT probe muons in a fashion similar to the Medium,Tight, and High-pTcategories. The level of agreement of the measured efficiency, Data (X),with theefficiencymeasuredwiththesame method in simulation, MC (X), is expressed as the ratio of these two numbers, called the “efficiency scale factor” (SF): SF =Data (X) MC (X).(2) This quantity describes the deviation of the simulation from the real detector behaviour, and is of particular interest to physics analyses, where it is used to correct the simulation. 6.1.1 The tag-and-probe method with Z →μμ events Events are selected by requiring muon pairs with an invariant mass within 10 GeV of the Zboson mass. The tag muon is required to satisfy the Loose isolation (see Sect. 7.2) and Medium muon identification selections and to have a transverse momentum of at least 24 GeV. Requirements on the significance of the transverse impact parameter d0 (|d0|/σ(d0)<3.0) and on the longitudinal impact parameter |z0|(|z0|<10 mm) of the tag muon are imposed. Finally, the tag muon is required to have triggered the readout of the event. The probe muon is required to have a transverse momentum of at least 10 GeV and to satisfy the Loose isolation criteria. While this is sufficient to ensure high purity in the case of MS probe tracks, further requirements are applied to both the ID track and CT muon probes. In the case of ID tracks, an isolation requirement is applied which is considerably stricter than the Loose selection in order to suppress backgrounds as much as possible. In addition, the invariant mass window is tightened to 5 GeV around the Zboson mass, rather than the 10 GeV used in the other cases. For CT muon probes, additional requirements on the compatibility of the associated calorimeter energy deposit with a muon signature are applied to further enhance the purity. The ID probe tracks and calorimeter-tagged probe muons must also have transverse and longitudinal impact parameters consistent with being produced in a primary pp interaction, as required for tag muons. A probe is considered successfully reconstructed if a reconstructed muon is found within a cone in the η–φplane of size R=0.05 around the probe track. A small fraction (about 0.1 %) of the selected tag–probe pairs originates from sources other than Z→μμ events. For a precise efficiency measurement, these backgrounds must be estimated and subtracted. Contributions from Z→ττ and t¯ tdecays are estimated using simulation. Additionally, multijet events and W→μν decays in association with jet activity (W+jets) can yield tag–probe pairs through secondary muons from heavyor light-hadron decays. As these backgrounds are approximately charge-symmetric, they are estimated from the data using same-charge (SC) tag–probe pairs. This leads to the following estimate of the oppositecharge (OC) background, NBkg, for each region of the kinematic phase-space: NBkg =NZ,t¯ tMC OC +T·NData SC −NZ,t¯ tMC SC (3) where NZ,t¯ tMC OC is the contribution from Z→ττ and t¯ t decays, NData SC is the number of SC pairs measured in data and NZ,t¯ tMC SC is the estimated contribution of the Z→μμ, Z→ττ, and t¯ tprocesses to the SC sample. Tis a global transfer factor that takes into account the charge asymmetry of the multijet and W+jets processes, estimated in data using a control sample of events obtained by inverting the probe isolationrequirement.ForMS(ID)tracks,avalueof T=1.7 (1.1)is obtained, while for calorimeter-tagged muon probes the transfer factor is T=1.2. The systematic uncertainties in the transfer factor vary between 40% and 100 % and are included in the systematic error in the reconstruction efficiency described in Sect. 6.1.3. The efficiency measured in the data is corrected for the background contributions described above by subtracting the predicted probe yields attributed to these sources from the number of observed probes, =NData R−NBkg R NData P−NBkg P ,(4) where NPdenotes the total number of probes and NRthe number of successfully reconstructed probes. The resulting efficiency can then be compared directly to the result of the simulation. 6.1.2 The tag-and-probe method with J/ψ →μμ events The reconstruction efficiencies of the Loose,Medium, and Tight muon selections at low pTare measured from a sample of J/ψ →μμ events selected using a combination of single-muon triggers and the dedicated “muon + track” trigger described in Sect. 4. Tag–probe pairs are selected within the invariant mass window of 2.7–3.5 GeV and requiring a transverse momentumofatleast 5GeVforeachmuon.The tagmuonisrequired to satisfy the Medium muon identification selection and to have triggered the readout of the event. In order to avoid lowmomentum curved tracks sharing the same trigger region, tag and probe muons are required to be R>0.2 apart when extrapolated to the MS trigger surfaces. Finally, they 123 Eur. Phys. J. C (2016) 76 :292 Page 7 of 30 292 η 2.5−2−1.5−1−0.5−0 0.5 1 1.5 2 2.5 Relative Uncertainty [%] 3− 10 2− 10 1− 10 1 10 2 10 3 10 Truth Closure Background Statistics Statistics (MC) Total ATLAS -1 = 13 TeV, 3.2 fbs muonsMedium μμ→Z η 2.5−2−1.5−1−0.5−0 0.5 1 1.5 2 2.5 Relative Uncertainty [%] 3− 10 2− 10 1− 10 1 10 2 10 3 10 Truth closure Statistics (MC) Background Statistics Signal Total ATLAS -1 = 13 TeV, 3.2 fbs muonsMedium μμ→ψJ/ Fig. 1 Total uncertainty in the efficiency scale factor for Medium muons as a function of ηas obtained from Z→μμ data (left) for muons with pT>10 GeV, and from J/ψ →μμ data (right) for muons with 5 <pT<20 GeV. The combined uncertainty is the sum in quadrature of the individual contributions are selected with z0≡|ztag 0−zprobe 0|<5 mm, to suppress background. A probe is considered successfully reconstructed if a selected muon is found within a R=0.05 cone around the probe track. The background contamination and the muon reconstruction efficiency are measured with a simultaneous maximumlikelihood fit of two statistically independent distributions of the invariant mass: events in which the probe is or is not successfully matched to the selected muon. The fits are performed in six pTand nine ηbins of the probe tracks. The signal is modelled with a Crystal Ball function [26] with a single set of parameters for the two independent samples. Separate first-order polynomial fits are used to describe the background shape for matched and unmatched probes. 6.1.3 Systematic uncertainties The main contributions to the systematic uncertainty in the measurement of the efficiency SFs with Z→μμ and J/ψ →μμ events are shown in Figs. 1and 2, as a function of ηand pT, respectively. The uncertainty in the background estimate is evaluated in the Z→μμ analysis by taking the maximum variation of the transfer factor Twhen estimated with a simulation-based approach as described in Ref. [12] and when assuming the background to be charge-symmetric. This results in an uncertaintyoftheefficiencymeasurementbelow0.1 % over a large momentumrange, butreaching ∼1%forlowmuonmomenta where the contribution of the background is most significant. In the J/ψ →μμ analysis, the background uncertainty is estimated by changing the function used in the fit to model the background, replacing the first-order polynomial with an exponential function. An uncertainty due to the signal modelling in the fit, labelled as “Signal” in Figs. 1and 2,isalso estimated using a convolution of exponential and Gaussian [GeV] T p 6 7 8 910 20 30 40 50 60 2 10 Relative Uncertainty [%] 2− 10 1− 10 1 10 2 10 3 10 Truth closure Background Signal Statistics (MC) Statistics Total Truth closure Background Statistics (MC) Statistics Total ATLAS -1 = 13 TeV, 3.2 fbs muonsMedium μμ→ψJ/ μμ→Z Fig. 2 Total uncertainty in the efficiency scale factor for Medium muons as a function of pTas obtained from Z→μμ (solid lines) and J/ψ →μμ (dashed lines) decays. The combined uncertainty is the sum in quadrature of the individual contributions functions as an alternative model. Each uncertainty is about 0.1%. The cone size used for matching selected muons to probe tracks is optimised in terms of efficiency and purity of the matching. The systematic uncertainty deriving from this choice is evaluated by varying the cone size by ±50 %. This yields an uncertainty below 0.1 % in both analyses. Possible biases in the tag-and-probe method, such as biasesduetodifferentkinematicdistributionsbetweenreconstructed probes and generated muons or correlations between ID and MS efficiencies, are estimated in simulation by comparing the efficiency measured with the tag-and-probe method with the “true” efficiency given by the fraction of generator-level muons that are successfully reconstructed. This uncertainty is labelled as “Truth Closure” in Figs. 1 and 2.IntheZ→μμ analysis, agreement better than 0.1% is observed in the high momentum range. This uncertainty 123 292 Page 8 of 30 Eur. Phys. J. C (2016) 76 :292 Efficiency 0.96 0.98 1 0.6 0.65 ATLAS -1 = 13 TeV, 3.2 fbs Data MC μμ→Z η 2.5−2−1.5−1−0.5−00.511.522.5 Data / MC 0.98 1 1.02 Stat only Stat⊕Sys muonsMedium | < 0.1)η muons (|Loose Efficiency 0.85 0.9 0.95 1 0.45 0.5 0.55 0.6 ATLAS -1 = 13 TeV, 3.2 fbs muonsTight Data MC μμ→Z η 2.5−2−1.5−1−0.5−0 0.5 1 1.5 2 2.5 Data / MC 0.95 1 1.05 Stat only Stat⊕Sys Efficiency 0.5 1 ATLAS -1 = 13 TeV, 3.2 fbs muons T High-p μμ→Z Data MC η 2.5−2−1.5−1−0.5−0 0.5 1 1.5 2 2.5 Data / MC 0.9 1 1.1 Stat only Stat⊕Sys Fig. 3 Muon reconstruction efficiency as a function of ηmeasured in Z→μμ events for muons with pT>10 GeV shown for Medium (top), Tight (bottom left), and High-pT(bottom right) muon selections. In addition, the top plot also shows the efficiency of the Loose selection (squares) in the region |η|<0.1wheretheLoose and Medium selections differ significantly. The error bars on the efficiencies indicate the statistical uncertainty. Panels at the bottom show the ratio of the measured to predicted efficiencies, with statistical and systematic uncertainties grows at low pT, and differences up to 0.7 % are found in the J/ψ →μμ analysis. A larger effect of up to 1–2 % is measured in both analyses in the region |η|<0.1. In the extraction of the efficiency scale factors, the difference between the measured and the “true” efficiency cancels to first order. To take into account possible imperfections of the simulation, half of the observed difference is used as an additional systematic uncertainty in the SF. No significant dependence of the measured SFs with pTis observed in the momentum range considered in the Z→μμ analysis. An upper limit on the SF variation for large muon momenta is extracted from simulation, leading to an additional uncertainty of 2–3 % per TeV for muons with pT>200 GeV. The efficiency scale factor is observed to be independent of the amount of pile-up. 6.1.4 Results Figure 3shows the muon reconstruction efficiency as a function of ηas measured from Z→μμ events for the different muon selections. The efficiency as measured in data and the corresponding scale factors for the Medium selection are also shown in Fig. 4as a function of ηand φ. The efficiency at low pTis reported in Fig. 5as measured from J/ψ →μμ events as a function of pTin different ηregions. The efficiencies of the Loose and Medium selections are very similar throughout the detector with the exception of the region |η|<0.1, where the Loose selection fills the MS acceptance gap using the calorimeter and segment-tagged muons contributions. The efficiency of these selections is observedtobeinexcessof98%,andbetween90and98%for the Tight selection, with all efficiencies in very good agreement with those predicted by the simulation. An inefficiency due to a poorly aligned MDT chamber is clearly localised at (η, φ) ∼(−1.3,1.6), and is the most significant feature of the comparison between collision data and simulation for these three categories. In addition, a 2 %-level local inefficiency is visible in the region (η, φ) ∼(1.9,2.5), traced to temporary failures in the SCT readout system. Further local inefficiencies in the barrel region around φ∼−1.1 are also 123 Eur. Phys. J. C (2016) 76 :292 Page 9 of 30 292 Fig. 4 Reconstruction efficiency measured in data (top), and the data/MC efficiency scale factor (bottom) for Medium muons as a function of ηand φfor muons with pT>10 GeV in Z→μμ events. The thin white bins visible in the region |φ|∼πare due to the different bin boundaries in φin the endcap and barrel regions η 2.5−2−1.5−1−0.5−00.511.522.5 φ 3− 2− 1− 0 1 2 3 Data Efficiency [%] 0 20 40 60 80 100 97.7 98.8 97.9 98.7 98.6 98.5 98.4 98.9 98.3 98.9 98.7 99.0 98.1 98.5 99.0 98.4 98.9 99.4 98.8 99.3 99.4 99.5 98.5 99.3 99.4 99.6 99.0 99.5 99.4 99.5 99.5 99.4 99.0 98.9 99.0 99.3 98.9 99.2 98.5 99.2 99.4 99.1 99.0 99.2 99.3 99.2 99.4 99.3 99.5 99.5 99.7 99.4 100.0 99.4 99.2 99.7 99.7 99.2 99.9 99.6 99.7 99.4 99.8 99.6 99.4 99.5 99.6 99.1 97.5 99.2 99.4 99.5 98.9 99.5 99.3 99.3 99.5 99.1 99.4 99.4 98.9 99.2 98.3 95.8 82.1 98.8 99.4 99.4 99.2 98.9 98.4 98.9 99.3 98.9 98.2 99.2 99.4 98.5 98.6 98.3 99.4 98.9 99.5 98.6 99.7 98.6 99.0 98.6 99.4 98.6 99.6 98.8 99.3 99.2 98.5 99.2 99.4 99.4 99.6 99.3 99.5 99.2 99.0 97.5 98.7 94.0 99.4 99.2 99.3 99.0 98.6 98.2 99.6 99.2 99.6 99.2 99.4 99.0 98.8 99.1 99.5 98.8 99.5 99.2 99.5 99.0 98.6 99.0 99.5 99.3 98.1 99.4 99.4 99.3 98.9 97.7 99.3 97.8 99.5 99.4 55.2 91.2 60.8 90.3 44.9 86.1 2.7 81.9 7.9 84.4 17.0 86.4 61.8 86.8 16.2 87.9 99.6 99.3 98.6 99.2 99.5 99.1 97.4 99.1 98.3 99.3 98.4 97.7 99.3 97.6 99.5 99.3 99.7 98.9 99.4 99.3 99.7 99.2 99.7 99.1 99.5 99.2 98.4 98.9 99.5 98.6 99.4 99.5 99.5 99.0 99.1 99.3 99.6 99.1 99.5 99.4 99.4 99.4 98.5 98.2 99.5 87.4 99.5 99.2 99.7 98.2 99.4 98.4 99.5 98.5 99.5 98.7 99.5 99.0 99.0 98.5 99.4 98.5 99.4 98.5 99.1 99.3 99.5 99.5 99.4 99.1 99.8 99.4 99.6 99.3 98.5 98.7 99.8 98.8 98.6 99.1 99.5 99.6 99.6 98.9 98.6 99.2 99.4 99.4 99.3 99.6 99.5 99.0 99.7 99.0 99.2 99.3 99.6 99.6 99.5 99.5 99.7 99.6 99.7 100.0 99.4 99.5 99.6 99.4 99.5 99.7 99.7 99.5 99.3 99.3 99.4 99.3 98.9 99.1 97.7 98.1 98.9 99.1 99.2 99.2 99.3 99.2 99.0 99.5 99.5 99.7 99.5 99.6 99.7 99.6 99.2 99.2 98.5 99.4 99.5 99.6 99.5 99.5 99.5 99.6 98.2 98.7 98.5 98.8 98.1 98.7 98.6 98.8 98.6 98.8 99.1 98.9 98.8 99.0 98.3 99.1 ATLAS -1 = 13 TeV, 3.2 fbs muonsMedium η 2.5−2−1.5−1−0.5−00.511.522.5 φ 3− 2− 1− 0 1 2 3 Data/MC [%] 60 70 80 90 100 110 98.0 99.0 98.3 99.0 98.9 98.9 98.8 99.4 98.7 99.2 99.1 99.3 98.4 98.8 99.4 98.7 99.1 99.6 99.1 99.5 99.7 99.7 98.6 99.5 99.5 99.8 99.4 99.7 99.6 99.7 99.7 99.6 99.4 99.3 99.5 99.8 99.3 99.7 98.9 99.6 99.8 99.5 99.5 99.6 99.6 99.6 99.9 99.7 99.7 99.8 99.9 99.7 100.3 99.7 99.5 100.0 99.9 99.5 100.2 99.9 99.8 99.6 100.0 99.8 99.9 100.0 99.9 99.7 98.2 99.8 99.7 99.9 99.3 99.9 99.7 100.0 99.8 99.7 99.8 99.9 99.6 99.8 99.0 96.5 82.6 99.6 100.1 100.0 99.8 99.6 99.2 99.6 99.9 99.6 99.1 99.8 99.8 99.4 99.0 99.4 99.8 99.8 99.8 99.6 100.0 99.5 99.3 99.1 99.8 99.0 100.0 99.8 99.6 99.7 98.9 99.6 99.7 99.8 100.0 99.7 99.8 99.6 99.3 98.3 99.1 94.9 99.8 99.6 99.5 99.4 98.9 98.6 99.9 99.6 99.9 99.7 99.7 99.5 99.2 99.7 99.8 99.3 99.8 99.6 100.0 99.3 99.1 99.3 99.8 99.7 100.2 99.8 99.7 99.6 99.3 99.7 99.6 99.7 99.9 99.7 99.6 99.3 98.7 99.7 101.1 99.3 90.6 99.5 100.1 98.8 105.3 99.1 100.6 100.0 103.4 99.3 99.8 99.7 99.0 99.6 99.8 99.6 99.3 99.6 100.1 99.6 98.7 99.6 99.6 99.4 99.8 99.7 100.0 99.3 99.8 99.8 100.0 99.6 99.9 99.6 99.8 99.6 98.8 99.5 99.8 99.1 99.8 99.9 99.8 99.4 99.5 99.7 99.8 99.5 99.7 99.8 99.8 99.8 98.8 99.0 99.8 88.1 100.0 99.6 100.0 99.2 99.7 99.4 99.7 99.5 99.8 99.9 99.9 99.9 99.4 98.9 99.8 98.9 99.8 99.6 99.9 100.2 100.0 100.5 99.9 100.1 100.6 100.3 100.2 100.1 99.4 99.5 100.3 99.7 99.5 100.0 99.9 100.1 100.0 99.5 99.4 99.8 99.9 99.9 99.7 100.0 99.9 99.6 100.1 99.7 99.7 99.8 99.8 99.9 99.8 99.8 100.0 99.9 100.0 100.2 99.7 99.7 99.9 99.7 99.8 99.9 99.9 99.8 99.7 99.7 99.8 99.8 99.3 99.5 98.1 98.5 99.3 99.5 99.6 99.6 99.7 99.7 99.5 99.8 99.6 99.8 99.8 99.8 99.9 99.8 99.4 99.4 98.6 99.6 99.8 99.8 99.8 99.7 99.6 99.8 98.6 99.0 99.0 99.3 98.5 99.0 98.9 99.1 98.9 99.1 99.6 99.2 99.1 99.3 98.6 99.4 ATLAS -1 = 13 TeV, 3.2 fbs muonsMedium Efficiency 0.7 0.8 0.9 1 ATLAS -1 = 13 TeV, 3.2 fbs muonsLoose Data MC μμ→ψJ/ Data / MC 0.95 1 1.05 <-2.0 η -2.5< <-1.5 η -2.0< <-1.05 η -1.5< <-0.1 η -1.05< <0.1 η -0.1< <1.05 η 0.1< <1.5 η 1.05< <2.0 η 1.5< <2.5 η 2.0< (5-15) GeV T pStat only Stat⊕Sys Efficiency 0.6 0.8 1 ATLAS -1 = 13 TeV, 3.2 fbs muonsTight Data MC μμ→ψJ/ Data / MC 0.9 1 1.1 <-2.0 η -2.5< <-1.5 η -2.0< <-1.05 η -1.5< <-0.1 η -1.05< <0.1 η -0.1< <1.05 η 0.1< <1.5 η 1.05< <2.0 η 1.5< <2.5 η 2.0< (5-15) GeV T pStat only Stat⊕Sys Fig. 5 Muon reconstruction efficiency in different ηregions measured in J/ψ →μμ events for Loose (left)andTight (right) muon selections. Within each ηregion, the efficiency is measured in six pTbins (5–6, 6–7, 7–8, 8–10, 10–12, and 12–15 GeV). The resulting values are plotted as distinct measurements in each ηbin with pTincreasing from 5 to 15 GeV going from left to right.Theerror bars on the efficiencies indicate the statistical uncertainty. The panel at the bottom shows the ratio of the measured to predicted efficiencies, with statistical and systematic uncertainties linked to temporary faults during data taking. The efficiency of the High-pTselection is significantly lower, as a consequence of the strict requirements on momentum resolution. Local disagreements between prediction and observation are more severe than in the case of the other muon selections. Apart from the poorly aligned MDT chamber, they are most prominent in the CSC region. Figure 6shows the reconstruction efficiencies for the Medium muon selection as a function of transverse momentum, including results from Z→μμ and J/ψ →μμ,for 123 292 Page 16 of 30 Eur. Phys. J. C (2016) 76 :292 [GeV] μμ σ 1.5 2 2.5 3 3.5 4 μμ→Z ATLAS -1 = 13 TeV, 2.7 fbs Data MC Syst. uncert. ) lead μ( η 2.5−2−1.5−1−0.5−00.511.522.5 Data/MC 0.8 1 1.2 [GeV] μμ σ 0.03 0.04 0.05 0.06 0.07 0.08 0.09 μμ→ψJ/ ATLAS -1 = 13 TeV, 2.7 fbs Data MC Syst. uncert. ) lead μ( η 2.5−2−1.5−1−0.5−0 0.5 1 1.5 2 2.5 Data/MC 0.9 1 1.1 Fig. 11 Dimuon invariant mass resolution for CB muons for Z→μμ (left)andJ/ψ →μμ (right) events for data and corrected simulation as a function of the pseudorapidity of the highest-pTmuon. The upper panels showthefittedresolution valuefordataandcorrectedsimulation. The lower panels show the data/MC ratio. The error bars represent the statistical uncertainty; the shaded bands represent the systematic uncertainty in the correction and the systematic uncertainty in the extraction method added in quadrature uncertainties. The systematic uncertainties are estimated following the same procedure described for the determination of the energy scale. Good agreement between the dimuon mass resolution measured in data and simulation is also observed for the ID and MS components of the combined tracks. The relative dimuon mass resolution σμμ/mμμ depends approximately on the average momentum of the muons, as shown in Eq. (10). This allows a direct comparison of the momentum resolution function determined with J/ψ and Zboson decays. This is shown in Fig. 12, where the relative dimuon mass resolution from J/ψ →μμ and Z→μμ events is compared to simulation. The J/ψ →μμ and Z→μμ resolutions are in good agreement. For the J/ψ, the average momentum is defined as pT=1 2(pT,1+pT,2) while for the Zboson it is defined as p∗ T=mZsin θ1sin θ2 2(1−cos α12),(12) where mZis the Zboson mass [30], θ1and θ2are the polar angles of the two muons, and α12 is the opening angle of the muon pair. This definition, based on angular variables only, removes the correlation between the measurement of the dimuon mass and the average pT. 9 Conclusions The performance of the ATLAS muon reconstruction has been measured using 3.2 fb−1of data from pp collisions at √s=13 TeV recorded during the 25 ns run at the LHC in 2015. A large calibration sample consisting of Z→μμ μμ m / μμ σ 0.01 0.02 0.03 0.04 0.05 0.06 ATLAS -1 = 13 TeV, 2.7 fbs Dataμμ→ψJ/ MCμμ→ψJ/ Dataμμ→Z MCμμ→Z Syst. uncert. [GeV]* T p>, T p< 10 2 10 Data/MC 0.6 0.8 1 1.2 1.4 Fig. 12 Dimuon invariant mass resolution divided by the dimuon invariant mass for CB muons measured from J/ψ →μμ and Z→μμ events as a function of the average transverse momentum variables pT and p∗ Tdefined in the text. Both muons are required to be in the same |η|range. The error bars represent the statistical uncertainty while the bands show the systematic uncertainties decays and J/ψ →μμ decays allows for a precise measurement of the reconstruction and isolation efficiency as well as of the momentum resolution and scale over a wide pTrange. The muon reconstruction efficiency is close to 99 % over most of the pseudorapidity range of |η|<2.5for pT>5 GeV. The Z→μμ sample enables a measurement of the efficiency with a precision at the 0.2 % level for pT> 20 GeV. The J/ψ →μμ sample provides a measurement of the reconstruction efficiency between 5 and 20 GeV with a precision better than 1 %. The Z→μμ sample is also used to measure the isolation efficiency for seven isolation working points in the 123 Eur. Phys. J. C (2016) 76 :292 Page 17 of 30 292 momentum range 10–120 GeV. The isolation efficiency varies between 93 and 100 % depending on the selection and on the momentum of the particle, and is well reproduced in the simulation. Themuonmomentumscaleandresolutionhavebeenstudied in detail using J/ψ →μμ and Z→μμ decays. These studies are used to correct the simulation to improve the agreement with data and to minimise the systematic uncertainties in physics analyses. For Z→μμ decays, the uncertainty in the momentum scale varies from a minimum of 0.05 % for |η|<1toamaximumof0.3%for|η|∼2.5. The dimuonmassresolutionisabout1.2%(1.6%)atsmallvalues of pseudorapidity for J/ψ (Z) decays, and increases to 1.6 and 1.9 % in the endcaps for J/ψ and Zdecays, respectively. This corresponds to a relative muon pTresolution of 1.7 and 2.3 % at small values of pseudorapidity and 2.3 and 2.9 % in the endcaps for J/ψ and Zdecays, respectively. After applying momentum corrections, the pTresolution in data and simulation agree to better than 5 % for most of the ηrange. Acknowledgments We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFWandFWF,Austria;ANAS,Azerbaijan; SSTC,Belarus;CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia;BMBF,HGF,andMPG, Germany;GSRT,Greece;RGC,Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the OntarioInnovationTrust,Canada;EPLANET,ERC,FP7,Horizon2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society andLeverhulmeTrust, UnitedKingdom.The crucialcomputingsupport from all WLCG partners is acknowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA) and in the Tier-2 facilities worldwide. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. References 1. ATLAS Collaboration, The ATLAS experiment at the CERN large hadron collider. JINST 3, S08003 (2008). doi:10.1088/1748-0221/ 3/08/S08003 2. ATLAS Collaboration, Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC. Phys. Lett. B 716, 1–29 (2012). doi:10.1016/j.physletb. 2012.08.020.arXiv:1207.7214 [hep-ex] 3. ATLAS Collaboration, Measurement of the Higgs boson mass from the H→γγ and H→ZZ∗→4lchannel with the ATLAS detector using 25 fb−1of pp collision data. Phys. Rev. D 90, 052004 (2014). doi:10.1103/PhysRevD.90.052004. arXiv:1406.3827 [hep-ex] 4. ATLAS Collaboration, Study of the spin and parity of the Higgs boson in diboson decays with the ATLAS detector. Eur. Phys. J. C 75, 476 (2015). doi:10.1140/epjc/s10052-015-3685-1. arXiv:1506.05669 [hep-ex] 5. ATLAS Collaboration, Measurements of Higgs boson production and couplings in the four-lepton channel in pp collisions at center-of-mass energies of 7 and 8 TeV with the ATLAS detector. Phys. Rev. D 91, 012006 (2015). doi:10.1103/PhysRevD.91. 012006.arXiv:1408.5191 [hep-ex] 6. ATLAS Collaboration, Measurement of the transverse momentum and φ∗ ηdistributions of Drell–Yan lepton pairs in proton–proton collisions at √s=8 TeV with the ATLAS detector. Submitted to PLB (2015). arXiv:1512.02192 [hep-ex] 7. ATLAS Collaboration, Measurement of the ZZ production cross section in pp collisions at √s=13 TeV with the ATLAS detector. Phys. Rev. Lett. 116(10), 101801 (2016). arXiv:1512.05314 [hepex] 8. ATLAS Collaboration, Search for high-mass dilepton resonances in pp collisions at √s=8 TeV with the ATLAS detector. Phys. Rev. D 90, 052005 (2014). doi:10.1103/PhysRevD.90.052005. arXiv:1405.4123 [hep-ex] 9. ATLAS Collaboration, Search for new particles in events with one lepton and missing transverse momentum in pp collisions at √s= 8 TeV with the ATLAS detector. JHEP 09, 037 (2014). doi:10. 1007/JHEP09(2014)037.arXiv:1407.7494 [hep-ex] 10. ATLAS Collaboration,Combinationofsearches for WW,WZ,and ZZ resonances in pp collisions at √s=8 TeV with the ATLAS detector. Phys. Lett. B 755, 285–305 (2016). arXiv:1512.05099 [hep-ex] 11. ATLAS Collaboration, Search for new light gauge bosons in Higgs boson decays to four-lepton final states in pp collisions at √s=8 TeV with the ATLAS detector at the LHC. Phys. Rev. D 92, 092001 (2015). doi:10.1103/PhysRevD.92.092001. arXiv:1505.07645 [hep-ex] 12. ATLAS Collaboration, Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton–proton collision data. Eur. Phys. J. C 74, 3130 (2014). doi:10.1140/epjc/s10052-014-3130-x.arXiv:1407.3935 [hep-ex] 13. ATLAS Collaboration, Muon reconstruction efficiency and momentum resolution of the ATLAS experiment in proton–proton collisions at √s=7 TeV in 2010. Eur. Phys. J. C 74, 3034 (2014). doi:10.1140/epjc/s10052-014-3034-9.arXiv:1404.4562 [hep-ex] 14. ATLAS Collaboration, ATLAS muon spectrometer: technical design report. CERN-LHCC-97-22, ATLAS-TDR-10 (1997) 123 292 Page 18 of 30 Eur. Phys. J. C (2016) 76 :292 15. T. Cornelissen et al., Concepts, design and implementation of the ATLAS new tracking (NEWT). ATL-SOFT-PUB-2007-007 (2007). http://cds.cern.ch/record/1020106 16. ATLAS Collaboration, Performance of the ATLAS silicon pattern recognition algorithm in data and simulation at √s=7 TeV. ATLAS-CONF-2010-072 (2010). http://cds.cern.ch/record/ 1281363 17. J. Illingworth, J. Kittler, A survey of the Hough transform. Comput. Vis. Graph. Image Process. 44, 87–116 (1988). ISSN: 0734-189X. http://www.sciencedirect.com/science/article/ pii/S0734189X88800331 18. ATLAS Collaboration, Performance of the ATLAS trigger system in 2010. Eur. Phys. J. C 72, 1849 (2012). doi:10.1140/epjc/ s10052-011-1849-1.arXiv:1110.1530 [hep-ex] 19. S. Alioli et al., A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX. JHEP 06, 043 (2010). arXiv:1002.2581 [hep-ph] 20. T.Sjöstrand, S.Mrenna, P.Skands, Abrief introductionto PYTHIA 8.1. Comput. Phys. Commun. 178, 852 (2008). doi:10.1016/j.cpc. 2008.01.036.arXiv:0710.3820 [hep-ph] 21. H.-L. Lai et al., New parton distributions for collider physics. Phys. Rev. D 82, 074024 (2010). doi:10.1103/PhysRevD.82.074024. arXiv:1007.2241 [hep-ph] 22. P. Golonka, Z. Was, PHOTOS Monte Carlo: a precision tool for QED corrections in Zand Wdecays. Eur. Phys. J. C 45, 97 (2006). doi:10.1140/epjc/s2005-02396-4.arXiv:0506026 [hep-ph] 23. T. Gleisberg et al., Event generation with SHERPA 1.1. JHEP 02, 007 (2009). doi:10.1088/1126-6708/2009/02/007. arXiv:0811.4622 [hep-ph] 24. ATLAS Collaboration, The ATLAS simulation infrastructure. Eur. Phys.J.C70, 823 (2010). arXiv:1005.4568 [physics.ins-det] 25. S. Agostinelli et al., Geant4, a simulation toolkit. Nucl. Instrum. MethodsA 506,250(2003).doi:10.1016/S0168-9002(03)01368-8 26. M. Oreglia, Ph.D. thesis. SLAC-R-0236 (1980) Appendix D 27. ATLAS Collaboration, Jet energy measurement with the ATLAS detector in proton–proton collisions at √s=7TeV.Eur. Phys.J.C73, 2304 (2013). doi:10.1140/epjc/s10052-013-2304-2. arXiv:1112.6426 [hep-ex] 28. M. Cacciari, G.P. Salam, Pileup subtraction using jet areas. Phys. Lett. B 659, 119 (2008). doi:10.1016/j.physletb.2007.09.077 29. M. Cacciari, G.P. Salam, G. Soyez, The anti-ktjet clustering algorithm. JHEP 04, 063 (2008). doi:10.1088/1126-6708/2008/04/063 30. K.A. Olive et al., Review of particle physics. Chin. Phys. C 38, 090001 (2014). doi:10.1088/1674-1137/38/9/090001 ATLAS Collaboration G. Aad87, B. Abbott114, J. Abdallah65, O. Abdinov12, B. Abeloos118, R. Aben108, M. Abolins92, O. S. AbouZeid138, N. L. Abraham150, H. Abramowicz154, H. Abreu153, R. Abreu117, Y. Abulaiti147a,147b, B. S. Acharya164a,164b,a, L. Adamczyk40a, D. L. Adams27, J. Adelman109, S. Adomeit101, T. Adye132, A. A. Affolder76, T. Agatonovic-Jovin14, J. Agricola56, J. A. Aguilar-Saavedra127a,127f, S. P. Ahlen24, F. Ahmadov67,b, G. Aielli134a,134b, H. Akerstedt147a,147b, T. P. A. Åkesson83,A.V.Akimov 97, G. L. Alberghi22a,22b, J. Albert169, S. Albrand57, M. J. Alconada Verzini73, M. Aleksa32, I. N. Aleksandrov67,C.Alexa 28b, G. Alexander154, T. Alexopoulos10, M. Alhroob114, M. Aliev75a,75b, G. Alimonti93a, J. Alison33, S. P. Alkire37, B.M.M.Allbrooke 150, B. W. Allen117, P. P. Allport19, A. Aloisio105a,105b, A. Alonso38, F. Alonso73, C. Alpigiani139, M. Alstaty87, B. Alvarez Gonzalez32, D. Álvarez Piqueras167, M. G. Alviggi105a,105b, B. T. Amadio16, K. Amako68, Y. Amaral Coutinho26a, C. Amelung25, D. Amidei91, S. P. Amor Dos Santos127a,127c, A. Amorim127a,127b, S. Amoroso32, G. Amundsen25, C. Anastopoulos140, L. S. Ancu51, N. Andari109, T. Andeen11, C. F. Anders60b, G. Anders32, J. K. Anders76, K. J. Anderson33, A. Andreazza93a,93b, V. Andrei60a, S. Angelidakis9, I. Angelozzi108, P. Anger46, A. Angerami37, F. Anghinolfi32, A. V. Anisenkov110,c, N. Anjos13, A. Annovi125a,125b, M. Antonelli49, A. Antonov99, J. Antos145b, F. Anulli133a, M. Aoki68, L. Aperio Bella19, G. Arabidze92,Y.Arai 68, J. P. Araque127a,A.T.H.Arce 47, F. A. Arduh73, J-F. Arguin96, S. Argyropoulos65,M.Arik 20a, A. J. Armbruster32, L. J. Armitage78, O. Arnaez32, H. Arnold50, M. Arratia30, O. Arslan23, A. Artamonov98, G. Artoni121, S. Artz85,S.Asai 156, N. Asbah44, A. Ashkenazi154,B.Åsman 147a,147b, L. Asquith150, K. Assamagan27, R. Astalos145a, M. Atkinson166, N. B. Atlay142, K. Augsten129, G. Avolio32,B.Axen 16, M. K. Ayoub118, G. Azuelos96,d, M.A.Baak 32, A. E. Baas60a, M.J.Baca 19, H. Bachacou137, K. Bachas75a,75b, M. Backes32, M. Backhaus32, P. Bagiacchi133a,133b, P. Bagnaia133a,133b,Y.Bai 35a, J. T. Baines132, O. K. Baker176, E.M.Baldin 110,c, P. Balek130, T. Balestri149, F. Balli137, W. K. Balunas123, E. Banas41, Sw. Banerjee173,e, A. A. E. Bannoura175, L. Barak32, E. L. Barberio90, D. Barberis52a,52b, M. Barbero87, T. Barillari102, T. Barklow144,N.Barlow 30, S. L. Barnes86, B. M. Barnett132, R. M. Barnett16, Z. Barnovska5, A. Baroncelli135a, G. Barone25,A.J.Barr 121, L. Barranco Navarro167,F.Barreiro 84, J. Barreiro Guimarães da Costa35a, R. Bartoldus144, A.E.Barton 74,P.Bartos 145a, A. Basalaev124, A. Bassalat118, R. L. Bates55, S. J. Batista159, J. R. Batley30, M. Battaglia138, M. Bauce133a,133b, F. Bauer137,H.S.Bawa 144,f, J. B. Beacham112, M. D. Beattie74, T. Beau82, P. H. Beauchemin162, P. Bechtle23, H. P. Beck18,g, K. Becker121, M. Becker85, M. Beckingham170, C. Becot111, A. J. Beddall20e, A. Beddall20b, V. A. Bednyakov67, M. Bedognetti108,C.P.Bee 149, L. J. Beemster108, T. A. Beermann32, M. Begel27, J.K.Behr 44, C. Belanger-Champagne89, A.S.Bell 80, G. Bella154, L. Bellagamba22a, A. Bellerive31, M. Bellomo88, K. Belotskiy99, O. Beltramello32, N. L. Belyaev99, O. Benary154, D. Benchekroun136a, M. Bender101, K. Bendtz147a,147b, N. Benekos10, Y. Benhammou154, E. Benhar Noccioli176, J. Benitez65, J. A. Benitez Garcia160b, D. P. Benjamin47, J. R. Bensinger25, S. Bentvelsen108, L. Beresford121, 123 Eur. Phys. J. C (2016) 76 :292 Page 19 of 30 292 M. Beretta49, D. Berge108, E. Bergeaas Kuutmann165, N. Berger5, J. Beringer16, S. Berlendis57, N. R. Bernard88, C. Bernius111, F. U. Bernlochner23,T.Berry 79,P.Berta 130, C. Bertella85, G. Bertoli147a,147b, F. Bertolucci125a,125b, I. A. Bertram74, C. Bertsche114, D. Bertsche114,G.J.Besjes 38, O. Bessidskaia Bylund147a,147b, M. Bessner44, N. Besson137, C. Betancourt50, S. Bethke102,A.J.Bevan 78,W.Bhimji 16, R. M. Bianchi126, L. Bianchini25, M. Bianco32, O. Biebel101, D. Biedermann17, R. Bielski86,N.V.Biesuz 125a,125b, M. Biglietti135a, J. Bilbao De Mendizabal51, H. Bilokon49, M. Bindi56, S. Binet118, A. Bingul20b,C.Bini 133a,133b, S. Biondi22a,22b, D. M. Bjergaard47,C.W.Black 151, J. E. Black144, K. M. Black24, D. Blackburn139, R. E. Blair6, J.-B. Blanchard137, J. E. Blanco79, T. Blazek145a, I. Bloch44, C. Blocker25, W. Blum85,*, U. Blumenschein56, S. Blunier34a, G. J. Bobbink108, V. S. Bobrovnikov110,c, S. S. Bocchetta83, A. Bocci47, C. Bock101, M. Boehler50, D. Boerner175, J. A. Bogaerts32, D. Bogavac14, A. G. Bogdanchikov110, C. Bohm147a, V. Boisvert79,T.Bold 40a, V. Boldea28b, A. S. Boldyrev164a,164c, M. Bomben82, M. Bona78, M. Boonekamp137, A. Borisov131, G. Borissov74, J. Bortfeldt101, D. Bortoletto121, V. Bortolotto62a,62b,62c,K.Bos 108, D. Boscherini22a, M. Bosman13, J. D. Bossio Sola29, J. Boudreau126, J. Bouffard2, E. V. Bouhova-Thacker74, D. Boumediene36, C. Bourdarios118, S. K. Boutle55, A. Boveia32,J.Boyd 32, I. R. Boyko67, J. Bracinik19, A. Brandt8, G. Brandt56, O. Brandt60a, U. Bratzler157,B.Brau 88,J.E.Brau 117, H. M. Braun175,*, W. D. Breaden Madden55, K. Brendlinger123, A. J. Brennan90, L. Brenner108, R. Brenner165, S. Bressler172, T.M.Bristow 48, D. Britton55, D. Britzger44, F. M. Brochu30, I. Brock23, R. Brock92, G. Brooijmans37, T. Brooks79, W. K. Brooks34b,J.Brosamer 16, E. Brost117, J. H. Broughton19, P. A. Bruckman de Renstrom41, D. Bruncko145b, R. Bruneliere50, A. Bruni22a, G. Bruni22a , BH Brunt30, M. Bruschi22a, N. Bruscino23, P. Bryant33, L. Bryngemark83, T. Buanes15, Q. Buat143, P. Buchholz142, A. G. Buckley55, I. A. Budagov67, F. Buehrer50, M. K. Bugge120, O. Bulekov99, D. Bullock8, H. Burckhart32, S. Burdin76,C.D.Burgard 50, B. Burghgrave109, K. Burka41,S.Burke 132, I. Burmeister45, E. Busato36, D. Büscher50, V. Büscher85, P. Bussey55, J. M. Butler24, C. M. Buttar55, J. M. Butterworth80, P. Butti108, W. Buttinger27, A. Buzatu55, A. R. Buzykaev110,c, S. Cabrera Urbán167, D. Caforio129,V.M.Cairo 39a,39b, O. Cakir4a, N. Calace51, P. Calafiura16, A. Calandri87, G. Calderini82, P. Calfayan101, L. P. Caloba26a,D.Calvet 36,S.Calvet 36,T.P.Calvet 87, R. Camacho Toro33, S. Camarda32, P. Camarri134a,134b, D. Cameron120, R. Caminal Armadans166, C. Camincher57, S. Campana32, M. Campanelli80, A. Camplani93a,93b, A. Campoverde149, V. Canale105a,105b, A. Canepa160a, M. Cano Bret35e, J. Cantero84, R. Cantrill127a, T. Cao42, M. D. M. Capeans Garrido32, I. Caprini28b, M. Caprini28b, M. Capua39a,39b, R. Caputo85, R. M. Carbone37, R. Cardarelli134a, F. Cardillo50,I.Carli 130,T.Carli 32, G. Carlino105a, L. Carminati93a,93b, S. Caron107, E. Carquin34b, G. D. Carrillo-Montoya32, J.R.Carter 30,J.Carvalho 127a,127c, D. Casadei19, M. P. Casado13,h, M. Casolino13, D. W. Casper163, E. Castaneda-Miranda146a, A. Castelli108, V. Castillo Gimenez167,N.F.Castro 127a,i, A. Catinaccio32, J. R. Catmore120, A. Cattai32, J. Caudron85, V. Cavaliere166, E. Cavallaro13, D. Cavalli93a, M. Cavalli-Sforza13, V. Cavasinni125a,125b, F. Ceradini135a,135b, L. Cerda Alberich167,B.C.Cerio 47, A. S. Cerqueira26b,A.Cerri 150, L. Cerrito78, F. Cerutti16,M.Cerv 32, A. Cervelli18, S. A. Cetin20d, A. Chafaq136a, D. Chakraborty109, S. K. Chan59, Y. L. Chan62a, P. Chang166, J. D. Chapman30, D. G. Charlton19, A. Chatterjee51, C. C. Chau159, C. A. Chavez Barajas150,S.Che 112, S. Cheatham74, A. Chegwidden92, S. Chekanov6, S. V. Chekulaev160a,G.A.Chelkov 67,j,M.A.Chelstowska 91, C. Chen66, H. Chen27, K. Chen149, S. Chen35c, S. Chen156, X. Chen35f, Y. Chen69, H. C. Cheng91, H. J. Cheng35a, Y. Cheng33, A. Cheplakov67, E. Cheremushkina131, R. Cherkaoui El Moursli136e, V. Chernyatin27,*, E. Cheu7, L. Chevalier137, V. Chiarella49, G. Chiarelli125a,125b, G. Chiodini75a, A. S. Chisholm19, A. Chitan28b, M. V. Chizhov67, K. Choi63, A. R. Chomont36, S. Chouridou9, B.K.B.Chow 101, V. Christodoulou80, D. Chromek-Burckhart32, J. Chudoba128, A. J. Chuinard89, J. J. Chwastowski41,L.Chytka 116, G. Ciapetti133a,133b, A.K.Ciftci 4a, D. Cinca55, V. Cindro77, I. A. Cioara23, A. Ciocio16, F. Cirotto105a,105b,Z.H.Citron 172, M. Citterio93a, M. Ciubancan28b,A.Clark 51,B.L.Clark 59, M. R. Clark37,P.J.Clark 48,R.N.Clarke 16, C. Clement147a,147b, Y. Coadou87, M. Cobal164a,164c, A. Coccaro51, J. Cochran66,L.Coffey 25, L. Colasurdo107,B.Cole 37,S.Cole 109, A. P. Colijn108, J. Collot57, T. Colombo32, G. Compostella102, P. Conde Muiño127a,127b, E. Coniavitis50, S. H. Connell146b, I. A. Connelly79, V. Consorti50, S. Constantinescu28b,C. Conta122a,122b,G. Conti32,F. Conventi105a,k,M. Cooke16,B. D. Cooper80,A. M. Cooper-Sarkar121, K. J. R. Cormier159, T. Cornelissen175, M. Corradi133a,133b, F. Corriveau89,l, A. Corso-Radu163, A. Cortes-Gonzalez13, G. Cortiana102,G.Costa 93a, M.J.Costa 167, D. Costanzo140, G. Cottin30,G.Cowan 79,B.E.Cox 86, K. Cranmer111, S. J. Crawley55,G.Cree 31, S. Crépé-Renaudin57, F. Crescioli82, W.A.Cribbs 147a,147b, M. Crispin Ortuzar121, M. Cristinziani23,V.Croft 107, G. Crosetti39a,39b, T. Cuhadar Donszelmann140, J. Cummings176, M. Curatolo49,J.Cúth 85, C. Cuthbert151,H.Czirr 142, P. Czodrowski3,S.D’Auria 55, M. D’Onofrio76, M. J. Da Cunha Sargedas De Sousa127a,127b, C. Da Via86, W. Dabrowski40a, T. Dado145a,T.Dai 91,O.Dale 15, F. Dallaire96, C. Dallapiccola88,M.Dam 38, J. R. Dandoy33, N. P. Dang50, A. C. Daniells19,N. S. Dann86, M. Danninger168,M. Dano Hoffmann137,V.Dao50,G. Darbo52a,S.Darmora8, J. Dassoulas3, A. Dattagupta63, W. Davey23,C.David 169, T. Davidek130,M.Davies 154,P.Davison 80,E.Dawe 90, I. Dawson140, R. K. Daya-Ishmukhametova88,K.De 8, R. de Asmundis105a, A. De Benedetti114,S.DeCastro 22a,22b, 123 292 Page 20 of 30 Eur. Phys. J. C (2016) 76 :292 S. De Cecco82, N. De Groot107, P. de Jong108,H.DelaTorre 84, F. De Lorenzi66, D. De Pedis133a, A. De Salvo133a, U. De Sanctis150, A. De Santo150, J.B.DeVivieDeRegie 118, W. J. Dearnaley74, R. Debbe27, C. Debenedetti138, D. V. Dedovich67, I. Deigaard108, M. Del Gaudio39a,39b, J. Del Peso84, T. Del Prete125a,125b, D. Delgove118, F. Deliot137, C. M. Delitzsch51, M. Deliyergiyev77, A. Dell’Acqua32, L. Dell’Asta24, M. Dell’Orso125a,125b, M. Della Pietra105a,k, D. della Volpe51,M.Delmastro 5,P.A.Delsart 57, C. Deluca108, D. A. DeMarco159, S. Demers176, M. Demichev67, A. Demilly82, S. P. Denisov131, D. Denysiuk137, D. Derendarz41, J. E. Derkaoui136d, F. Derue82,P.Dervan 76, K. Desch23, C. Deterre44, K. Dette45,P.O.Deviveiros 32, A. Dewhurst132, S. Dhaliwal25, A. Di Ciaccio134a,134b, L. Di Ciaccio5, W. K. Di Clemente123, C. Di Donato133a,133b, A.DiGirolamo 32, B. Di Girolamo32, B. Di Micco135a,135b, R. Di Nardo49, A. Di Simone50, R.DiSipio 159, D.DiValentino 31, C. Diaconu87, M. Diamond159,F.A.Dias 48,M.A.Diaz 34a, E. B. Diehl91, J. Dietrich17, S. Diglio87, A. Dimitrievska14, J. Dingfelder23, P. Dita28b, S. Dita28b, F. Dittus32,F.Djama 87, T. Djobava53b, J. I. Djuvsland60a, M.A.B.doVale 26c, D. Dobos32, M. Dobre28b, C. Doglioni83, T. Dohmae156, J. Dolejsi130, Z. Dolezal130, B. A. Dolgoshein99,*, M. Donadelli26d, S. Donati125a,125b, P. Dondero122a,122b, J. Donini36, J. Dopke132,A.Doria 105a,M.T.Dova 73,A.T.Doyle 55, E. Drechsler56,M.Dris 10,Y.Du 35d, J. Duarte-Campderros154, E. Duchovni172, G. Duckeck101, O. A. Ducu96,m, D. Duda108, A. Dudarev32, L. Duflot118, L. Duguid79, M. Dührssen32, M. Dumancic172, M. Dunford60a, H. Duran Yildiz4a, M. Düren54, A. Durglishvili53b, D. Duschinger46, B. Dutta44, M. Dyndal40a, C. Eckardt44, K.M.Ecker 102, R. C. Edgar91, N. C. Edwards48,T.Eifert 32, G. Eigen15, K. Einsweiler16, T. Ekelof165, M. El Kacimi136c, V. Ellajosyula87, M. Ellert165, S. Elles5, F. Ellinghaus175, A. A. Elliot169, N. Ellis32, J. Elmsheuser27, M. Elsing32, D. Emeliyanov132, Y. Enari156, O. C. Endner85, M. Endo119, J. S. Ennis170, J. Erdmann45, A. Ereditato18,G.Ernis 175,J.Ernst 2,M.Ernst 27, S. Errede166,E.Ertel 85, M. Escalier118,H.Esch 45, C. Escobar126, B. Esposito49, A. I. Etienvre137, E. Etzion154, H. Evans63, A. Ezhilov124, F. Fabbri22a,22b, L. Fabbri22a,22b, G. Facini33, R. M. Fakhrutdinov131, S. Falciano133a,R.J.Falla 80, J. Faltova130, Y. Fang35a, M. Fanti93a,93b, A. Farbin8, A. Farilla135a, C. Farina126, T. Farooque13,S.Farrell 16, S. M. Farrington170, P. Farthouat32, F. Fassi136e, P. Fassnacht32, D. Fassouliotis9, M. Faucci Giannelli79, A. Favareto52a,52b, W. J. Fawcett121, L. Fayard118, O. L. Fedin124,n, W. Fedorko168, S. Feigl120, L. Feligioni87, C. Feng35d, E. J. Feng32, H. Feng91, A. B. Fenyuk131, L. Feremenga8, P. Fernandez Martinez167, S. Fernandez Perez13, J. Ferrando55, A. Ferrari165, P. Ferrari108, R. Ferrari122a, D. E. Ferreira de Lima60b, A. Ferrer167, D. Ferrere51, C. Ferretti91, A. Ferretto Parodi52a,52b, F. Fiedler85, A. Filipˇciˇc77, M. Filipuzzi44, F. Filthaut107, M. Fincke-Keeler169, K.D.Finelli 151, M.C.N.Fiolhais 127a,127c,L.Fiorini 167,A.Firan 42, A. Fischer2, C. Fischer13, J. Fischer175, W.C.Fisher 92, N. Flaschel44, I. Fleck142, P. Fleischmann91, G. T. Fletcher140, R. R. M. Fletcher123, T. Flick175, A. Floderus83, L. R. Flores Castillo62a,M.J.Flowerdew 102, G. T. Forcolin86, A. Formica137,A.Forti 86, A. G. Foster19, D. Fournier118,H.Fox 74, S. Fracchia13, P. Francavilla82, M. Franchini22a,22b, D. Francis32, L. Franconi120, M. Franklin59,M.Frate 163, M. Fraternali122a,122b, D. Freeborn80, S. M. Fressard-Batraneanu32, F. Friedrich46, D. Froidevaux32, J.A.Frost 121, C. Fukunaga157, E. Fullana Torregrosa85, T. Fusayasu103, J. Fuster167, C. Gabaldon57, O. Gabizon175, A. Gabrielli22a,22b, A. Gabrielli16, G. P. Gach40a, S. Gadatsch32, S. Gadomski51, G. Gagliardi52a,52b, L. G. Gagnon96, P. Gagnon63, C. Galea107, B. Galhardo127a,127c, E. J. Gallas121,B.J.Gallop 132, P. Gallus129, G. Galster38, K.K.Gan 112,J.Gao 35b,87,Y.Gao 48,Y.S.Gao 144,f, F. M. Garay Walls48, C. García167, J. E. García Navarro167, M. Garcia-Sciveres16, R. W. Gardner33, N. Garelli144, V. Garonne120, A. Gascon Bravo44, C. Gatti49, A. Gaudiello52a,52b, G. Gaudio122a, B. Gaur142, L. Gauthier96, I.L.Gavrilenko 97,C.Gay 168, G. Gaycken23, E. N. Gazis10, Z. Gecse168, C.N.P.Gee 132, Ch. Geich-Gimbel23, M.P.Geisler 60a, C. Gemme52a, M. H. Genest57, C. Geng35b,o, S. Gentile133a,133b, S. George79, D. Gerbaudo13, A. Gershon154, S. Ghasemi142, H. Ghazlane136b, M. Ghneimat23, B. Giacobbe22a, S. Giagu133a,133b, P. Giannetti125a,125b, B. Gibbard27,S.M.Gibson 79, M. Gignac168, M. Gilchriese16, T. P. S. Gillam30, D. Gillberg31, G. Gilles175, D.M.Gingrich 3,d, N. Giokaris9, M. P. Giordani164a,164c, F. M. Giorgi22a,F.M.Giorgi 17, P.F.Giraud 137, P. Giromini59, D. Giugni93a, F. Giuli121, C. Giuliani102, M. Giulini60b, B. K. Gjelsten120, S. Gkaitatzis155, I. Gkialas155, E. L. Gkougkousis118, L. K. Gladilin100,C.Glasman 84, J. Glatzer32, P. C. F. Glaysher48, A. Glazov44, M. Goblirsch-Kolb102, J. Godlewski41, S. Goldfarb91, T. Golling51, D. Golubkov131, A. Gomes127a,127b,127d, R. Gonçalo127a, J. Goncalves Pinto Firmino Da Costa137, L. Gonella19, A. Gongadze67, S. González de la Hoz167, G. Gonzalez Parra13, S. Gonzalez-Sevilla51, L. Goossens32, P. A. Gorbounov98, H. A. Gordon27, I. Gorelov106,B.Gorini 32,E.Gorini 75a,75b, A. Gorišek77, E. Gornicki41, A. T. Goshaw47, C. Gössling45, M. I. Gostkin67, C. R. Goudet118, D. Goujdami136c,A.G.Goussiou 139, N. Govender146b,p, E. Gozani153, L. Graber56, I. Grabowska-Bold40a, P. O. J. Gradin57, P. Grafström22a,22b, J. Gramling51,E.Gramstad 120, S. Grancagnolo17, V. Gratchev124, H.M.Gray 32, E. Graziani135a, Z. D. Greenwood81,q, C. Grefe23, K. Gregersen80, I. M. Gregor44, P. Grenier144,K.Grevtsov 5, J. Griffiths8, A. A. Grillo138,K.Grimm 74, S. Grinstein13,r, Ph. Gris36,J.-F.Grivaz 118,S.Groh 85, J. P. Grohs46, E. Gross172, J. Grosse-Knetter56, G. C. Grossi81, Z.J.Grout 150, L. Guan91, W. Guan173, J. Guenther129, F. Guescini51, D. Guest163, O. Gueta154, E. Guido52a,52b, T. Guillemin5, S. Guindon2,U.Gul 55, C. Gumpert32,J.Guo 35e,Y.Guo 35b,o, 123 Eur. Phys. J. C (2016) 76 :292 Page 21 of 30 292 S. Gupta121, G. Gustavino133a,133b, P. Gutierrez114, N. G. Gutierrez Ortiz80, C. Gutschow46, C. Guyot137, C. Gwenlan121, C. B. Gwilliam76, A. Haas111, C. Haber16, H. K. Hadavand8, N. Haddad136e, A. Hadef87, P. Haefner23, S. Hageböck23, Z. Hajduk41, H. Hakobyan177,*, M. Haleem44,J.Haley 115, G. Halladjian92, G. D. Hallewell87, K. Hamacher175, P. Hamal116, K. Hamano169, A. Hamilton146a, G. N. Hamity140, P. G. Hamnett44,L.Han 35b, K. Hanagaki68,s, K. Hanawa156, M. Hance138, B. Haney123, P. Hanke60a, R. Hanna137, J. B. Hansen38, J. D. Hansen38, M. C. Hansen23, P. H. Hansen38, K. Hara161,A.S.Hard 173, T. Harenberg175,F.Hariri 118, S. Harkusha94, R. D. Harrington48, P. F. Harrison170, F. Hartjes108, M. Hasegawa69, Y. Hasegawa141,A.Hasib 114, S. Hassani137, S. Haug18, R. Hauser92, L. Hauswald46, M. Havranek128, C.M.Hawkes 19, R. J. Hawkings32, A. D. Hawkins83, D. Hayden92, C. P. Hays121, J.M.Hays 78, H. S. Hayward76, S. J. Haywood132, S.J.Head 19, T. Heck85, V. Hedberg83, L. Heelan8,S.Heim 123,T.Heim 16, B. Heinemann16, J. J. Heinrich101, L. Heinrich111, C. Heinz54, J. Hejbal128, L. Helary24, S. Hellman147a,147b, C. Helsens32, J. Henderson121, R. C. W. Henderson74, Y. Heng173, S. Henkelmann168, A. M. Henriques Correia32, S. Henrot-Versille118, G. H. Herbert17, H. Herde25, Y. Hernández Jiménez167,G.Herten 50, R. Hertenberger101,L.Hervas 32, G. G. Hesketh80, N. P. Hessey108, J. W. Hetherly42, R. Hickling78, E. Higón-Rodriguez167, E. Hill169, J. C. Hill30, K. H. Hiller44, S. J. Hillier19, I. Hinchliffe16, E. Hines123,R.R.Hinman 16,M.Hirose 158, D. Hirschbuehl175, J. Hobbs149, N. Hod160a, M. C. Hodgkinson140, P. Hodgson140, A. Hoecker32, M. R. Hoeferkamp106, F. Hoenig101, M. Hohlfeld85, D. Hohn23, T.R.Holmes 16, M. Homann45, T. M. Hong126, B. H. Hooberman166, W. H. Hopkins117,Y.Horii 104, A. J. Horton143,J-Y. Hostachy57,S.Hou152,A. Hoummada136a,J.Howarth44,M. Hrabovsky116,I.Hristova17,J. Hrivnac118, T. Hryn’ova5, A. Hrynevich95,C.Hsu 146c,P.J.Hsu 152,t,S.-C.Hsu 139,D.Hu 37,Q.Hu 35b, Y. Huang44, Z. Hubacek129, F. Hubaut87, F. Huegging23,T.B.Huffman 121, E. W. Hughes37, G. Hughes74, M. Huhtinen32, T. A. Hülsing85,P.Huo 149, N. Huseynov67,b,J.Huston 92,J.Huth 59, G. Iacobucci51, G. Iakovidis27, I. Ibragimov142, L. Iconomidou-Fayard118, E. Ideal176, Z. Idrissi136e, P. Iengo32, O. Igonkina108,u,T.Iizawa 171,Y.Ikegami 68, M. Ikeno68, Y. Ilchenko11,v, D. Iliadis155, N. Ilic144, T. Ince102, G. Introzzi122a,122b, P. Ioannou9,*, M. Iodice135a, K. Iordanidou37, V. Ippolito59, M. Ishino70, M. Ishitsuka158, R. Ishmukhametov112, C. Issever121, S. Istin20a,F.Ito 161, J. M. Iturbe Ponce86, R. Iuppa134a,134b, W. Iwanski41, H. Iwasaki68, J.M.Izen 43, V. Izzo105a, S. Jabbar3, B. Jackson123, M. Jackson76, P. Jackson1,V.Jain 2, K. B. Jakobi85, K. Jakobs50, S. Jakobsen32, T. Jakoubek128, D.O.Jamin 115, D. K. Jana81, E. Jansen80, R. Jansky64, J. Janssen23, M. Janus56,G.Jarlskog 83, N. Javadov67,b,T.Jav˚urek50, F. Jeanneau137, L. Jeanty16, J. Jejelava53a,w, G.-Y. Jeng151, D. Jennens90, P. Jenni50,x, J. Jentzsch45,C.Jeske 170, S. Jézéquel5,H.Ji 173,J.Jia 149, H. Jiang66, Y. Jiang35b, S. Jiggins80, J. Jimenez Pena167,S.Jin 35a, A. Jinaru28b, O. Jinnouchi158, P. Johansson140, K. A. Johns7, W. J. Johnson139, K. Jon-And147a,147b, G. Jones170, R. W. L. Jones74, S. Jones7, T. J. Jones76, J. Jongmanns60a, P. M. Jorge127a,127b, J. Jovicevic160a,X.Ju 173, A. Juste Rozas13,r, M. K. Köhler172, A. Kaczmarska41, M. Kado118, H. Kagan112, M. Kagan144, S. J. Kahn87, E. Kajomovitz47, C. W. Kalderon121, A. Kaluza85,S.Kama 42, A. Kamenshchikov131, N. Kanaya156, S. Kaneti30, L. Kanjir77, V. A. Kantserov99, J. Kanzaki68, B. Kaplan111, L. S. Kaplan173, A. Kapliy33,D.Kar 146c, K. Karakostas10, A. Karamaoun3, N. Karastathis10, M. J. Kareem56, E. Karentzos10, M. Karnevskiy85, S. N. Karpov67, Z. M. Karpova67, K. Karthik111, V. Kartvelishvili74, A. N. Karyukhin131, K. Kasahara161, L. Kashif173, R.D.Kass 112, A. Kastanas15, Y. Kataoka156,C.Kato 156,A.Katre 51, J. Katzy44, K. Kawagoe72, T. Kawamoto156, G. Kawamura56, S. Kazama156, V. F. Kazanin110,c, R. Keeler169, R. Kehoe42, J. S. Keller44, J. J. Kempster79 , K Kentaro104, H. Keoshkerian159, O. Kepka128, B. P. Kerševan77, S. Kersten175, R. A. Keyes89, F. Khalil-zada12, A. Khanov115, A. G. Kharlamov110,c, T. J. Khoo30, V. Khovanskiy98, E. Khramov67, J. Khubua53b,y,S.Kido 69,H.Y.Kim 8,S.H.Kim 161, Y. K. Kim33,N.Kimura 155, O.M.Kind 17,B.T.King 76,M.King 167, S.B.King 168,J.Kirk 132, A. E. Kiryunin102, T. Kishimoto69, D. Kisielewska40a,F.Kiss 50, K. Kiuchi161,O.Kivernyk 137, E. Kladiva145b, M.H.Klein 37, M. Klein76, U. Klein76, K. Kleinknecht85, P. Klimek147a,147b, A. Klimentov27, R. Klingenberg45, J. A. Klinger140, T. Klioutchnikova32, E.-E. Kluge60a, P. Kluit108, S. Kluth102, J. Knapik41, E. Kneringer64, E. B. F. G. Knoops87, A. Knue55, A. Kobayashi156, D. Kobayashi158, T. Kobayashi156, M. Kobel46, M. Kocian144, P. Kodys130, N. M. Koehler102,T.Koffas 31,E.Koffeman 108, T. Koi144, H. Kolanoski17,M.Kolb 60b, I. Koletsou5, A. A. Komar97,*, Y. Komori156, T. Kondo68, N. Kondrashova44, K. Köneke50, A.C.König 107, T. Kono68,z, R. Konoplich111,aa, N. Konstantinidis80, R. Kopeliansky63, S. Koperny40a, L. Köpke85, A. K. Kopp50,K.Korcyl 41, K. Kordas155,A.Korn 80, A.A.Korol 110,c, I. Korolkov13, E. V. Korolkova140, O. Kortner102, S. Kortner102, T. Kosek130, V. V. Kostyukhin23,A.Kotwal 47, A. Kourkoumeli-Charalampidi155, C. Kourkoumelis9, V. Kouskoura27, A.B.Kowalewska 41, R. Kowalewski169, T.Z.Kowalski 40a, W. Kozanecki137, A. S. Kozhin131, V.A.Kramarenko 100, G. Kramberger77, D. Krasnopevtsev99, M.W.Krasny 82, A. Krasznahorkay32, J. K. Kraus23, A. Kravchenko27,M.Kretz 60c, J. Kretzschmar76, K. Kreutzfeldt54, P. Krieger159, K. Krizka33, K. Kroeninger45, H. Kroha102,J.Kroll 123, J. Kroseberg23, J. Krstic14, U. Kruchonak67, H. Krüger23, N. Krumnack66, A. Kruse173,M.C.Kruse 47,M. Kruskal24,T. Kubota90,H. Kucuk80,S. Kuday4b,J. T. Kuechler175,S. Kuehn50,A. Kugel60c, F. Kuger174, A. Kuhl138, T. Kuhl44, V. Kukhtin67, R. Kukla137, Y. Kulchitsky94, S. Kuleshov34b, M. Kuna133a,133b, 123 292 Page 22 of 30 Eur. Phys. J. C (2016) 76 :292 T. Kunigo70, A. Kupco128, H. Kurashige69, Y. A. Kurochkin94,V.Kus 128, E. S. Kuwertz169, M. Kuze158, J. Kvita116, T. Kwan169, D. Kyriazopoulos140,A.LaRosa 102, J.L.LaRosaNavarro 26d, L. La Rotonda39a,39b, C. Lacasta167, F. Lacava133a,133b, J. Lacey31, H. Lacker17, D. Lacour82, V. R. Lacuesta167, E. Ladygin67, R. Lafaye5, B. Laforge82, T. Lagouri176,S.Lai 56, S. Lammers63, W. Lampl7, E. Lançon137, U. Landgraf50, M. P. J. Landon78, V. S. Lang60a, J. C. Lange13, A. J. Lankford163, F. Lanni27, K. Lantzsch23, A. Lanza122a, S. Laplace82, C. Lapoire32, J. F. Laporte137, T. Lari93a, F. Lasagni Manghi22a,22b, M. Lassnig32, P. Laurelli49, W. Lavrijsen16,A.T.Law 138, P. Laycock76, T. Lazovich59, M. Lazzaroni93a,93b,B.Le 90,O.LeDortz 82,E.LeGuirriec 87, E. Le Menedeu13, E. P. Le Quilleuc137, M. LeBlanc169, T. LeCompte6, F. Ledroit-Guillon57,C.A.Lee 27,S.C.Lee 152,L.Lee 1, G. Lefebvre82, M. Lefebvre169, F. Legger101, C. Leggett16, A. Lehan76, G. Lehmann Miotto32,X.Lei 7, W. A. Leight31,A.Leisos 155,ab,A.G.Leister 176, M. A. L. Leite26d, R. Leitner130, D. Lellouch172, B. Lemmer56, K.J.C.Leney 80, T. Lenz23, B. Lenzi32, R. Leone7, S. Leone125a,125b, C. Leonidopoulos48, S. Leontsinis10, G. Lerner150,C.Leroy 96, A. A. J. Lesage137,C.G.Lester 30, M. Levchenko124, J. Levêque5,D.Levin 91,L.J.Levinson 172,M.Levy 19,A.M.Leyko 23,M.Leyton 43,B.Li 35b,o,H.Li 149, H. L. Li33,L.Li 47,L.Li 35e,Q.Li 35a,S.Li 47,X.Li 86,Y.Li 142, Z. Liang138, B. Liberti134a, A. Liblong159, P. Lichard32, K. Lie166, J. Liebal23, W. Liebig15, A. Limosani151,S.C.Lin 152,ac,T.H.Lin 85, B. E. Lindquist149, E. Lipeles123, A. Lipniacka15, M. Lisovyi60b,T.M.Liss 166, D. Lissauer27, A. Lister168, A. M. Litke138,B.Liu 152,ad,D.Liu 152,H.Liu 91, H. Liu27,J.Liu 87, J.B.Liu 35b,K.Liu 87,L.Liu 166,M.Liu 47,M.Liu 35b, Y.L.Liu 35b,Y.Liu 35b,M.Livan 122a,122b, A. Lleres57, J. Llorente Merino84,S.L.Lloyd 78,F.LoSterzo 152, E. Lobodzinska44, P. Loch7, W. S. Lockman138, F. K. Loebinger86, A. E. Loevschall-Jensen38,K.M.Loew 25, A. Loginov176, T. Lohse17, K. Lohwasser44, M. Lokajicek128, B. A. Long24, J.D.Long 166, R. E. Long74, L. Longo75a,75b, K. A. Looper112, L. Lopes127a, D. Lopez Mateos59, B. Lopez Paredes140, I. Lopez Paz13, A. Lopez Solis82, J. Lorenz101, N. Lorenzo Martinez63, M. Losada21, P. J. Lösel101, X. Lou35a, A. Lounis118, J. Love6, P. A. Love74,H.Lu 62a,N.Lu 91, H.J.Lubatti 139, C. Luci133a,133b, A. Lucotte57, C. Luedtke50, F. Luehring63, W. Lukas64, L. Luminari133a, O. Lundberg147a,147b, B. Lund-Jensen148, D. Lynn27, R. Lysak128,E.Lytken 83, V. Lyubushkin67,H.Ma 27,L.L.Ma 35d,Y.Ma 35d, G. Maccarrone49, A. Macchiolo102, C. M. Macdonald140,B.Maˇcek77, J. Machado Miguens123,127b, D. Madaffari87, R. Madar36, H. J. Maddocks165, W. F. Mader46, A. Madsen44, J. Maeda69, S. Maeland15, T. Maeno27, A. Maevskiy100, E. Magradze56, J. Mahlstedt108, C. Maiani118, C. Maidantchik26a, A.A.Maier 102, T. Maier101,A.Maio 127a,127b,127d,S.Majewski 117, Y. Makida68, N. Makovec118, B. Malaescu82, Pa. Malecki41, V. P. Maleev124, F. Malek57, U. Mallik65, D. Malon6, C. Malone144, S. Maltezos10, S. Malyukov32, J. Mamuzic167, G. Mancini49, B. Mandelli32, L. Mandelli93a, I. Mandi´c77, J. Maneira127a,127b, L. Manhaes de Andrade Filho26b, J. Manjarres Ramos160b, A. Mann101, B. Mansoulie137, R. Mantifel89, M. Mantoani56, S. Manzoni93a,93b, L. Mapelli32, G. Marceca29, L. March51, G. Marchiori82, M. Marcisovsky128, M. Marjanovic14,D.E.Marley 91, F. Marroquim26a, S. P. Marsden86, Z. Marshall16, S. Marti-Garcia167, B. Martin92, T. A. Martin170, V. J. Martin48, B. Martin dit Latour15, M. Martinez13,r, S. Martin-Haugh132, V. S. Martoiu28b, A. C. Martyniuk80,M.Marx 139, A. Marzin32, L. Masetti85, T. Mashimo156, R. Mashinistov97,J.Masik 86, A. L. Maslennikov110,c, I. Massa22a,22b, L. Massa22a,22b, P. Mastrandrea5, A. Mastroberardino39a,39b, T. Masubuchi156, P. Mättig175, J. Mattmann85, J. Maurer28b, S. J. Maxfield76, D. A. Maximov110,c, R. Mazini152, S. M. Mazza93a,93b, N. C. Mc Fadden106, G. Mc Goldrick159, S.P.McKee 91, A. McCarn91, R. L. McCarthy149, T. G. McCarthy31, L. I. McClymont80, E. F. McDonald90, K. W. McFarlane58,*, J. A. Mcfayden80, G. Mchedlidze56, S. J. McMahon132, R. A. McPherson169,l, M. Medinnis44, S. Meehan139, S. Mehlhase101, A. Mehta76, K. Meier60a, C. Meineck101, B. Meirose43, B.R.MelladoGarcia 146c,M.Melo 145a, F. Meloni18, A. Mengarelli22a,22b, S. Menke102, E. Meoni162, S. Mergelmeyer17,P.Mermod 51, L. Merola105a,105b, C. Meroni93a, F. S. Merritt33, A. Messina133a,133b, J. Metcalfe6, A. S. Mete163, C. Meyer85, C. Meyer123, J-P. Meyer137, J. Meyer108, H. Meyer Zu Theenhausen60a, R. P. Middleton132, S. Miglioranzi52a,52b, L. Mijovi´c23, G. Mikenberg172, M. Mikestikova128, M. Mikuž77, M. Milesi90, A. Milic32, D. W. Miller33, C. Mills48, A. Milov172, D. A. Milstead147a,147b, A. A. Minaenko131, Y. Minami156, I. A. Minashvili67, A. I. Mincer111, B. Mindur40a, M. Mineev67,Y.Ming 173,L.M.Mir 13, K. P. Mistry123, T. Mitani171, J. Mitrevski101, V. A. Mitsou167, A. Miucci51, P.S.Miyagawa 140, J.U.Mjörnmark 83,T.Moa 147a,147b, K. Mochizuki87, S. Mohapatra37, W. Mohr50, S. Molander147a,147b, R. Moles-Valls23, R. Monden70, M. C. Mondragon92, K. Mönig44, J. Monk38, E. Monnier87, A. Montalbano149, J. Montejo Berlingen32, F. Monticelli73, S. Monzani93a,93b,R.W.Moore 3, N. Morange118, D. Moreno21, M. Moreno Llácer56, P. Morettini52a,D.Mori 143,T.Mori 156,M.Morii 59, M. Morinaga156, V. Morisbak120, S. Moritz85, A.K.Morley 151, G. Mornacchi32,J.D.Morris 78, S. S. Mortensen38,L.Morvaj 149, M. Mosidze53b, J. Moss144, K. Motohashi158, R. Mount144, E. Mountricha27, S. V. Mouraviev97,*, E.J.W.Moyse 88, S. Muanza87, R. D. Mudd19, F. Mueller102, J. Mueller126, R.S.P.Mueller 101, T. Mueller30, D. Muenstermann74, P. Mullen55, G. A. Mullier18, F. J. Munoz Sanchez86, J. A. Murillo Quijada19, W.J.Murray 170,132, H. Musheghyan56, M. Muškinja77, A. G. Myagkov131,ae, M. Myska129, B. P. Nachman144, O. Nackenhorst51, J. Nadal56, K. Nagai121, R. Nagai68,z, 123 Eur. Phys. J. C (2016) 76 :292 Page 23 of 30 292 K. Nagano68, Y. Nagasaka61, K. Nagata161, M. Nagel102, E. Nagy87, A.M.Nairz 32, Y. Nakahama32, K. Nakamura68, T. Nakamura156, I. Nakano113, H. Namasivayam43, R. F. Naranjo Garcia44, R. Narayan11, D. I. Narrias Villar60a, I. Naryshkin124, T. Naumann44,G.Navarro 21, R. Nayyar7, H.A.Neal 91, P. Yu. Nechaeva97, T. J. Neep86, P. D. Nef144,A.Negri 122a,122b,M.Negrini 22a, S. Nektarijevic107, C. Nellist118,A.Nelson 163, S. Nemecek128, P. Nemethy111, A. A. Nepomuceno26a, M. Nessi32,af, M. S. Neubauer166, M. Neumann175,R.M.Neves 111,P.Nevski 27, P. R. Newman19, D. H. Nguyen6, T. Nguyen Manh96, R. B. Nickerson121, R. Nicolaidou137, J. Nielsen138, A. Nikiforov17, V. Nikolaenko131,ae, I. Nikolic-Audit82, K. Nikolopoulos19, J.K.Nilsen 120, P. Nilsson27, Y. Ninomiya156,A.Nisati 133a, R. Nisius102, T. Nobe156, L. Nodulman6, M. Nomachi119, I. Nomidis31, T. Nooney78, S. Norberg114, M. Nordberg32, N. Norjoharuddeen121, O. Novgorodova46,S.Nowak 102, M. Nozaki68, L. Nozka116, K. Ntekas10,E.Nurse 80, F. Nuti90, F. O’grady7, D.C.O’Neil 143, A. A. O’Rourke44, V. O’Shea55, F. G. Oakham31,d, H. Oberlack102, T. Obermann23, J. Ocariz82, A. Ochi69, I. Ochoa37, J. P. Ochoa-Ricoux34a,S.Oda 72, S. Odaka68, H. Ogren63,A.Oh 86, S. H. Oh47,C.C.Ohm 16, H. Ohman165,H.Oide 32,H.Okawa 161, Y. Okumura33, T. Okuyama68,A.Olariu 28b, L. F. Oleiro Seabra127a,S.A.OlivaresPino 48, D. Oliveira Damazio27, A. Olszewski41, J. Olszowska41, A. Onofre127a,127e, K. Onogi104, P.U.E.Onyisi 11,v, M. J. Oreglia33,Y.Oren 154, D. Orestano135a,135b, N. Orlando62b,R.S.Orr 159, B. Osculati52a,52b, R. Ospanov86, G. Otero y Garzon29, H. Otono72, M. Ouchrif136d, F. Ould-Saada120, A. Ouraou137, K. P. Oussoren108, Q. Ouyang35a, M. Owen55, R. E. Owen19, V. E. Ozcan20a, N. Ozturk8, K. Pachal143, A. Pacheco Pages13, C. Padilla Aranda13,M.Pagáˇcová50, S. Pagan Griso16, F. Paige27,P.Pais 88, K. Pajchel120, G. Palacino160b, S. Palestini32, M. Palka40b, D. Pallin36,A.Palma 127a,127b, E. St. Panagiotopoulou10, C. E. Pandini82, J. G. Panduro Vazquez79, P. Pani147a,147b, S. Panitkin27, D. Pantea28b, L. Paolozzi51, Th. D. Papadopoulou10, K. Papageorgiou155, A. Paramonov6, D. Paredes Hernandez176,A.J.Parker 74,M.A.Parker 30,K.A.Parker 140, F. Parodi52a,52b,J.A.Parsons 37, U. Parzefall50, V. R. Pascuzzi159, E. Pasqualucci133a, S. Passaggio52a,F.Pastore 135a,135b,*,Fr.Pastore 79, G. Pásztor31,ag, S. Pataraia175, J. R. Pater86, T. Pauly32, J. Pearce169, B. Pearson114, L. E. Pedersen38, M. Pedersen120, S. Pedraza Lopez167, R. Pedro127a,127b, S. V. Peleganchuk110,c, D. Pelikan165, O. Penc128, C. Peng35a, H. Peng35b, J. Penwell63, B. S. Peralva26b, M. M. Perego137, D. V. Perepelitsa27, E. Perez Codina160a, L. Perini93a,93b, H. Pernegger32, S. Perrella105a,105b, R. Peschke44, V. D. Peshekhonov67, K. Peters44, R. F. Y. Peters86, B. A. Petersen32, T. C. Petersen38, E. Petit57, A. Petridis1, C. Petridou155, P. Petroff118, E. Petrolo133a, M. Petrov121, F. Petrucci135a,135b, N. E. Pettersson88, A. Peyaud137, R. Pezoa34b, P. W. Phillips132, G. Piacquadio144, E. Pianori170, A. Picazio88, E. Piccaro78, M. Piccinini22a,22b,M.A.Pickering 121, R. Piegaia29, J. E. Pilcher33, A. D. Pilkington86, A.W.J.Pin 86, M. Pinamonti164a,164c,ah, J.L.Pinfold 3, A. Pingel38, S. Pires82,H.Pirumov 44, M. Pitt172, L. Plazak145a, M.-A. Pleier27,V.Pleskot 85, E. Plotnikova67, P. Plucinski92, D. Pluth66, R. Poettgen147a,147b, L. Poggioli118, D. Pohl23, G. Polesello122a, A. Poley44, A. Policicchio39a,39b, R. Polifka159, A. Polini22a, C. S. Pollard55, V. Polychronakos27, K. Pommès32, L. Pontecorvo133a, B. G. Pope92, G. A. Popeneciu28c, D. S. Popovic14, A. Poppleton32, S. Pospisil129, K. Potamianos16, I.N.Potrap 67, C.J.Potter 30, C. T. Potter117, G. Poulard32, J. Poveda32, V. Pozdnyakov67, M. E. Pozo Astigarraga32, P. Pralavorio87, A. Pranko16,S.Prell 66, D. Price86,L.E.Price 6, M. Primavera75a, S. Prince89, M. Proissl48, K. Prokofiev62c, F. Prokoshin34b, S. Protopopescu27, J. Proudfoot6, M. Przybycien40a, D. Puddu135a,135b, D. Puldon149, M. Purohit27,ai, P. Puzo118,J.Qian 91,G.Qin 55,Y.Qin 86, A. Quadt56, W. B. Quayle164a,164b, M. Queitsch-Maitland86, D. Quilty55, S. Raddum120, V. Radeka27, V. Radescu60b, S. K. Radhakrishnan149, P. Radloff117, P. Rados90, F. Ragusa93a,93b, G. Rahal178, J.A.Raine 86, S. Rajagopalan27, M. Rammensee32, C. Rangel-Smith165, M.G.Ratti 93a,93b, F. Rauscher101,S.Rave 85, T. Ravenscroft55, M. Raymond32, A. L. Read120, N. P. Readioff76, D. M. Rebuzzi122a,122b, A. Redelbach174, G. Redlinger27, R. Reece138,K.Reeves 43, L. Rehnisch17, J. Reichert123,H.Reisin 29, C. Rembser32,H.Ren 35a, M. Rescigno133a, S. Resconi93a, O. L. Rezanova110,c, P. Reznicek130, R. Rezvani96, R. Richter102, S. Richter80, E. Richter-Was40b,O.Ricken 23, M. Ridel82, P. Rieck17, C. J. Riegel175, J. Rieger56,O.Rifki 114, M. Rijssenbeek149, A. Rimoldi122a,122b, L. Rinaldi22a, B. Risti´c51,E.Ritsch 32, I. Riu13, F. Rizatdinova115, E. Rizvi78, C. Rizzi13, S. H. Robertson89,l, A. Robichaud-Veronneau89, D. Robinson30, J. E. M. Robinson44, A. Robson55, C. Roda125a,125b, Y. Rodina87, A. Rodriguez Perez13, D. Rodriguez Rodriguez167, S. Roe32, C. S. Rogan59, O. Røhne120, A. Romaniouk99, M. Romano22a,22b, S. M. Romano Saez36, E. Romero Adam167, N. Rompotis139, M. Ronzani50, L. Roos82,E.Ros 167, S. Rosati133a, K. Rosbach50,P.Rose 138, O. Rosenthal142, V. Rossetti147a,147b, E. Rossi105a,105b, L. P. Rossi52a,J.H.N.Rosten 30,R.Rosten 139, M. Rotaru28b,I.Roth 172, J. Rothberg139, D. Rousseau118, C. R. Royon137, A. Rozanov87, Y. Rozen153, X. Ruan146c, F. Rubbo144, V.I.Rud 100, M. S. Rudolph159, F. Rühr50, A. Ruiz-Martinez31,Z.Rurikova 50, N. A. Rusakovich67, A. Ruschke101, H.L.Russell 139, J. P. Rutherfoord7, N. Ruthmann32, Y. F. Ryabov124, M. Rybar166, G. Rybkin118,S.Ryu 6, A. Ryzhov131, G. F. Rzehorz56, A. F. Saavedra151, G. Sabato108, S. Sacerdoti29, H. F-W. Sadrozinski138, R. Sadykov67, F. Safai Tehrani133a, P. Saha109, M. Sahinsoy60a, M. Saimpert137, T. Saito156, H. Sakamoto156, Y. Sakurai171, G. Salamanna135a,135b, A. Salamon134a,134b, J. E. Salazar Loyola34b, D. Salek108, P. H. Sales De Bruin139, D. Salihagic102, A. Salnikov144, 123 292 Page 24 of 30 Eur. Phys. J. C (2016) 76 :292 J. Salt167, D. Salvatore39a,39b, F. Salvatore150, A. Salvucci62a, A. Salzburger32, D. Sammel50, D. Sampsonidis155, A. Sanchez105a,105b, J. Sánchez167, V. Sanchez Martinez167, H. Sandaker120, R. L. Sandbach78, H. G. Sander85, M. Sandhoff175, C. Sandoval21, R. Sandstroem102, D. P. C. Sankey132, M. Sannino52a,52b, A. Sansoni49, C. Santoni36, R. Santonico134a,134b, H. Santos127a, I. Santoyo Castillo150, K. Sapp126, A. Sapronov67, J. G. Saraiva127a,127d, B. Sarrazin23, O. Sasaki68, Y. Sasaki156, K. Sato161, G. Sauvage5,*, E. Sauvan5, G. Savage79,P.Savard 159,d, C. Sawyer132, L. Sawyer81,q, J. Saxon33, C. Sbarra22a, A. Sbrizzi22a,22b, T. Scanlon80, D. A. Scannicchio163, M. Scarcella151, V. Scarfone39a,39b, J. Schaarschmidt172, P. Schacht102, D. Schaefer32, R. Schaefer44, J. Schaeffer85, S. Schaepe23, S. Schaetzel60b, U. Schäfer85, A. C. Schaffer118, D. Schaile101, R. D. Schamberger149, V. Scharf60a, V. A. Schegelsky124, D. Scheirich130, M. Schernau163, C. Schiavi52a,52b, C. Schillo50, M. Schioppa39a,39b, S. Schlenker32, K. Schmieden32, C. Schmitt85, S. Schmitt44, S. Schmitz85, B. Schneider160a, U. Schnoor50, L. Schoeffel137, A. Schoening60b, B. D. Schoenrock92, E. Schopf23, A. L. S. Schorlemmer45, M. Schott85, J. Schovancova8, S. Schramm51, M. Schreyer174, N. Schuh85, M. J. Schultens23, H.-C. Schultz-Coulon60a, H. Schulz17, M. Schumacher50, B. A. Schumm138, Ph. Schune137, C. Schwanenberger86, A. Schwartzman144, T. A. Schwarz91, Ph. Schwegler102, H. Schweiger86, Ph. Schwemling137, R. Schwienhorst92, J. Schwindling137, T. Schwindt23, G. Sciolla25, F. Scuri125a,125b, F. Scutti90, J. Searcy91, P. Seema23, S. C. Seidel106, A. Seiden138, F. Seifert129, J. M. Seixas26a, G. Sekhniaidze105a, K. Sekhon91, S. J. Sekula42, D. M. Seliverstov124,*, N. Semprini-Cesari22a,22b, C. Serfon120, L. Serin118, L. Serkin164a,164b, M. Sessa135a,135b, R. Seuster169,H.Severini 114, T. Sfiligoj77, F. Sforza32, A. Sfyrla51, E. Shabalina56, N. W. Shaikh147a,147b, L. Y. Shan35a, R. Shang166, J. T. Shank24, M. Shapiro16, P. B. Shatalov98, K. Shaw164a,164b, S. M. Shaw86, A. Shcherbakova147a,147b, C. Y. Shehu150, P. Sherwood80, L. Shi152,aj, S. Shimizu69, C.O.Shimmin 163, M. Shimojima103, M. Shiyakova67,ak, A. Shmeleva97, D. Shoaleh Saadi96, M. J. Shochet33, S. Shojaii93a,93b, S. Shrestha112, E. Shulga99, M. A. Shupe7, P. Sicho128, P. E. Sidebo148, O. Sidiropoulou174, D. Sidorov115, A. Sidoti22a,22b, F. Siegert46, Dj. Sijacki14, J. Silva127a,127d, S. B. Silverstein147a, V. Simak129,O.Simard 5,Lj.Simic 14, S. Simion118, E. Simioni85, B. Simmons80,D.Simon 36,M.Simon 85, P. Sinervo159, N.B.Sinev 117, M. Sioli22a,22b, G. Siragusa174, S. Yu. Sivoklokov100, J. Sjölin147a,147b,T.B.Sjursen 15, M. B. Skinner74, H. P. Skottowe59, P. Skubic114, M. Slater19, T. Slavicek129, M. Slawinska108, K. Sliwa162,R.Slovak 130, V. Smakhtin172,B.H.Smart 5,L.Smestad 15, S. Yu. Smirnov99,Y.Smirnov 99,L.N.Smirnova 100,al,O.Smirnova 83, M. N. K. Smith37, R. W. Smith37, M. Smizanska74,K.Smolek 129, A. A. Snesarev97, S. Snyder27, R. Sobie169,l, F. Socher46, A. Soffer154, D.A.Soh 152,aj, G. Sokhrannyi77, C. A. Solans Sanchez32, M. Solar129, E. Yu. Soldatov99, U. Soldevila167, A. A. Solodkov131, A. Soloshenko67, O. V. Solovyanov131, V. Solovyev124, P. Sommer50, H. Son162, H. Y. Song35b,am, A. Sood16, A. Sopczak129, V. Sopko129, V. Sorin13, D. Sosa60b, C. L. Sotiropoulou125a,125b, R. Soualah164a,164c, A. M. Soukharev110,c, D. South44, B. C. Sowden79, S. Spagnolo75a,75b, M. Spalla125a,125b, M. Spangenberg170, F. Spanò79, D. Sperlich17, F. Spettel102, R. Spighi22a, G. Spigo32, L. A. Spiller90, M. Spousta130, R. D. St. Denis55,*, A. Stabile93a,R.Stamen 60a,S.Stamm 17, E. Stanecka41, R. W. Stanek6, C. Stanescu135a, M. Stanescu-Bellu44, M. M. Stanitzki44, S. Stapnes120, E. A. Starchenko131,G.H.Stark 33,J.Stark 57, P. Staroba128, P. Starovoitov60a,S.Stärz 32, R. Staszewski41, P. Steinberg27, B. Stelzer143, H.J.Stelzer 32, O. Stelzer-Chilton160a, H. Stenzel54,G.A.Stewart 55, J. A. Stillings23, M. C. Stockton89, M. Stoebe89, G. Stoicea28b, P. Stolte56, S. Stonjek102, A. R. Stradling8, A. Straessner46, M. E. Stramaglia18, J. Strandberg148, S. Strandberg147a,147b, A. Strandlie120, M. Strauss114, P. Strizenec145b, R. Ströhmer174, D. M. Strom117, R. Stroynowski42, A. Strubig107, S. A. Stucci18, B. Stugu15, N. A. Styles44,D.Su 144,J.Su 126, R. Subramaniam81, S. Suchek60a, Y. Sugaya119, M. Suk129, V. V. Sulin97, S. Sultansoy4c, T. Sumida70, S. Sun59, X. Sun35a, J. E. Sundermann50, K. Suruliz150, G. Susinno39a,39b, M. R. Sutton150, S. Suzuki68,M.Svatos 128, M. Swiatlowski33, I. Sykora145a, T. Sykora130,D.Ta 50, C. Taccini135a,135b, K. Tackmann44, J. Taenzer159,A.Taffard 163, R. Tafirout160a, N. Taiblum154, H. Takai27, R. Takashima71, T. Takeshita141, Y. Takubo68, M. Talby87, A. A. Talyshev110,c,J.Y.C.Tam 174, K. G. Tan90, J. Tanaka156, R. Tanaka118, S. Tanaka68, B. B. Tannenwald112, S. Tapia Araya34b, S. Tapprogge85, S. Tarem153, G. F. Tartarelli93a,P.Tas 130,M.Tasevsky 128, T. Tashiro70, E. Tassi39a,39b, A. Tavares Delgado127a,127b, Y. Tayalati136d, A. C. Taylor106, G. N. Taylor90, P. T. E. Taylor90, W. Taylor160b, F. A. Teischinger32, P. Teixeira-Dias79, K. K. Temming50, D. Temple143,H.TenKate 32, P. K. Teng152, J. J. Teoh119, F. Tepel175, S. Terada68, K. Terashi156, J. Terron84, S. Terzo102,M.Testa 49, R. J. Teuscher159,l, T. Theveneaux-Pelzer87, J. P. Thomas19, J. Thomas-Wilsker79, E. N. Thompson37, P. D. Thompson19, A. S. Thompson55, L.A.Thomsen 176, E. Thomson123, M. Thomson30, M. J. Tibbetts16, R. E. Ticse Torres87, V. O. Tikhomirov97,an, Yu. A. Tikhonov110,c, S. Timoshenko99, P. Tipton176, S. Tisserant87, K. Todome158, T. Todorov5,*, S. Todorova-Nova130,J.Tojo 72, S. Tokár145a, K. Tokushuku68,E.Tolley 59, L. Tomlinson86, M. Tomoto104, L. Tompkins144,ao,K.Toms 106, B. Tong59, E. Torrence117,H.Torres 143, E. Torró Pastor139, J. Toth87,ap, F. Touchard87, D. R. Tovey140, T. Trefzger174, A. Tricoli27, I. M. Trigger160a, S. Trincaz-Duvoid82, M. F. Tripiana13, W. Trischuk159, B. Trocmé57,A.Trofymov 44, C. Troncon93a, M. Trottier-McDonald16, M. Trovatelli169, L. Truong164a,164b, M. Trzebinski41, A. Trzupek41, J.C-L.Tseng 121, P. V. Tsiareshka94, G. Tsipolitis10, N. Tsirintanis9, 123 Eur. Phys. J. C (2016) 76 :292 Page 25 of 30 292 S. Tsiskaridze13, V. Tsiskaridze50, E. G. Tskhadadze53a,K.M.Tsui 62a, I.I.Tsukerman 98, V. Tsulaia16, S. Tsuno68, D. Tsybychev149, A. Tudorache28b, V. Tudorache28b, A. N. Tuna59, S. A. Tupputi22a,22b, S. Turchikhin100,al, D. Turecek129, D. Turgeman172,R.Turra 93a,93b, A.J.Turvey 42, P.M.Tuts 37, M. Tyndel132, G. Ucchielli22a,22b, I. Ueda156, R. Ueno31, M. Ughetto147a,147b,F.Ukegawa 161, G. Unal32, A. Undrus27, G. Unel163, F.C.Ungaro 90, Y. Unno68, C. Unverdorben101, J. Urban145b, P. Urquijo90, P. Urrejola85,G.Usai 8, A. Usanova64, L. Vacavant87, V. Vacek129, B. Vachon89, C. Valderanis101, E. Valdes Santurio147a,147b, N. Valencic108, S. Valentinetti22a,22b, A. Valero167, L. Valery13, S. Valkar130, S. Vallecorsa51, J. A. Valls Ferrer167, W. Van Den Wollenberg108, P. C. Van Der Deijl108, R. van der Geer108, H. van der Graaf108, N. van Eldik153, P. van Gemmeren6, J. Van Nieuwkoop143, I. van Vulpen108, M. C. van Woerden32, M. Vanadia133a,133b, W. Vandelli32, R. Vanguri123, A. Vaniachine6, P. Vankov108, G. Vardanyan177, R. Vari133a, E. W. Varnes7, T. Varol42, D. Varouchas82, A. Vartapetian8,K.E.Varvell 151, J. G. Vasquez176, F. Vazeille36, T. Vazquez Schroeder89, J. Veatch56, L. M. Veloce159, F. Veloso127a,127c, S. Veneziano133a, A. Ventura75a,75b, M. Venturi169, N. Venturi159, A. Venturini25, V. Vercesi122a, M. Verducci133a,133b,W.Verkerke 108, J. C. Vermeulen108,A.Vest 46,aq, M. C. Vetterli143,d, O. Viazlo83, I. Vichou166,T.Vickey 140, O.E.VickeyBoeriu 140, G. H. A. Viehhauser121,S.Viel 16, L. Vigani121, R. Vigne64, M. Villa22a,22b, M. Villaplana Perez93a,93b, E. Vilucchi49, M. G. Vincter31, V. B. Vinogradov67, C. Vittori22a,22b, I. Vivarelli150, S. Vlachos10,M.Vlasak 129, M. Vogel175, P. Vokac129, G. Volpi125a,125b, M. Volpi90, H. von der Schmitt102, E. von Toerne23, V. Vorobel130, K. Vorobev99,M.Vos 167,R.Voss 32, J. H. Vossebeld76, N. Vranjes14, M. Vranjes Milosavljevic14,V.Vrba 128, M. Vreeswijk108, R. Vuillermet32, I. Vukotic33, Z. Vykydal129, P. Wagner23, W. Wagner175, H. Wahlberg73, S. Wahrmund46, J. Wakabayashi104, J. Walder74,R.Walker 101, W. Walkowiak142, V. Wallangen147a,147b, C. Wang152, C. Wang35d,87, F. Wang173, H. Wang16, H. Wang42, J. Wang44, J. Wang151, K. Wang89, R. Wang6, S. M. Wang152, T. Wang23, T. Wang37, X. Wang176, C. Wanotayaroj117, A. Warburton89, C. P. Ward30, D. R. Wardrope80, A. Washbrook48, P. M. Watkins19,A.T.Watson 19,M.F.Watson 19, G. Watts139, S. Watts86, B. M. Waugh80, S. Webb85, M. S. Weber18, S. W. Weber174,J.S.Webster 6, A. R. Weidberg121, B. Weinert63, J. Weingarten56,C.Weiser 50, H. Weits108, P. S. Wells32, T. Wenaus27, T. Wengler32, S. Wenig32,N.Wermes 23, M. Werner50, P. Werner32, M. Wessels60a, J. Wetter162, K. Whalen117, N. L. Whallon139, A. M. Wharton74, A. White8, M. J. White1, R. White34b, S. White125a,125b, D. Whiteson163, F. J. Wickens132, W. Wiedenmann173, M. Wielers132, P. Wienemann23, C. Wiglesworth38, L. A. M. Wiik-Fuchs23, A. Wildauer102, F. Wilk86, H. G. Wilkens32, H. H. Williams123, S. Williams108, C. Willis92, S. Willocq88, J.A.Wilson 19, I. Wingerter-Seez5, F. Winklmeier117,O.J.Winston 150, B. T. Winter23, M. Wittgen144, J. Wittkowski101, S.J.Wollstadt 85, M.W.Wolter 41, H. Wolters127a,127c,B.K.Wosiek 41, J. Wotschack32, M. J. Woudstra86, K. W. Wozniak41,M.Wu 57,M.Wu 33,S.L.Wu 173,X.Wu 51,Y.Wu 91, T. R. Wyatt86, B. M. Wynne48, S. Xella38,D.Xu 35a,L.Xu 27, B. Yabsley151, S. Yacoob146a, R. Yakabe69, D. Yamaguchi158, Y. Yamaguchi119, A. Yamamoto68, S. Yamamoto156, T. Yamanaka156, K. Yamauchi104, Y. Yamazaki69,Z.Yan 24, H. Yang35e, H. Yang173, Y. Yang152, Z. Yang15,W-M.Yao 16,Y.C.Yap 82,Y.Yasu 68, E. Yatsenko5, K. H. Yau Wong23,J.Ye 42,S.Ye 27, I. Yeletskikh67,A.L.Yen 59, E. Yildirim44, K. Yorita171, R. Yoshida6, K. Yoshihara123, C. Young144, C. J. S. Young32, S. Youssef24,D.R.Yu 16,J.Yu 8,J.M.Yu 91,J.Yu 66, L. Yuan69,S.P.Y.Yuen 23, I. Yusuff30,ar, B. Zabinski41, R. Zaidan35d, A. M. Zaitsev131,ae, N. Zakharchuk44, J. Zalieckas15, A. Zaman149, S. Zambito59, L. Zanello133a,133b, D. Zanzi90, C. Zeitnitz175, M. Zeman129,A.Zemla 40a,J.C.Zeng 166, Q. Zeng144, K. Zengel25, O. Zenin131, T. Ženiš145a,D.Zerwas 118, D. Zhang91, F. Zhang173, G. Zhang35b,am, H. Zhang35c, J. Zhang6, L. Zhang50, R. Zhang23, R. Zhang35b,as, X. Zhang35d, Z. Zhang118, X. Zhao42, Y. Zhao35d, Z. Zhao35b, A. Zhemchugov67, J. Zhong121, B. Zhou91, C. Zhou47, L. Zhou37, L. Zhou42, M. Zhou149, N. Zhou35f,C.G.Zhu 35d,H.Zhu 35a,J.Zhu 91,Y.Zhu 35b, X. Zhuang35a, K. Zhukov97, A. Zibell174, D. Zieminska63, N.I.Zimine 67, C. Zimmermann85, S. Zimmermann50, Z. Zinonos56,M.Zinser 85, M. Ziolkowski142, L. Živkovi´c14, G. Zobernig173, A. Zoccoli22a,22b, M. zur Nedden17, G. Zurzolo105a,105b, L. Zwalinski32 1Department of Physics, University of Adelaide, Adelaide, Australia 2Physics Department, SUNY Albany, Albany, NY, USA 3Department of Physics, University of Alberta, Edmonton, AB, Canada 4(a)Department of Physics, Ankara University, Ankara, Turkey; (b)Istanbul Aydin University, Istanbul, Turkey; (c)Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey 5LAPP, CNRS/IN2P3 and Université Savoie Mont Blanc, Annecy-le-Vieux, France 6High Energy Physics Division, Argonne National Laboratory, Argonne, IL, USA 7Department of Physics, University of Arizona, Tucson, AZ, USA 8Department of Physics, The University of Texas at Arlington, Arlington, TX, USA 9Physics Department, University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 123