DOI 10.1140/epjc/s10052-012-2056-4
Letter
Search for heavy neutrinos and right-handed W bosons in events
with two leptons and jets in pp collisions at
√
s
= 7 TeV
with the ATLAS detector
The ATLAS CollaborationCERN, 1211 Geneva 23, Switzerland
Received: 24 March 2012 / Revised: 17 May 2012 / Published online: 3 July 2012
© CERN for the benefit of the ATLAS collaboration 2012. This article is published with open access at Springerlink.com
Abstract This letter reports on a search for hypothetical heavy neutrinos, N , and right-handed gauge bosons, WR, in events with high transverse momentum objects which in-clude two reconstructed leptons and at least one hadronic jet. The results were obtained from data corresponding to an integrated luminosity of 2.1 fb−1collected in proton–proton collisions at √s= 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. No excess above the Stan-dard Model background expectation is observed. Excluded mass regions for Majorana and Dirac neutrinos are presented using two approaches for interactions that violate lepton and lepton-flavor numbers. One approach uses an effective oper-ator framework, the other approach is guided by the Left– Right Symmetric Model. The results described in this letter represent the most stringent limits to date on the masses of heavy neutrinos and WRbosons obtained in direct searches.
1 Introduction
The discovery of neutrino oscillations [1,2] unambiguously establishes that neutrinos have non-zero mass and provides clear evidence for physics beyond the Standard Model (SM). One possible explanation for the mass of light neutrinos is provided by theoretical models based on a Grand Unified Theory (GUT). Such models often introduce one or more additional neutrino fields, which manifest themselves as new heavy particles that could be directly observable at the Large Hadron Collider (LHC). In the framework of GUT mod-els, the mass of the light neutrinos could be explained via the see-saw mechanism [3–6]. This predicts mν≈ m2D/mN, where, for each generation, mν is the mass of a known light neutrino, mDis the Dirac mass for charged fermions of the
e-mail:atlas.publications@cern.ch
same generation, and mN is the mass of a new heavy neu-trino, N . If the see-saw mechanism were to explain the mas-ses of the known neutrinos, both the light and the heavy neutrinos would have to be Majorana particles. This would violate lepton number conservation, and yield a striking sig-nature of two leptons with the same charge at the LHC [7].
This letter reports on a search for new heavy neutrinos of either Majorana or Dirac type, with data corresponding to an integrated luminosity of 2.1 fb−1recorded with the ATLAS detector at the LHC. Two approaches are employed. The first approach aims at exploring possible sources of new physics predicting heavy neutrinos using a Lagrangian of effective operators (referred to as HNEO hereafter) [8]. The theory is built on effective four-fermion operators (q¯q→ N) with the N decaying promptly via a three-body decay, N→ jj. The second approach is based on the concept of Left–Right Symmetry [9–11] which extends the electroweak part of the SM by a new gauge group. Its force particles (WRand Z bosons) could be produced at LHC energies. A particular implementation of left–right symmetry breaking [12], the Left–Right Symmetric Model (LRSM) with doubly charged Higgs bosons [13,14] is used in the present analysis. Ac-cording to this model, the heavy neutrinos would be pro-duced in the decays of a WRboson via q¯q→ WR→ N, with N decaying subsequently via N→ WR∗→ jj. Thus, the final state signature for both models consists of two leptons and two jets with high transverse momenta (pT). Only electrons and muons are considered in this analy-sis.
The N invariant mass can be fully reconstructed from the decay products in both approaches. Given the s-channel production in the LRSM, the WRmass, mWR, can also be reconstructed in this model. The reconstructed WR boson and N masses are used to perform the search in the con-text of the HNEO and LRSM models, respectively. Like the SM neutrinos, heavy neutrinos can mix if their masses are
different. Both the scenarios of no mixing [15] and maxi-mal mixing [16] between two generations of lepton flavors (electron and muon) are investigated assuming that the mass difference between the heavy neutrinos is much smaller than the experimental resolution of their reconstructed invariant mass. In the case of maximal mixing, a mass difference of 2 GeV is assumed. If the heavy neutrinos are of Majorana type, they would contribute to both the same-sign (SS) and opposite-sign (OS) channels, while heavy Dirac neutrinos would contribute solely to the OS channel.
Heavy neutrinos were previously searched for at LEP and excluded for masses up to ≈100 GeV [17–20]. The most stringent direct limits on WRbosons [21,22] come from the Tevatron, where WR→ tb decays were searched for. As-suming a branching ratio of 100 %, WRboson masses be-low 825 GeV are excluded at 95 % confidence level (C.L.). Recently, the ATLAS collaboration published an inclusive search for new physics in the same-sign dilepton signature for an integrated luminosity of 34 pb−1 [23]. The 95 % C.L. limits presented exclude WRmasses up to about 1 TeV for the LRSM model and Majorana neutrino masses around 460 GeV for the HNEO model.
2 The ATLAS detector
The ATLAS detector [24] is a multipurpose particle physics apparatus with a forward-backward symmetric cylindrical geometry and nearly 4π coverage in solid angle.1The in-ner tracking detector (ID) covers the pseudorapidity range
|η| < 2.5 and consists of: a silicon pixel detector,
provid-ing typically three measurements per track; a silicon mi-crostrip detector (SCT), which provides typically four to five measurements; and, for |η| < 2.0, a transition radi-ation tracker (TRT), giving typically 30 straw-tube mea-surements per track. The ID is surrounded by a thin su-perconducting solenoid providing a 2 T magnetic field. A high-granularity liquid-argon (LAr) sampling electromag-netic calorimeter covers the region|η| < 3.2. An iron-scinti-llator tile calorimeter provides hadronic coverage in the cen-tral rapidity range of |η| < 1.7. The end-cap and forward regions, spanning 1.5 <|η| < 4.9, are instrumented with LAr calorimeters for both electromagnetic and hadronic measurements. The muon spectrometer (MS) surrounds the calorimeters and consists of a system of air-core super-conducting toroid coils, precision tracking chambers up
1ATLAS uses a right-handed coordinate system with its origin at the
nominal interaction point in the center of the detector and the z-axis coinciding with the axis of the beam pipe. The x-axis points from the interaction point to the center 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 is defined in terms of the polar angle θ as η= ln tan(θ/2).
to |η| < 2.7, and detectors for triggering in the region of
|η| < 2.4.
3 Trigger and data
The data used in this analysis were recorded between March and August 2011 at a center-of-mass energy of 7 TeV. The application of beam, detector, and data quality requirements results in a total integrated luminosity of 2.1 fb−1with an estimated uncertainty of±3.7 % [25, 26]. The data were recorded with single lepton (e or μ) triggers [27]. At the last stage of the trigger decision, the electron trigger selects candidate electrons with transverse energy ET>20 GeV, satisfying shower-shape requirements and matching an ID track. For the last part of the dataset, corresponding to an integrated luminosity of 0.5 fb−1, the threshold was raised to 22 GeV. The muon trigger selects candidate muons with pT>18 GeV and|η| < 2.4. These triggers reach full ef-ficiency for electrons with pT>25 GeV and muons with pT >20 GeV. The typical trigger efficiencies measured from data for leptons selected for offline analysis are 99± 1 % for electrons, and 74 % and 91 % for muons in the barrel (|η| < 1.05) and end-cap (1.05 < |η| < 2.4) regions, respectively, with an uncertainty of about±1 %.
4 Monte Carlo simulation
Fully simulated Monte Carlo (MC) event samples are used to develop and validate the analysis procedure, es-timate the detector acceptance and reconstruction effi-ciency, and aid in the background determination. The sim-ulation of background processes is described in detail in Ref. [28]. For the major backgrounds, Z/γ∗+ jets pro-duction and top quark pair propro-duction, ALPGEN [29] and MC@NLO [30–32] are used, respectively. The leading-order parametrization CTEQ6L1 [33] of the parton density functions (PDF) is used for the ALPGENsimulation, while the next-to-leading order parametrization CTEQ6.6 [33] is used for the MC@NLO simulation. Fragmentation and hadronization are performed in both cases with HERWIG [34–36], using JIMMY [37] for the underlying event mod-elling. Diboson (W W , W Z, and ZZ) event samples are gen-erated using HERWIG, while MADGRAPH[38] interfaced to PYTHIA[39] is used for W γ and Zγ production. Single top-quark production is generated with MC@NLO. The produc-tion of W+W+ arising from a t-channel gluon exchange, resulting in two jets in the final state and two same-sign W bosons, are generated with MADGRAPH interfaced to PYTHIA. The associated production of a vector boson with a t¯t pair (t ¯tW , t ¯tZ, t ¯tγ ) is simulated with MADGRAPH interfaced with PYTHIA.
The HNEO signal MC samples are generated using CALCHEP [40] and the leading-order PDF CTEQ6L [33], and hadronization simulated with PYTHIA. All lepton com-binations of e, μ or τ leading to lepton number violating (LNV) signatures, which produce SS or OS dilepton events, are included. The model is implemented via a Lagrangian of effective operators defined as
L =∞ n=5 1 Λn−4· i αiOi(n), (1)
where n is the operator dimension, Λ is the scale of LNV interactions, αi are the coupling constants between the neu-trino N and the leptons, and Oi are the effective opera-tors [8]. The signal samples are produced for four effective operator hypotheses: the four-fermion vector operator,OV, and four-fermion scalar operators,Os1,Os2, andOs3. The tree-level-generated dimension-6 operator OV corresponds to duNe, whileOs1andOs2correspond to QuNL and LNQd, respectively, andOs3corresponds to QNLd (e, u, d and L, Qdenote the right-handed SU(2) singlets and left-handed SU(2) doublets, respectively). The production via the effec-tive operatorsOs1andOs2have the same cross section and lead to identical event kinematics, which makes them indis-tinguishable. The production cross sections for the Majorana and Dirac neutrinos in the framework of the effective La-grangian are related to the energy scale of new physics and the coupling constant σ ≈ α2/Λ4, such that the coupling can be varied to scan for new physics at different Λ scales.
The LRSM signal MC samples are generated using an implementation of this model [14] in PYTHIA, with modified leading-order parton distribution functions MRST2008LO* [41]. The coupling constants for the WRand left-handed W boson are assumed to be the same, including the CKM ma-trix for WR boson couplings to right-handed chiral quark components. It is assumed that there is no mixing between the WRboson and the SM W boson. The LRSM signal MC samples are generated constraining the decays to e or μ and with mN< mWR. The branching fractions used are the ones predicted by PYTHIA. When the mass difference between the WRand the N is large, the leptonic branching fractions are ≈8 %, and they decrease with decreasing mass differ-ence.
Both Majorana and Dirac type heavy neutrinos are con-sidered, assuming that the total production cross section is the same for both cases. The leading-order theoretical cross sections are used.
All signal and background samples are generated us-ing the ATLAS underlyus-ing event tunes [42, 43] and pro-cessed through the ATLAS detector simulation [44] based on GEANT4 [45]. The MC samples are produced includ-ing the simulation of multiple interactions per LHC bunch crossing (pile-up). Varying pile-up conditions and their de-pendence on the instantaneous luminosity of the LHC are
taken into account by reweighting MC events to match the pile-up conditions measured in data.
5 Object reconstruction and event selection
The criteria for electron and muon identification closely fol-low those described in Ref. [46]. Electrons are required to pass the “medium” selection criteria, with pT>25 GeV and
|η| < 2.47, excluding the electromagnetic calorimeter
tran-sition region, 1.37 <|η| < 1.52 [47]. To improve the back-ground rejection for|η| > 2.0, more stringent requirements are placed on the track-cluster matching in η and shower shape. Electron tracks that pass through an active region of the innermost pixel detector are required to have a measure-ment in that layer in order to suppress electrons from photon conversions. Additionally, an electron whose track matches the ID track of a muon candidate is rejected.
Muons are required to be identified in both the ID and the MS systems. The ID track is required to have at least one pixel hit, more than five SCT hits, and a number of TRT hits that varies with η. Muon tracks that pass through an ac-tive region of the innermost pixel detector are required to have a measurement in that layer. The curvatures, as mea-sured by the ID and MS systems, must have the same sign. Only muons with pT>25 GeV and |η| < 2.4 are consid-ered. Selection criteria on the displacement of the muon rel-ative to the primary vertex, selected as the one with the high-estpT2 of associated tracks, are required. The longitudi-nal (z0) and transverse (d0) impact parameters must satisfy
|z0| < 5 mm, |d0| < 0.2 mm, and |d0/σd0| < 5, where σd0 is the uncertainty on d0. These cuts reduce the cosmic ray muon background to a negligible level and also reduce the background from non-prompt muons.2
To reduce the background due to leptons from decays of hadrons (including heavy-flavor hadrons) produced in jets, requirements on the isolation of leptons are imposed. To evaluate the isolation energy for electrons, the transverse en-ergies deposited in the calorimeter towers in a cone in η–φ space of radius R=(φ)2+ (η)2= 0.2 around the electron direction are summed and corrected for energy de-position from pile-up events. In addition, the transverse en-ergy of the electron, ET, corrected for energy leakage into the neighboring towers, is subtracted. The isolation trans-verse energy is required to be less than 15 % of the elec-tron ET. An equivalent quantity, ETR=0.3, is calculated for the muon using a cone size of R= 0.3. If there is no jet with pT>20 GeV within R < 0.4 of the muon, ERT =0.3 is required to be less than 15 % of the muon pT. Addition-ally, muons with pT<80 GeV should have no other track
2Leptons from W , Z and τ decays are classified as prompt leptons,
with pT>1 GeV originating from the primary vertex within a cone of R= 0.3 around the muon. Otherwise, if the muon has a jet nearby, it must satisfy pT>80 GeV and (ERT =0.3/pT− 3)/pT>−0.02 GeV−1. These isolation re-quirements are powerful in rejecting background muons and highly efficient for selecting signal muons produced in the decays of heavy neutrinos and reconstructed near the signal jets in cases where the heavy neutrino is boosted.
Jets are reconstructed using the anti-kt jet clustering al-gorithm [48,49] with a radius parameter R= 0.4. The input to this algorithm is clusters of calorimeter cells seeded by cells with energies significantly above the measured noise. The energies and momenta of jets are evaluated by perform-ing a four-vector sum over these clusters, treatperform-ing each clus-ter as an (E, p) four-vector with zero mass. Jets are cor-rected for calorimeter non-compensation, upstream material and other effects using pTand η-dependent calibration fac-tors [50] obtained from MC simulation [51], and validated with test-beam and collision-data studies. Only jets with pT>20 GeV and|η| < 2.8 are considered. To avoid dou-ble counting, the closest jet within R < 0.5 of an electron candidate is discarded. The selected jets must pass quality requirements based on their shower shape, and their calori-meter signal timing must be consistent with the timing of the beam crossings [52]. Events with any jet that fails the jet quality criteria are rejected. To suppress jets unrelated to the hard scattering of interest, at least 75 % of the summed pTof all reconstructed tracks associated with a jet with|η| < 2.8 must come from tracks originating from the selected pri-mary vertex. During a part of the data-taking period, cor-responding to an integrated luminosity of 0.9 fb−1, an elec-tronic failure in a small η–φ region of the LAr EM calorime-ter created a dead region. For this integrated luminosity, events in data and MC containing either an identified elec-tron or a jet, with pT>40 GeV, satisfying−0.1 < η < 1.5 and−0.9 < φ < −0.5 are rejected, leading to a loss of sig-nal efficiency of about 10 % for this portion of the data.
Events are preselected by requiring exactly two identified leptons with pT>25 GeV originating from the primary ver-tex and at least one jet with pT>20 GeV. At least one of the lepton candidates must match a triggered lepton at the last stage of the trigger selection. To reduce the number of background events from Drell–Yan production and misiden-tified leptons, the dilepton invariant mass, m, is required to be greater than 110 GeV. The signal region is then sub-divided into SS and OS dilepton events. In the OS dilepton channels, further background reduction is achieved by re-quiring that the scalar sum of the transverse energies of the two leptons and the leading two jets with pT>20 GeV, de-noted by ST, is greater than 400 GeV. This event selection is referred to hereafter as the baseline selection. As mentioned previously, the mass of the N can be reconstructed from its decay products of one lepton and two jets. In the case where
the N is boosted, the hadronic decay products can be recon-structed as one jet due to their proximity to each other. For scenarios with a large mass splitting between the WRand N , up to half of the signal events have only one jet. The WR bo-son invariant mass is reconstructed from the leptons and the two highest pTjets in events with at least two jets, or a sin-gle jet in events with only one jet. Anti-kt jets are massive, and therefore, the jet four-momenta are used in calculating the invariant mass. For the LRSM, the WRboson invariant mass, mj (j ), is required to be greater than 400 GeV for both SS and OS final states.
6 Background estimation
Several processes have the potential to contaminate the sig-nal regions. The main background to the SS dilepton fi-nal state, which is referred to as “fake lepton” background, arises from SM W+ jets, t ¯t, and multi-jet production where one or more jets are misidentified as prompt isolated lep-tons. This background is measured using a data-driven tech-nique rather than using less accurate estimates from MC simulation. The other significant background arises from charge misidentification of a reconstructed electron as a re-sult of hard bremsstrahlung followed by asymmetric conver-sion (e±hard→ e±softγhard→ e±softe±softe∓hard). This background is estimated with a combination of MC and data-driven tech-niques. Small contributions from diboson and single top-quark events are also accounted for using MC.
For the e±e∓and μ±μ∓final states, the dominant back-grounds are Z/γ∗+jets and t ¯t events, with about equal con-tributions after all selection criteria are applied. The e±μ∓ final state is dominated by t¯t production. The backgrounds from t¯t, single top-quark, and diboson production are es-timated from MC simulation, while the estimation of the Z/γ∗+ jets background is extracted from a normalization to the data. The fake lepton background is estimated from data, using the same method as for the SS final states.
A data-driven approach, similar to the one described in Refs. [23, 28], is used to estimate the fake lepton back-ground. The method uses “loose” leptons in addition to the candidate leptons. Loose muons are defined using the same identification criteria as the candidate muons, except for the isolation requirements, which are not applied. For the electrons, looser requirements on the shower shape vari-ables, track-cluster matching, and track quality are used, and the isolation requirement is not applied. The method uses the fractions of these loose fake leptons, Rfake, and loose prompt leptons, Rprompt, which also pass the can-didate lepton requirements. A 4× 4 matrix is then em-ployed on the “loose–loose” and “loose–tight” dilepton sample to predict the total fake lepton background con-tributing to the SS and OS dilepton final states. The Rfake
fractions are measured using fake lepton enriched control regions containing a single loose lepton. Additional cri-teria are imposed to reduce the true lepton contamina-tion from electroweak processes to a negligible level. For events in the control regions, the transverse mass, mT =
2· pT· EmissT · (1 − cos φ(, ETmiss)), is required to be less than 40 GeV. EmissT is defined as the missing trans-verse momentum based on the calorimeter information and the transverse momenta of muons within |η| < 2.7 [46], while φ(, ETmiss) is the azimuthal angle separation be-tween the lepton and the ETmissvectors. Additionally, the fol-lowing requirements are imposed: φ(jet or e, EmissT ) <0.1 for the electron control region and φ(μ, ETmiss) <0.5 for the muon control region. For the muon control region, an additional requirement of at least one jet is imposed. After these criteria are applied, the remaining background from electroweak processes is estimated to be less than 5 %. The Rpromptfractions are measured using Z boson events satis-fying 86 GeV < m<96 GeV via a method referred to as the “tag-and-probe” method. The “tag” lepton is required to satisfy all lepton selection criteria, while the unbiased op-posite charge “probe” lepton should satisfy the loose crite-ria. The Rpromptfractions are parametrized as a function of the lepton pTand range from 89 % to 98 % for muons and 96 % to 99 % for electrons. To improve the accuracy of the prediction, the fractions are parametrized as a function of kinematic variables separately for leptons that pass the anal-ysis trigger requirement and those that do not. The muon Rfake is measured separately for muons that originate from heavy flavor jets and those that do not, where the jet flavor is identified using a combination of the secondary vertex [53] and impact parameter-based [54] b-tagging algorithms. For muons, Rfake ranges from 5 % to 10 % (5 % to 40 %) for heavy flavor (light flavor) jets. For electrons, Rfake ranges from 45 % to 60 %.
A partially data-driven approach is adopted to estimate Z/γ∗ → ee and Z/γ∗ → μμ contributions to the OS dilepton channels. A control region is defined requiring 80 GeV < m<100 GeV and≥1 jets, where non-Z bo-son contributions are found to be negligible. Normaliza-tion factors between the observed number of events in data and the MC prediction are obtained as a function of jet multiplicity from this region and applied to the MC esti-mates in the signal region. All other backgrounds, including Z/γ∗→ ττ , are estimated from MC simulation. The con-tribution of Z/γ∗→ ττ is found to be negligible after all selection criteria are applied. Table1summarises the back-ground estimates for the OS channels. In the OS ee and μμ channels, Z/γ∗+ jets and t ¯t backgrounds dominate, while the t¯t production contributes more than 90 % in the eμ channel. Smaller contributions arise from diboson pro-duction and events with fake leptons.
The fraction of reconstructed electrons with charge mis-identification due to hard bremsstrahlung is measured from simulated Z/γ∗+ jets events, by comparing the MC gener-ated charge of the electron originating from the Z to that of the reconstructed electron candidate. The fraction is parame-trized as a function of the electron ETand η and applied to Z/γ∗→ e+e−and t¯t → e±∓b ¯bMC backgrounds to ob-tain their contributions to the SS dilepton final state, thus benefiting from the large number of simulated OS events. Since the MC overestimates the charge misidentification as observed in the Z/γ∗→ ee data sample, η-dependent scale factors between data and MC simulation are obtained us-ing Z/γ∗→ e±e±events with 80 GeV < m<100 GeV. Both electrons are required to be within the same η range and with the same charge. These factors are applied to the MC estimates. The rate of charge misidentification due to tracking resolution is found to be negligible within the lep-ton transverse momentum range of interest and is well de-scribed by the MC simulation.
All other backgrounds are estimated from MC simulation and found to be small, as shown in Table2. In the SS ee and eμchannels, the dominant background arises from fake lep-tons. The next most significant background is diboson pro-duction for the eμ channel and Z/γ∗production for the ee channel. The SS μμ channel is dominated by the diboson background with a smaller contribution from fake leptons.
7 Systematic uncertainties
The dominant contribution to the systematic uncertainties in the SS ee and eμ channels arises from the fake lep-ton background estimate. As a first step in validating the parametrization of Rfake and Rprompt, a closure test is per-formed in data. Measurements of Rfake and Rpromptare ob-tained by randomly sampling half of the control regions. The predicted values are then compared with the values mea-sured in the other half of the data. The closure test yields an agreement for Rfakeand Rpromptof, respectively,±40 % and±5 % for muons and, for electrons, ±5 % (±20 % for 1 <|η| < 1.9) and ±2 %, which are propagated to the fake lepton background estimate. To evaluate the uncertainty on the overall fake lepton background estimate, the robustness of the procedure is tested against variations across samples. The estimated fake lepton background is compared to the observed background in SS events passing the same selec-tion as events in the signal region but where the sub-leading lepton has a transverse momentum between 15 GeV and 25 GeV. The fake lepton background contributes between 65 % in e±e±to 87 % in e±μ±of the total background. This study tests the reliability of both the parametrization and the use of Rfake and Rprompt to extract the background predic-tion. In this sample, the total background prediction agrees
with the observed data within±10 %. A ±30 % overall sys-tematic uncertainty is assigned to cover for the differences between the predicted and the observed mspectra.
The uncertainties on the background due to the electron charge misidentification arise from the limited number of MC events used to parametrize the rate and the scale factors used to correct the simulation for differences between data and MC and contribute±13 % and ±12 %, respectively.
The background and signal estimates derived from MC are affected by the jet energy scale (JES) calibration and the jet energy resolution (JER), theoretical and MC modelling uncertainties, and pTand η dependent uncertainties on the lepton identification and reconstruction efficiencies (identi-fication±(0.2–3.3) %, pTscale±(0.2–2) % and resolution
±(0.4–10) %) [47,55,56]. The JES (±(2–6) %) and JER (±(5–12) %) uncertainties applied depend on jet pTand η and are measured from the 2010 dataset [52]. An additional contribution of±(2–7) % to the JES uncertainty is added in quadrature to account for the effect of high luminosity
pile-up in the 2011 dataset. MC modelling uncertainties for t¯t production [28] are derived using different MC generators and varying, within their uncertainties, the parameters that control initial and final state radiation. The resulting uncer-tainties are±15 % and ±(5–7) % for t ¯t and diboson contri-butions, respectively.
Due to the limited knowledge of PDFs and αs, the uncer-tainties are evaluated using a range of current PDF sets with the procedure described in Ref. [57]. The final uncertainty is taken from the outer bounds of the overall error bands. The PDF uncertainties are estimated to be±9 % for the LRSM signal and±12 % for the HNEO signals.
8 Results and interpretation
The expected and observed numbers of events in each dilep-ton final state for the baseline selection and the LRSM se-lections are compared in Tables 1 and 2 for the OS and
Table 1 Summary of the expected background yields and observed
numbers of events for the OS dilepton channels. The top part of the table shows the numbers obtained for events with two leptons,≥1 jet,
m>110 GeV, and ST>400 GeV. The bottom part of the table
shows the numbers for the final LRSM selection, where an additional
requirement mj (j )≥ 400 GeV is imposed. The quoted uncertainties
include statistical and systematic components, excluding the luminos-ity uncertainty of±3.7 %. The latter is relevant for all backgrounds except for the fake lepton(s) background, which is measured using data
Physics processes e±e∓ μ±μ∓ e±μ∓ Total
Z/γ∗+ jets 136.1± 12.5 173.2± 15.1 0.8± 0.8 310± 20 Diboson 4.3± 1.8 7.3± 1.9 5.9± 1.6 18± 3 Top 103.1± 12.3 100.9± 12.0 199.4± 23.3 403± 46 Fake lepton(s) 12.5± 8.1 −0.2 ± 0.7 6.1± 4.2 18± 9 Total background 256.0± 26.2 281.2± 27.9 212.3± 33.8 750± 78 Observed events 248 245 247 740 mj (j )≥ 400 GeV Total background 254.8± 25.8 279.7± 27.6 210.9± 33.4 745± 77 Observed events 246 241 244 731
Table 2 Summary of the expected background yields and observed
numbers of events for the SS dilepton channels. The top part of the table shows the numbers obtained for events with two leptons,≥ 1 jet and m>110 GeV. The bottom part of the table shows the
num-bers for the final LRSM selection, where an additional requirement
mj (j )≥ 400 GeV is imposed. The quoted uncertainties include
statis-tical and systematic components, excluding the luminosity uncertainty of±3.7 %. The latter is relevant for all backgrounds except for the fake lepton(s) background, which is measured using data
Physics processes e±e± μ±μ± e±μ± Total
Z/γ∗+ jets 26.1± 5.6 0.0+1.6−0 1.2± 0.7 27± 6 Diboson 12.7± 2.3 7.2± 1.7 18.8± 3.0 39± 6 Top 5.8± 1.3 0.7± 0.3 6.8± 1.6 13± 3 Fake lepton(s) 93.6± 35.7 3.1± 1.6 53.8± 20.3 151± 50 Total background 138.3± 36.5 11.0+2.9−2.5 80.7± 20.8 230± 52 Observed events 155 14 99 268 mj (j )≥ 400 GeV Total background 48.4± 16.1 4.4+2.1−1.3 24.6± 7.6 77± 21 Observed events 59 8 39 106
SS events, respectively. Additionally, the reconstructed ma-sses of the N and WR candidates, mj (j ) and, mj (j ) re-spectively, are examined in each dilepton channel. Figures1 and2show those distributions for the OS and SS channels (ee, μμ, and eμ combined).
Given the good agreement between the data and the ex-pectations from SM processes, the results are used to set limits at 95 % C.L. on the visible cross section, σA, where σ is the cross section for new phenomena,A is the accep-tance (i.e. the fraction of events passing geometric and kine-matic selection requirements at the particle level), and is the efficiency (i.e. the detector reconstruction and identifica-tion efficiency). For the HNEO model,A is about 10 % for mN= 0.1 TeV and reaches a plateau value of about 28 % at around mN= 0.8 TeV, for all six dilepton channels. For
Fig. 1 Distributions of the reconstructed N invariant mass, mj (j ),
for OS (top) and SS (bottom) dilepton events with ≥1 jets and
m>110 GeV. A selection criterion ST≥ 400 GeV is used for the
OS selection. The hypothetical signal distributions for mN= 0.3 TeV
forOV and Λ/√α= 2 TeV are superimposed
the LRSM,A varies between 40 % and 65 % across the (mWR, mN) plane. The lowestA occurs for small mN. It should be noted that the difference inA between the two models is dominated by the fact the decays to τ leptons are included in generating the HNEO samples, while only de-cays to e and μ are included in the LRSM samples. Table3 quotes the limits obtained for each channel, after the base-line selection.
The resulting limits for the interpretation of the data in terms of the HNEO and LRSM models are derived using as templates the reconstructed masses of the N and WR candi-dates in each dilepton channel. The baseline selection is used for the HNEO model, while the additional cut of mj (j ) is applied for the LRSM model. Systematic uncertainties
Fig. 2 Distributions of the reconstructed WRinvariant mass, mj (j ),
for OS (top) and SS (bottom) dilepton events with ≥1 jets,
m >110 GeV, and mj (j ) ≥ 400 GeV. A selection criterion
ST≥ 400 GeV is used for the OS selection. The hypothetical signal
distributions for mWR= 1.2 TeV and mN= 0.1 TeV (mWR= 1.5 TeV and mN= 0.8 TeV) for the case of maximal mixing, are superimposed
Table 3 Observed (obs) and expected (exp) 95 % C.L. upper limits
on the visible cross section,σA 95, for each OS and SS dilepton channel after the baseline selection
Channels σA 95obs[fb] σA 95exp[fb]
e±e∓ 28.6 31.0 μ±μ∓ 25.1 36.7 e±μ∓ 50.9 36.4 e±e± 37.6 29.6 μ±μ± 6.1 4.6 e±μ± 25.4 16.2
Fig. 3 Expected and observed 95 % C.L. upper limits on Λ/√αas a function of the mass of a heavy neutrino, for the operators OV, Os1/Os2, andOs3, using the formalism of Lagrangian of effective
op-erators, for the Majorana (top) and Dirac (bottom) scenarios
from JES and JER are included as variations in the signal and background templates. The uncertainties on the mea-surement of Rfake and Rpromptare included as variations in the fake lepton background templates. All other uncertain-ties have no significant kinematic dependence. Correlations of uncertainties between signal and background, as well as across channels, are taken into account.
The 95 % C.L. exclusion limits on the mass of the heavy neutrino in the HNEO model and their dependence
Fig. 4 Expected and observed 95 % C.L. upper limits on the heavy
neutrino and WR masses for the Majorana (top) and Dirac (bottom)
cases, in the no-mixing and maximal-mixing scenarios
on Λ/√αare shown in Fig.3 for the Majorana and Dirac scenarios using various effective operator hypotheses. Fig-ure 4 shows the exclusion limits for the masses of heavy neutrinos and the WRboson in the LRSM interpretation, for the no-mixing and maximal-mixing scenarios between Ne and Nμ neutrinos, for both the Majorana and Dirac heavy neutrinos hypotheses.
The above results are obtained with a Bayesian [58] ap-proach, where systematic uncertainties are treated as nui-sance parameters with a truncated Gaussian as a prior shape. The prior shape on the parameters of interest, σ× BR, is as-sumed to be flat.
9 Conclusions
A dedicated search for hypothetical heavy Majorana and Dirac neutrinos, and WR bosons in final states with two high-pT same-sign or opposite-sign leptons and hadronic jets has been presented. In a data sample corresponding to an integrated pp luminosity of 2.1 fb−1 at √s= 7 TeV, no significant deviations from the SM expectations are ob-served, and 95 % C.L. limits are set on the contributions
of new physics. Excluded mass regions for Majorana and Dirac neutrinos are presented for various operators of an ef-fective Lagrangian framework and for the LRSM. The latter interpretation was used to extract a lower limit on the mass of the gauge boson WR. For both no-mixing and maximal-mixing scenarios, WRbosons with masses below≈1.8 TeV (≈2.3 TeV) are excluded for mass differences between the WRand N masses larger than 0.3 TeV (0.9 TeV). In the ef-fective Lagrangian interpretation, considering the vector op-erator and Majorana-type heavy neutrinos, the lower limit on Λ/√αranges from≈2.5 TeV to ≈0.7 TeV for heavy neu-trino masses ranging from 0.1 TeV to 2.7 TeV. Comparable limits are obtained for Dirac-type neutrinos in both models. The results described represent the most stringent limits to date on the masses of heavy neutrinos and WR boson ob-tained in direct searches.
Acknowledgements We thank CERN for the very successful oper-ation 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, Ar-menia; ARC, Australia; BMWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIEN-CIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Repub-lic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET and ERC, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNAS, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Ger-many; GSRT, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slo-vakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United King-dom; DOE and NSF, United States of America.
The crucial computing support from all WLCG partners is ac-knowledged 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 Cre-ative Commons Attribution License which permits any use, distribu-tion, and reproduction in any medium, provided the original author(s) and the source are credited.
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J.R. Carter27, J. Carvalho123a,h, D. Casadei107, M.P. Casado11, M. Cascella121a,121b, C. Caso50a,50b,*, A.M. Castaneda Her-nandez171, E. Castaneda-Miranda171, V. Castillo Gimenez166, N.F. Castro123a, G. Cataldi71a, F. Cataneo29, A. Catinaccio29, J.R. Catmore29, A. Cattai29, G. Cattani132a,132b, S. Caughron87, D. Cauz163a,163c, P. Cavalleri77, D. Cavalli88a, M. Cavalli-Sforza11, V. Cavasinni121a,121b, F. Ceradini133a,133b, A.S. Cerqueira23b, A. Cerri29, L. Cerrito74, F. Cerutti47, S.A. Cetin18b, F. Cevenini101a,101b, A. Chafaq134a, D. Chakraborty105, K. Chan2, B. Chapleau84, J.D. Chapman27, J.W. Chapman86, E. Chareyre77, D.G. Charlton17, V. Chavda81, C.A. Chavez Barajas29, S. Cheatham84, S. Chekanov5, S.V. Chekulaev158a, G.A. Chelkov64, M.A. Chelstowska103, C. Chen63, H. Chen24, S. Chen32c, T. Chen32c, X. Chen171, S. Cheng32a, A. Chep-lakov64, V.F. Chepurnov64, R. Cherkaoui El Moursli134e, V. Chernyatin24, E. Cheu6, S.L. Cheung157, L. Chevalier135, G. Chiefari101a,101b, L. Chikovani51a, J.T. Childers29, A. Chilingarov70, G. Chiodini71a, A.S. Chisholm17, M.V. Chizhov64, G. Choudalakis30, S. Chouridou136, I.A. Christidi76, A. Christov48, D. Chromek-Burckhart29, M.L. Chu150, J. Chudoba124, G. Ciapetti131a,131b, K. Ciba37, A.K. Ciftci3a, R. Ciftci3a, D. Cinca33, V. Cindro73, M.D. Ciobotaru162, C. Ciocca19a, A. Ciocio14, M. Cirilli86, M. Citterio88a, M. Ciubancan25a, A. Clark49, P.J. Clark45, W. Cleland122, J.C. Clemens82, B. Clement55, C. Clement145a,145b, R.W. Clifft128, Y. Coadou82, M. Cobal163a,163c, A. Coccaro171, J. Cochran63, P. Coe117, J.G. Cogan142, J. Coggeshall164, E. Cogneras176, J. Colas4, A.P. Colijn104, N.J. Collins17, C. Collins-Tooth53, J. Col-lot55, G. Colon83, P. Conde Muiño123a, E. Coniavitis117, M.C. Conidi11, M. Consonni103, V. Consorti48, S. Constanti-nescu25a, C. Conta118a,118b, F. Conventi101a,i, J. Cook29, M. Cooke14, B.D. Cooper76, A.M. Cooper-Sarkar117, K. Copic14, T. Cornelissen173, M. Corradi19a, F. Corriveau84,j, A. Cortes-Gonzalez164, G. Cortiana98, G. Costa88a, M.J. Costa166, D. Costanzo138, T. Costin30, D. Côté29, R. Coura Torres23a, L. Courneyea168, G. Cowan75, C. Cowden27, B.E. Cox81, K. Cranmer107, F. Crescioli121a,121b, M. Cristinziani20, G. Crosetti36a,36b, R. Crupi71a,71b, S. Crépé-Renaudin55, C.-M. Cu-ciuc25a, C. Cuenca Almenar174, T. Cuhadar Donszelmann138, M. Curatolo47, C.J. Curtis17, C. Cuthbert149, P. Cwetanski60, H. Czirr140, P. Czodrowski43, Z. Czyczula174, S. D’Auria53, M. D’Onofrio72, A. D’Orazio131a,131b, P.V.M. Da Silva23a, C. Da Via81, W. Dabrowski37, T. Dai86, C. Dallapiccola83, M. Dam35, M. Dameri50a,50b, D.S. Damiani136, H.O. Daniels-son29, D. Dannheim98, V. Dao49, G. Darbo50a, G.L. Darlea25b, W. Davey20, T. Davidek125, N. Davidson85, R. Davidson70, E. Davies117,c, M. Davies92, A.R. Davison76, Y. Davygora58a, E. Dawe141, I. Dawson138, J.W. Dawson5,*, R.K. Daya-Ishmukhametova22, K. De7, R. de Asmundis101a, S. De Castro19a,19b, P.E. De Castro Faria Salgado24, S. De Cecco77, J. de Graat97, N. De Groot103, P. de Jong104, C. De La Taille114, H. De la Torre79, B. De Lotto163a,163c, L. de Mora70, L. De Nooij104, D. De Pedis131a, A. De Salvo131a, U. De Sanctis163a,163c, A. De Santo148, J.B. De Vivie De Regie114, S. Dean76, W.J. Dearnaley70, R. Debbe24, C. Debenedetti45, D.V. Dedovich64, J. Degenhardt119, M. Dehchar117, C. Del Papa163a,163c, J. Del Peso79, T. Del Prete121a,121b, T. Delemontex55, M. Deliyergiyev73, A. Dell’Acqua29, L. Dell’Asta21, M. Della Pietra101a,i, D. della Volpe101a,101b, M. Delmastro4, N. Delruelle29, P.A. Delsart55, C. Deluca147, S. Demers174, M. Demichev64, B. Demirkoz11,k, J. Deng162, S.P. Denisov127, D. Derendarz38, J.E. Derkaoui134d, F. Derue77, P. Dervan72, K. Desch20, E. Devetak147, P.O. Deviveiros104, A. Dewhurst128, B. DeWilde147, S. Dhaliwal157, R. Dhul-lipudi24,l, A. Di Ciaccio132a,132b, L. Di Ciaccio4, A. Di Girolamo29, B. Di Girolamo29, S. Di Luise133a,133b, A. Di Mattia171, B. Di Micco29, R. Di Nardo47, A. Di Simone132a,132b, R. Di Sipio19a,19b, M.A. Diaz31a, F. Diblen18c, E.B. Diehl86, J. Diet-rich41, T.A. Dietzsch58a, S. Diglio85, K. Dindar Yagci39, J. Dingfelder20, C. Dionisi131a,131b, P. Dita25a, S. Dita25a, F. Dit-tus29, F. Djama82, T. Djobava51b, M.A.B. do Vale23c, A. Do Valle Wemans123a, T.K.O. Doan4, M. Dobbs84, R. Dobinson29,*, D. Dobos29, E. Dobson29,m, J. Dodd34, C. Doglioni49, T. Doherty53, Y. Doi65,*, J. Dolejsi125, I. Dolenc73, Z. Dolezal125, B.A. Dolgoshein95,*, T. Dohmae154, M. Donadelli23d, M. Donega119, J. Donini33, J. Dopke29, A. Doria101a, A. Dos An-jos171, M. Dosil11, A. Dotti121a,121b, M.T. Dova69, J.D. Dowell17, A.D. Doxiadis104, A.T. Doyle53, Z. Drasal125, J. Drees173,
N. Dressnandt119, H. Drevermann29, C. Driouichi35, M. Dris9, J. Dubbert98, S. Dube14, E. Duchovni170, G. Duckeck97, A. Dudarev29, F. Dudziak63, M. Dührssen29, I.P. Duerdoth81, L. Duflot114, M-A. Dufour84, M. Dunford29, H. Duran Yildiz3a, R. Duxfield138, M. Dwuznik37, F. Dydak29, M. Düren52, W.L. Ebenstein44, J. Ebke97, S. Eckweiler80, K. Edmonds80, C.A. Edwards75, N.C. Edwards53, W. Ehrenfeld41, T. Ehrich98, T. Eifert142, G. Eigen13, K. Einsweiler14, E.
Eisenhan-dler74, T. Ekelof165, M. El Kacimi134c, M. Ellert165, S. Elles4, F. Ellinghaus80, K. Ellis74, N. Ellis29, J. Elmsheuser97, M. Elsing29, D. Emeliyanov128, R. Engelmann147, A. Engl97, B. Epp61, A. Eppig86, J. Erdmann54, A. Ereditato16, D. Eriksson145a, J. Ernst1, M. Ernst24, J. Ernwein135, D. Errede164, S. Errede164, E. Ertel80, M. Escalier114, C. Esco-bar122, X. Espinal Curull11, B. Esposito47, F. Etienne82, A.I. Etienvre135, E. Etzion152, D. Evangelakou54, H. Evans60, L. Fabbri19a,19b, C. Fabre29, R.M. Fakhrutdinov127, S. Falciano131a, Y. Fang171, M. Fanti88a,88b, A. Farbin7, A. Farilla133a,
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Fil-ipˇciˇc73, A. Filippas9, F. Filthaut103, M. Fincke-Keeler168, M.C.N. Fiolhais123a,h, L. Fiorini166, A. Firan39, G. Fischer41, P. Fischer20, M.J. Fisher108, M. Flechl48, I. Fleck140, J. Fleckner80, P. Fleischmann172, S. Fleischmann173, T. Flick173, A. Floderus78, L.R. Flores Castillo171, M.J. Flowerdew98, M. Fokitis9, T. Fonseca Martin16, D.A. Forbush137, A. Formica135, A. Forti81, D. Fortin158a, J.M. Foster81, D. Fournier114, A. Foussat29, A.J. Fowler44, K. Fowler136, H. Fox70, P. Fran-cavilla11, S. Franchino118a,118b, D. Francis29, T. Frank170, M. Franklin57, S. Franz29, M. Fraternali118a,118b, S. Fratina119, S.T. French27, F. Friedrich43, R. Froeschl29, D. Froidevaux29, J.A. Frost27, C. Fukunaga155, E. Fullana Torregrosa29, J. Fuster166, C. Gabaldon29, O. Gabizon170, T. Gadfort24, S. Gadomski49, G. Gagliardi50a,50b, P. Gagnon60, C. Galea97, E.J. Gallas117, V. Gallo16, B.J. Gallop128, P. Gallus124, K.K. Gan108, Y.S. Gao142,e, V.A. Gapienko127, A. Gaponenko14, F. Garberson174, M. Garcia-Sciveres14, C. García166, J.E. García Navarro166, R.W. Gardner30, N. Garelli29, H. Garitaonan-dia104, V. Garonne29, J. Garvey17, C. Gatti47, G. Gaudio118a, B. Gaur140, L. Gauthier135, I.L. Gavrilenko93, C. Gay167, G. Gaycken20, J-C. Gayde29, E.N. Gazis9, P. Ge32d, C.N.P. Gee128, D.A.A. Geerts104, Ch. Geich-Gimbel20, K. Geller-stedt145a,145b, C. Gemme50a, A. Gemmell53, M.H. Genest55, S. Gentile131a,131b, M. George54, S. George75, P. Ger-lach173, A. Gershon152, C. Geweniger58a, H. Ghazlane134b, N. Ghodbane33, B. Giacobbe19a, S. Giagu131a,131b, V. Giak-oumopoulou8, V. Giangiobbe11, F. Gianotti29, B. Gibbard24, A. Gibson157, S.M. Gibson29, L.M. Gilbert117, V. Gilewsky90, D. Gillberg28, A.R. Gillman128, D.M. Gingrich2,d, J. Ginzburg152, N. Giokaris8, M.P. Giordani163c, R. Giordano101a,101b, F.M. Giorgi15, P. Giovannini98, P.F. Giraud135, D. Giugni88a, M. Giunta92, P. Giusti19a, B.K. Gjelsten116, L.K. Gladilin96, C. Glasman79, J. Glatzer48, A. Glazov41, K.W. Glitza173, G.L. Glonti64, J.R. Goddard74, J. Godfrey141, J. Godlewski29, M. Goebel41, T. Göpfert43, C. Goeringer80, C. Gössling42, T. Göttfert98, S. Goldfarb86, T. Golling174, A. Gomes123a,b, L.S. Gomez Fajardo41, R. Gonçalo75, J. Goncalves Pinto Firmino Da Costa41, L. Gonella20, A. Gonidec29, S. Gonza-lez171, S. González de la Hoz166, G. Gonzalez Parra11, M.L. Gonzalez Silva26, S. Gonzalez-Sevilla49, J.J. Goodson147, L. Goossens29, P.A. Gorbounov94, H.A. Gordon24, I. Gorelov102, G. Gorfine173, B. Gorini29, E. Gorini71a,71b, A. Gorišek73, E. Gornicki38, S.A. Gorokhov127, V.N. Goryachev127, B. Gosdzik41, M. Gosselink104, M.I. Gostkin64, I. Gough Es-chrich162, M. Gouighri134a, D. Goujdami134c, M.P. Goulette49, A.G. Goussiou137, C. Goy4, S. Gozpinar22, I. Grabowska-Bold37, P. Grafström29, K-J. Grahn41, F. Grancagnolo71a, S. Grancagnolo15, V. Grassi147, V. Gratchev120, N. Grau34, H.M. Gray29, J.A. Gray147, E. Graziani133a, O.G. Grebenyuk120, T. Greenshaw72, Z.D. Greenwood24,l, K. Gregersen35, I.M. Gregor41, P. Grenier142, J. Griffiths137, N. Grigalashvili64, A.A. Grillo136, S. Grinstein11, Y.V. Grishkevich96, J.-F. Grivaz114, M. Groh98, E. Gross170, J. Grosse-Knetter54, J. Groth-Jensen170, K. Grybel140, V.J. Guarino5, D. Guest174, C. Guicheney33, A. Guida71a,71b, S. Guindon54, H. Guler84,n, J. Gunther124, B. Guo157, J. Guo34, A. Gupta30, Y. Gusakov64, V.N. Gushchin127, P. Gutierrez110, N. Guttman152, O. Gutzwiller171, C. Guyot135, C. Gwenlan117, C.B. Gwilliam72, A. Haas142, S. Haas29, C. Haber14, H.K. Hadavand39, D.R. Hadley17, P. Haefner98, F. Hahn29, S. Haider29, Z. Hajduk38, H. Hakobyan175, D. Hall117, J. Haller54, K. Hamacher173, P. Hamal112, M. Hamer54, A. Hamilton144b,o, S. Hamilton160, H. Han32a, L. Han32b, K. Hanagaki115, K. Hanawa159, M. Hance14, C. Handel80, P. Hanke58a, J.R. Hansen35, J.B. Hansen35, J.D. Hansen35, P.H. Hansen35, P. Hansson142, K. Hara159, G.A. Hare136, T. Harenberg173, S. Harkusha89, D. Harper86, R.D. Harrington45, O.M. Harris137, K. Harrison17, J. Hartert48, F. Hartjes104, T. Haruyama65, A. Harvey56, S. Hasegawa100, Y. Hasegawa139, S. Hassani135, M. Hatch29, D. Hauff98, S. Haug16, M. Hauschild29, R. Hauser87, M. Havranek20, B.M. Hawes117, C.M. Hawkes17, R.J. Hawkings29, A.D. Hawkins78, D. Hawkins162, T. Hayakawa66, T. Hayashi159, D. Hay-den75, H.S. Hayward72, S.J. Haywood128, E. Hazen21, M. He32d, S.J. Head17, V. Hedberg78, L. Heelan7, S. Heim87, B. Heinemann14, S. Heisterkamp35, L. Helary4, C. Heller97, M. Heller29, S. Hellman145a,145b, D. Hellmich20, C. Helsens11, R.C.W. Henderson70, M. Henke58a, A. Henrichs54, A.M. Henriques Correia29, S. Henrot-Versille114, F. Henry-Couannier82,
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