Measurement of jet activity in top quark events using the eμ final state with two b -tagged jets in pp collisions at s √ =8 TeV with the ATLAS detector
EEUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
JHEP 09 (2016) 074DOI: 10.1007/JHEP09(2016)074 CERN-EP-2016-1229th May 2018
Measurement of jet activity in top quark events using the e µ finalstate with two b -tagged jets in pp collisions at √ s = The ATLAS Collaboration
Abstract
Measurements of the jet activity in t ¯ t events produced in proton–proton collisions at √ s = − of data collected by the ATLAS experiment at theLarge Hadron Collider. The events were selected in the dilepton e µ decay channel withtwo identified b -jets. The numbers of additional jets for various jet transverse momentum( p T ) thresholds, and the normalised di ff erential cross-sections as a function of p T for the fivehighest- p T additional jets, were measured in the jet pseudorapidity range | η | < .
5. The gapfraction, the fraction of events which do not contain an additional jet in a central rapidity re-gion, was measured for several rapidity intervals as a function of the minimum p T of a singlejet or the scalar sum of p T of all additional jets. These fractions were also measured in di ff er-ent intervals of the invariant mass of the e µ b ¯ b system. All measurements were corrected fordetector e ff ects, and found to be mostly well-described by predictions from next-to-leading-order and leading-order t ¯ t event generators with appropriate parameter choices. The resultscan be used to further optimise the parameters used in such generators. c (cid:13) a r X i v : . [ h e p - e x ] S e p Introduction
The top quark plays a special role in the Standard Model and in some theories of physics beyond theStandard Model. The large top quark mass and large t ¯ t pair-production cross-section in pp collisions(242 ±
10 pb at √ s = b -quarks also make such events a primary source of back-ground in many searches for new physics. Therefore, the development of accurate modelling for eventsinvolving top quark production forms an important part of the LHC physics programme. Measurementsof the activity of additional jets in t ¯ t events, i.e. jets not originating from the decay of the top quark andantiquark, but arising from quark and gluon radiation produced in association with the t ¯ t system, havebeen made by ATLAS [2, 3] and CMS [4] using pp data at √ s = √ s = ffi ciency and resolution e ff ects, and compared to the predictions of Monte Carlo (MC)generators through tools such as the R ivet framework [6]. Such comparisons indicate that some state-of-the-art generators have di ffi culties in reproducing the data, whilst for others agreement with data can beimproved with an appropriate choice of generator parameter values or ‘tune’, including those controllingQCD factorisation and renormalisation scales, and matching to the parton shower [7–11].This paper presents two studies of the additional jet activity in t ¯ t events collected with the ATLAS detectorin pp collisions at a centre-of-mass energy of √ s = e µ final state with two jets identified (‘tagged’) as likely to contain b -hadrons. Distributions of the properties of additional jets in these events are normalised to the cross-section ( σ e µ b ¯ b ) for events passing this initial selection, requiring the electron, muon and two b -tagged jetsto have transverse momentum p T >
25 GeV and pseudorapidity | η | < . | η | < . p T >
25 GeV are measured di ff erentially in jet rank and p T ;1 σ d σ i d p T ≡ σ e µ b ¯ b d σ jet i d p T , (1)with rank i = i = p T ) additional jet. These normaliseddi ff erential cross-sections are then used to obtain the multiplicity distributions for additional jets as afunction of the minimum p T threshold for such extra jets.The additional-jet di ff erential cross-section measurements are complemented by a second study measur-ing the jet ‘gap fraction’, i.e. the fraction of events where no additional jet is present within a particularinterval of jet rapidity, denoted by ∆ y . The gap fraction is measured as a function of the jet p T threshold, Q ; f ( Q ) ≡ σ ( Q ) σ e µ b ¯ b , (2) ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point in the centre of the detector,and the z axis along the beam line. Pseudorapidity is defined in terms of the polar angle θ as η = − ln tan θ/
2, and transversemomentum and energy are defined relative to the beamline as p T = p sin θ and E T = E sin θ . The azimuthal angle around thebeam line is denoted by φ , and distances in ( η, φ ) space by ∆ R = (cid:112) ( ∆ η ) + ( ∆ φ ) . The rapidity is defined as y = ln (cid:16) E + p z E − p z (cid:17) ,where p z is the z -component of the momentum and E is the energy of the relevant object. Q of 25 GeV, where σ ( Q ) is the cross-section for events having no additionaljets with p T > Q , within the rapidity interval ∆ y . Following the corresponding measurement at √ s = ∆ y are defined: | y | < .
8, 0 . < | y | < .
5, 1 . < | y | < . | y | < .
1. These intervals are more restrictive than for the normalised additional jet cross-sections,which are measured over the wider angular range | η | < . f ( Q ), the gap fraction is measured as a function of a threshold Q sum placed on the scalar sumof the p T of all additional jets with p T >
25 GeV within the same rapidity intervals ∆ y : f ( Q sum ) ≡ σ ( Q sum ) σ e µ b ¯ b . (3)The gap fraction measured as a function of Q is sensitive to the leading p T emission accompanyingthe t ¯ t system, whereas the gap fraction based on Q sum is sensitive to all accompanying hard emissions.Finally, the gap fractions f ( Q ) and f ( Q sum ) in the inclusive rapidity region | y | < . e µ b ¯ b system m e µ b ¯ b , which is related to the invariantmass of the produced t ¯ t system and is on average higher if produced from quark–antiquark rather thangluon–gluon initial states.This paper is organised as follows. Section 2 describes the ATLAS detector and the data sample usedfor these measurements. Section 3 provides information about the Monte Carlo simulated samples usedto model signal and background processes, and to compare with the measured results. The commonobject and event selection criteria are presented in Section 4, and sources of systematic uncertainty arediscussed in Section 5. The measurement of the normalised jet di ff erential cross-sections by rank and p T is described in Section 6 and the measurement of the gap fraction is presented in Section 7, in both casesincluding comparisons with the predictions of various t ¯ t event generators. Section 8 gives a summary andconclusions. The ATLAS detector [12] at the LHC covers almost the full solid angle around the collision point, andconsists of an inner tracking detector surrounded by a thin superconducting solenoid magnet producing a2 T axial magnetic field, electromagnetic and hadronic calorimeters, and an external muon spectrometerincorporating three large toroidal magnet systems. The inner detector consists of a high-granularity siliconpixel detector and a silicon microstrip tracker, together providing precision tracking in the pseudorapidityrange | η | < .
5, complemented by a transition radiation tracker providing tracking and electron identific-ation information for | η | < .
0. A lead / liquid-argon (LAr) electromagnetic calorimeter covers the region | η | < .
2, and hadronic calorimetry is provided by steel / scintillator tile calorimeters for | η | < . / LAr hadronic endcap calorimeters covering 1 . < | η | < .
2. The calorimeter system is completed byforward LAr calorimeters with copper and tungsten absorbers which extend the coverage to | η | = .
9. Themuon spectrometer consists of precision tracking chambers covering the region | η | < .
7, and separatetrigger chambers covering | η | < .
4. A three-level trigger system, using custom hardware followed bytwo software-based levels, is used to reduce the event rate to about 400 Hz for o ffl ine storage.The analyses were performed on the 2012 ATLAS proton–proton collision data sample, correspondingto an integrated luminosity of 20.3 fb − at √ s = ffi ciency plateau is reached for leptons with p T >
25 GeV passing o ffl ine selections. Eachtriggered event also includes the signals from an average of 20 additional inelastic pp collisions in thesame bunch crossing (referred to as pile-up). Monte Carlo simulated event samples were used to evaluate signal e ffi ciencies and backgrounds, and toestimate and correct for resolution e ff ects. The samples were processed either through the full ATLASdetector simulation [14] based on GEANT4 [15], or through a faster simulation making use of para-meterised showers in the calorimeters [16]. Additional simulated inelastic pp collisions, generated withP ythia ff ects of both in- and out-of-time pile-up, from additional activity in thesame and nearby bunch crossings. The resulting simulated events were processed using the same recon-struction algorithms and analysis chains as the data. The e ff ects of pile-up were also studied with datarecorded from randomly selected bunch crossings (zero-bias data) as discussed in Section 5.The baseline t ¯ t full simulation sample was produced using the next-to-leading-order (NLO) QCD matrix-element generator P owheg -B ox v1.0 [20–22] using the CT10 PDFs [23] and interfaced to P ythia (cid:113) m t + p , the sum in quadrature of the top quark mass m t and transverse momentum p T , the latter evaluated for the underlying Born configuration before radiation.The P owheg parameter h damp , used in the damping function that limits the resummation of higher-ordere ff ects incorporated into the Sudakov form factor, was set to infinity, corresponding to no damping. Thetop quark mass was set to 172.5 GeV. The total t ¯ t production cross-section, used when comparing pre-dictions from simulation with data, was taken to be 253 + − pb, based on the next-to-next-to-leading-order(NNLO) calculation including the resummation of next-to-next-to-leading logarithmic soft gluon termsas described in Refs. [27–31] and implemented in the Top ++ α s uncertainties based on the PDF4LHC prescription [33] applied to the MSTW2008NNLO [18, 34], CT10 NNLO [23, 35] and NNPDF2.3 5f FFN [36] PDF sets, added in quadrature to theQCD scale uncertainty.Alternative t ¯ t simulation samples were used to evaluate systematic uncertainties, and were comparedwith the data measurements after unfolding for detector e ff ects. Samples were produced with P owheg with h damp = ∞ interfaced to H erwig (version 6.520) [37, 38] with the ATLAS AUET2 tune [39] andJ immy (version 4.31) [40] for underlying-event modelling. Samples with h damp = m t , which softens the t ¯ tp T spectrum, improving the agreement between data and simulation at √ s = owheg with either P ythia ythia erwig and J immy , with the generator’s default renormalisation and factorisation scales of (cid:113) m t + ( p , t + p , ¯ t ) / p T , t and p T , ¯ t are the transverse momenta of the top quark and antiquark. Several leading-order4multi-leg’ generators were also studied. The A lpgen generator (version 2.13) [44] was used with leading-order matrix elements for t ¯ t production accompanied by up to three additional light partons, and dedicatedmatrix elements for t ¯ t plus b ¯ b or c ¯ c production, interfaced to H erwig and J immy . An alternative samplewas generated with A lpgen interfaced to P ythia ad G raph ythia t ¯ t eventswere used, generated using A cer MC (version 3.8) [46], A lpgen or M ad G raph , each interfaced to P ythia t ¯ t gap fraction measurements at √ s = e µ b ¯ b event selection, the expected non- t ¯ t contribution is dominated by Wt , the associated pro-duction of a W boson and a single top quark. This process is distinct from t ¯ t production when consideredat leading order. But at NLO in QCD the two processes cannot be separated once the top quarks decayto Wb : the resulting WbW ¯ b final state can appear for example through both gg → t ¯ t → WbW ¯ b and gg → Wt ¯ b → WbW ¯ b , and the two processes interfere to an extent depending on the kinematics of thefinal state. However, the currently available generators do not allow a full treatment of this interference;instead they consider t ¯ t and Wt production as separate processes. Within this approximation, the ‘dia-gram removal’ and ‘diagram subtraction’ schemes have been proposed as alternatives for approximatelyhandling the interference between the t ¯ t and Wt processes [47, 48]. For this paper, Wt production wassimulated as a process separate from t ¯ t , using P owheg + P ythia . ± . Wt production,determined by using the approximate NNLO prediction described in Ref. [49].Other backgrounds with two prompt leptons arise from diboson production ( WW , WZ and ZZ ) accom-panied by b -tagged jets, modelled using A lpgen + H erwig + J immy with CTEQ6L1 PDFs and with totalcross-sections calculated using MCFM [50]; and Z → ττ ( → e µ ) + jets, modelled using A lpgen + P ythia Zb ¯ b production. The normalisa-tion of this background was determined from data using Z → ee /µµ events with two b -tagged jets asdescribed in Ref. [1]. The remaining background originates from events with one prompt and one misid-entified lepton, e.g. a non-prompt lepton from the decay of a bottom or charm hadron, an electron froma photon conversion, hadronic jet activity misidentified as an electron, or a muon produced from an in-flight decay of a pion or kaon. Such events can arise from t ¯ t production with one hadronically decaying W , modelled as for dileptonic t ¯ t production with P owheg + P ythia W + jets production, modelled as for Z + jets; and t -channel single-top production, modelled using A cer MC + P ythia e µ b ¯ b events with one real and one misidentified lepton [1]. The expected contributions tothe additional-jet distributions from t ¯ t production in association with a W , Z or Higgs boson are below thepercent level. Other backgrounds, including processes with two misidentified leptons, are negligible.5 Object and event selection
The two analyses use the same object and event selection as employed in the ATLAS inclusive t ¯ t cross-section analysis at √ s = E T >
25 GeV and pseudorapidity | η | < .
47, and to be isolated to reduce backgroundsfrom non-prompt and misidentified electrons. Electron candidates within the transition region betweenthe barrel and endcap electromagnetic calorimeters, 1 . < | η | < .
52, were removed. Muons wereidentified as described in Ref. [52], required to have p T >
25 GeV and | η | < .
5, and also required to beisolated.Jets were reconstructed using the anti- k t algorithm [53, 54] with radius parameter R = .
4, starting fromclusters of energy deposits in the calorimeters, calibrated using the local cluster weighting method [55].Jets were calibrated using an energy- and η -dependent simulation-based scheme, with the e ff ects of pile-up on the jet energy measurement being reduced using the jet-area method described in Ref. [56]. Afterthe application of in situ corrections based on data [57], jets were required to satisfy p T >
25 GeV and | η | < .
5. To suppress the contribution from low- p T jets originating from pile-up interactions, a jet vertexfraction (JVF) requirement was applied to jets with p T <
50 GeV and | η | < . p T of tracks associated with the jet originatingfrom tracks associated with the event primary vertex, the latter being defined as the reconstructed vertexwith the highest sum of associated track p . Jets with no associated tracks were also selected. To preventdouble-counting of electron energy deposits as jets, jets within ∆ R = . ∆ R = . b -hadrons were tagged using the MV1 algorithm, a multivariate discriminant making useof track impact parameters and reconstructed secondary vertices [59]. Jets were defined to be b -tagged ifthe MV1 discriminant value was larger than a threshold corresponding to a 70 % e ffi ciency for tagging b -quark jets in t ¯ t events, giving a rejection factor of about 140 against light-quark and gluon jets, andabout five against jets originating from charm quarks.Events were required to have a reconstructed primary vertex with at least five associated tracks. Eventswith any jets failing jet quality requirements [57], or with any muons compatible with cosmic-ray interac-tions or su ff ering substantial energy loss through bremsstrahlung in the detector material, were removed.An event preselection was then applied, requiring exactly one electron and one muon selected as de-scribed above, with opposite-sign electric charges. At least one of the leptons was required to be matchedto an electron or muon object triggering the event. Finally, selected events were required to have at leasttwo b -tagged jets. The resulting e µ b ¯ b event selection is similar to that of the √ s = b -tagged jets used in Ref. [1], except that events with three or more b -tagged jets are also accepted. Thenumbers of preselected opposite-sign e µ and selected e µ b ¯ b events are shown in Table 1. The observedevent count after requiring at least two b -tagged jets is in good agreement with the prediction from thebaseline simulation.Additional jets were defined as those other than the two b -tagged jets used to select the event. For thejet normalised di ff erential cross-section measurements, in the 3 % of selected events with three or more b -tagged jets, the jets with the two highest MV1 b -tagging weight values were taken to be the b -jetsfrom the top quark decays, and any other b -tagged jets were considered as additional jets, along with all The event counts di ff er from those in Ref. [1] as updated object calibrations were used in this analysis, in particular for the jetenergy scale. µ [%] ≥ b -jets [%]Data 70854 12437Total simulation 66200 100.0 12400 100.0 t ¯ t Wt single top 3840 5.8 360 2.9 Z ( → ττ → e µ ) + jets 12800 19.4 6 0.1Dibosons 8030 12.3 2 0.0Misidentified leptons 1200 1.8 96 0.8 Table 1: Selected numbers of events with an opposite-sign e µ pair, and with an opposite-sign e µ pair and at least two b -tagged jets in data, compared with the predictions from the baseline simulation, broken down into contributionsfrom t ¯ t , Wt and minor background processes. The predictions are normalised to the same integrated luminosity asthe data. untagged jets. Distributions of the number of additional jets are shown for various jet p T thresholds inFigure 1. The p T distributions for reconstructed additional jets are shown in Figure 2, with the estim-ated contribution from ‘unmatched jets’ (defined in Section 4.2 below) shown separately. In both cases,the data are shown compared to the predictions from simulation with the baseline P owheg + P ythia h damp = ∞ ) t ¯ t sample plus backgrounds, and the predictions from alternative t ¯ t simulation samples gen-erated with P owheg + P ythia owheg + P ythia h damp = m t , P owheg + H erwig with h damp = ∞ and MC@NLO + H erwig . The jet multiplicity distributions and p T spectra in the simulation samples aregenerally in reasonable agreement with those from data, except for MC@NLO + H erwig , which under-estimates the number of events with three or more extra jets, and also predicts significantly softer jet p T spectra.The gap fraction measurements use the same basic e µ b ¯ b event selection, but restricting the additionaljets to the central rapidity region, | y | < .
1. If three or more jets were b -tagged, the two highest- p T jetswere considered as the b -jets from the top quark decays, and the others as additional jets. This definitionfollows the p T -ordered selection used at particle level, and is di ff erent from that used in the di ff erentialcross-section analysis, as discussed in Sections 4.1 and 4.2 below. Distributions of the p T and | y | ofthe leading additional jet according to this definition are shown in Figure 3. The predictions generallydescribe the data well, and the trends seen are similar to those seen for the leading jet over the full rapidityregion in Figure 2(a). To facilitate comparisons with theoretical predictions, the measured jet di ff erential cross-sections and gapfractions were corrected to correspond to the particle level in simulation, thus removing reconstructione ffi ciency and resolution e ff ects. At particle level, electrons and muons were defined as those originatingfrom W decays, including via the leptonic decay of a τ lepton ( W → τ → e /µ ). The electron andmuon four-momenta were defined after final-state radiation, and ‘dressed’ by adding the four-momentaof all photons within a cone of size ∆ R = . k t algorithmwith radius parameter R = . × − s,excluding dressed leptons and neutrinos not originating from the decays of hadrons. Particles from theunderlying event were included, but those from overlaid pile-up collisions were not. Selected jets were7 > 25 GeV T p extra jets N0 1 2 3 4 5 e v en t s N ¥ Powheg+PY6 hdamp=ttWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | > 25 GeV T p extra jets N M C / D a t a ‡ (a) > 30 GeV T p extra jets N0 1 2 3 4 5 e v en t s N ¥ Powheg+PY6 hdamp=ttWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | > 30 GeV T p extra jets N M C / D a t a ‡ (b) > 40 GeV T p extra jets N0 1 2 3 4 e v en t s N ¥ Powheg+PY6 hdamp=ttWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | > 40 GeV T p extra jets N M C / D a t a ‡ (c) > 50 GeV T p extra jets N0 1 2 3 e v en t s N Data 2012 ¥ Powheg+PY6 hdamp=ttWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | > 50 GeV T p extra jets N M C / D a t a ‡ (d) Figure 1: Distributions of the number of reconstructed extra jets with | η | < . p T > (a) 25, (b) 30, (c) 40 and (d)50 GeV in selected e µ b ¯ b events in data and in simulation, normalised to the same number of events as the data. Thesimulation predictions for t ¯ t and Wt single-top production are shown separately, and the contributions from otherbackgrounds are negligible. The ratios of di ff erent MC samples to data are shown with error bars corresponding tothe simulation statistical uncertainty and a shaded band corresponding to the data statistical uncertainty. Systematicuncertainties are not shown. [GeV] T Jet p50 100 150 200 250 300 350 400 450 500 / G e V j e t s N Data 2012 ¥ Powheg+PY6 hdamp=ttUnmatched jetsWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | ordered extra jet T [GeV] T Jet p
50 100 150 200 250 300 350 400 450 500 M C / D a t a (a) [GeV] T Jet p50 100 150 200 250 300 / G e V j e t s N Data 2012 ¥ Powheg+PY6 hdamp=ttUnmatched jetsWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | ordered extra jet T [GeV] T Jet p
50 100 150 200 250 300 M C / D a t a (b) [GeV] T Jet p40 60 80 100 120 140 / G e V j e t s N Data 2012 ¥ Powheg+PY6 hdamp=ttUnmatched jetsWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | ordered extra jet T [GeV] T Jet p
40 60 80 100 120 140 M C / D a t a (c) [GeV] T Jet p30 40 50 60 70 80 90 100 / G e V j e t s N Data 2012 ¥ Powheg+PY6 hdamp=ttUnmatched jetsWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
ATLAS -1 =8 TeV, 20.3 fbs| < 4.5 h | ordered extra jet T [GeV] T Jet p
30 40 50 60 70 80 90 100 M C / D a t a (d) Figure 2: Distributions of reconstructed jet p T for the (a) first to (d) fourth additional jet in selected e µ b ¯ b events. Thedata are compared to simulation normalised to the same number of e µ b ¯ b events as the data. Backgrounds from Wt single-top and unmatched jets are estimated using the baseline P owheg + P ythia ff erent MC samples to data are shownwith error bars corresponding to the simulation statistical uncertainty and a shaded band corresponding to the datastatistical uncertainty. Systematic uncertainties are not shown. [GeV] T Jet p E v en t s / G e V Reconstructed MC Signal Events: Leading Additional Jet pT
ATLAS -1 =8 TeV, 20.3 fbs|y| < 2.1 ordered extra jet T Data 2012 ¥ Powheg+PY6 hdamp=ttWt ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty
Reconstructed MC Signal Events: Leading Additional Jet pT [GeV] T Jet p
50 100 150 200 250 300 M C / D a t a h_ratio1h_ratio1 (a) E v en t s / . |y| ordered extra jet T ATLAS |y| < 2.1 -1 =8 TeV, 20.3 fbsData 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Stat. uncertainty |y|
Jet rapidity |y| M C / D a t a ratio050etaratio050eta (b) Figure 3: Distributions of leading additional reconstructed jet (a) p T and (b) | y | in e µ b ¯ b events as used in the gapfraction measurement. The data are shown compared to simulation predictions using several t ¯ t generators, with the Wt background shown separately (not visible in (b)). Other backgrounds are negligible. The ratios of di ff erent MCsamples to data are shown with error bars corresponding to the simulation statistical uncertainty and a shaded bandcorresponding to the data statistical uncertainty. Systematic uncertainties are not shown. required to have p T >
25 GeV and | η | < .
5, and those within ∆ R = . b -hadrons were identified using a ghost-matching procedure [60],where the four-momenta of b -hadrons were scaled to a negligible magnitude and included in the set ofparticles on which the jet clustering algorithm was run. Jets whose constituents included b -hadrons afterthis procedure were labelled as b -jets.The particle-level e µ b ¯ b event selection was defined by requiring one electron and one muon with p T >
25 GeV and | η | < .
5, each separated from the nearest jet by ∆ R > .
4, and at least two b -jets with p T >
25 GeV and | η | < .
5. This closely matches the event selection used at reconstruction level.
For the definition of the gap fraction at particle level, if three or more b -jets were found, the two highest- p T jets were considered to be the b -jets from the top decays, and all other jets were considered to beadditional jets, whether labelled b -jets or not. In contrast, the di ff erential jet cross-section measurementsrequire an explicit jet-by-jet matching of particle-level to reconstructed jets. This was achieved by firstcalculating the ∆ R between each particle-level jet passing a looser requirement of p T >
10 GeV and eachreconstructed b -tagged jet, considering the two with highest MV1 weight if more than two reconstructedjets were b -tagged. Ordering the b -tagged jets by MV1 weight was found to give a greater fraction ofcorrect matches than the jet p T ordering used for the gap fraction measurements, where no jet matching is10eeded. If the closest reconstructed b -tagged jet was within ∆ R < .
4, the particle-level and reconstruc-ted jets were considered matched. The procedure was then repeated with the remaining particle-level andreconstructed jets, allowing each particle-level and reconstructed jet to be matched only once. Recon-structed jets which remained unassociated with particle-level jets after this procedure are referred to as‘unmatched’ jets; these originate from single particle-level jets which are split in two at reconstructionlevel (only one of which is matched), and from pile-up (since particles from pile-up collisions are notconsidered in the particle-level jet clustering). The contributions from such unmatched jets are shownseparately in Figure 2.
Monte Carlo simulation was used to determine selection e ffi ciencies, detector resolution e ff ects and back-grounds. The corresponding systematic uncertainties were evaluated as discussed in detail below, andpropagated through the jet di ff erential cross-section and gap fraction measurements. t ¯ t modelling: Although the analyses measure the properties of additional jets in t ¯ t events, they are stillslightly sensitive to the modelling of such jets in simulation due to the finite jet energy resolutionand reconstruction e ffi ciency, as well as the modelling of other t ¯ t event properties related to theleptons and b -jets from the top quark decays. The corresponding uncertainties were assessed bycomparing samples from the di ff erent generator configurations described in Section 3. In the di ff er-ential cross-section measurement, which is sensitive to the modelling of multiple additional jets, theuncertainty due to the choice of matrix-element generator was determined by comparing the NLOgenerator P owheg with the leading-order multi-leg generator M ad G raph , both interfaced to P y - thia
6. In the gap fraction measurements, which are more sensitive to an accurate modelling of thefirst additional jet, the corresponding uncertainty was assessed by comparing the NLO generatorsP owheg and MC@NLO, both interfaced to H erwig . The choice of parton shower and hadronisa-tion model was studied for both analyses by comparing samples with P owheg interfaced either toP ythia erwig . In all these cases, the full di ff erence between the predictions from the twocompared samples was assigned as the corresponding systematic uncertainty. The uncertainty dueto the modelling of additional radiation was calculated as half the di ff erence between the resultsusing M ad G raph + P ythia ff erential cross-section) or A lpgen + P ythia √ s = t ¯ t modelling uncertainty. Simulation statistical uncertainty:
In addition to the modelling uncertainties discussed above, the sizeof the t ¯ t simulation samples was also taken into account. Parton distribution functions:
The uncertainties due to limited knowledge of the proton PDFs wereevaluated by reweighting the MC@NLO + H erwig simulated t ¯ t sample based on the x and Q val-ues of the partons participating in the hard scattering in each event. The samples were reweightedusing the eigenvector variations of the CT10 [23], MSTW2008 [18] and NNPDF 2.3 [36] NLOPDF sets. The final uncertainty was calculated as half the envelope encompassing the predictionsfrom all three PDF sets along with their associated uncertainties, following the PDF4LHC recom-mendations [33]. 11 et energy scale: The uncertainty due to the jet energy scale (JES) was evaluated by varying it in simu-lation using a model with 23 separate orthogonal uncertainty components [57]. These componentscover in situ measurement uncertainties, the cross-calibration of di ff erent η regions, and the de-pendence on pile-up and the flavour of the jets. The total jet energy scale uncertainty varies in therange 1–6 % with a dependence on both jet p T and | η | . Jet energy resolution / e ffi ciency: The jet energy resolution (JER) was found to be well-modelled in sim-ulation [61], and residual uncertainties were assessed by applying additional smearing to the simu-lated jet energies. The calorimeter jet reconstruction e ffi ciency was measured in data using track-based jets, and found to be generally well-described by the simulation. Residual uncertainties wereassessed by discarding 2 % of jets with p T <
30 GeV; the uncertainties for higher-momentum jetsare negligible. Both these uncertainties were symmetrised about the nominal value. The uncertaintydue to the veto on events failing jet quality requirements is negligible.
Unmatched jets modelling:
The modelling of the component of unmatched jets from pile-up colli-sions was checked by comparing the predictions from simulated t ¯ t events combined with eitherP owheg+ P ythia t ¯ t sample. The estimated number of additional jetsper event from pile-up is 0 . ± .
002 in the central region used by the gap fraction measurements( | y | < .
1) and 0 . ± .
005 over the full region used by the di ff erential cross-section measure-ments ( | η | < . ff erence between the rate in zero-bias dataand simulation. The rate of unmatched jets in simulation was varied by these uncertainties in orderto determine the e ff ect on the results. In the di ff erential cross-section measurements, the full rate ofparticle-level jets that were split in two at reconstruction level in the baseline simulation was takenas an additional uncertainty on the rate of unmatched jets. Jet vertex fraction:
In both measurements, the contribution of jets from pile-up within | η | < . ffi ciency on non-pile-up jets of the JVF requirement were assessed by varying the cut value in simulation, based onstudies of Z → ee and Z → µµ events [56]. Other detector uncertainties:
The modelling of the electron and muon trigger and identification e ffi -ciencies, energy scales and resolutions were studied using Z → ee /µµ , J /ψ → ee /µµ and W → e ν events in data and simulation, using the techniques described in Refs. [51, 62, 63]. The uncertain-ties in the e ffi ciencies for b -tagging b , c and light-flavour jets were assessed using studies of b -jetscontaining muons, jets containing D ∗ mesons, and inclusive jet events [59]. The resulting uncer-tainties in the measured normalised di ff erential jet distributions and gap fractions are very small,since these uncertainties typically a ff ect the numerators and denominators in a similar way. Backgrounds:
As shown in Table 1, the most significant background comes from Wt single-top events.The uncertainty due to this background was assessed by conservatively doubling and removing theestimated Wt contribution, taking half the di ff erence in the result between these extreme variations.The sensitivity to the modelling of Wt single-top events was also assessed by using a sample simu-lated with P owheg + P ythia Z + jets and diboson background is negligible incomparison. In the gap fraction measurements, the additional background uncertainty from eventswith a misidentified lepton was also assessed by doubling and removing it, a conservative range12ccording to the studies of Ref. [1]. In the jet di ff erential cross-section measurements, the misiden-tification of jets as leptons induces migration in the additional-jet rank distributions, and is correctedfor as part of the unfolding procedure. The resulting e ff ects on the unfolding corrections are sig-nificantly smaller than the uncertainties from considering di ff erent t ¯ t generators, and no additionaluncertainty was included.Each independent uncertainty was evaluated according to the prescription above and then added in quad-rature to obtain the total systematic uncertainty in the final measurements. Since both measurements aree ff ectively ratios of cross-sections, normalised to the total number of selected e µ b ¯ b events, many of thesystematic uncertainties that typically contribute to a t ¯ t cross-section measurement cancel, such as thosein the integrated luminosity, lepton trigger and identification e ffi ciencies, lepton momentum scales andresolution, and b -jet energy scale and tagging e ffi ciency. Instead, the significant systematic uncertaintiesare those that directly a ff ect the measured additional-jet activity, i.e. systematic uncertainties in the jetenergy scale and resolution, and the modelling of unmatched jets. p T spectra The normalised di ff erential cross-sections for additional jets, corrected to the particle level, were meas-ured as a function of jet multiplicity and p T as defined in Equation (1). The fiducial requirements for eventand object selection are defined in Section 4.1, and include additional jets in the range | η | < .
5. As dis-cussed in Section 3, the fiducial region receives contributions from both the t ¯ t and Wt processes. Althoughthe requirement for two b -tagged jets ensures that t ¯ t is dominant, once the Wt process is considered atNLO, the two processes cannot in principle be cleanly separated. Therefore the results are presented bothwith the Wt contribution subtracted, to allow comparison with the t ¯ t generators discussed in Section 3,and for the combined t ¯ t + Wt final state, which may be compared with future NLO calculations treating t ¯ t and Wt concurrently. In practice, since the results are normalised to the number of selected e µ b ¯ b events,from t ¯ t or t ¯ t + Wt as appropriate in each case, and the predicted additional-jet distributions in simulated t ¯ t and Wt events are rather similar, the results from the two definitions are very close. The correction procedure transforms the measured spectra shown in Figure 2, after background subtrac-tion, to the particle-level spectra for events that pass the fiducial requirements. The unfolding was per-formed using a one-dimensional distribution encoding both the rank and p T of each additional jet in eachselected e µ b ¯ b event, as shown in Table 2 and graphically in Figure 4. The integral of the input (measured)distribution is the number of measured jets in the e µ b ¯ b sample and the integral of the output (unfolded)distribution is the number of particle-level jets passing the fiducial requirements. This procedure involvesseveral steps, as defined in the equation:1 σ e µ b ¯ b d σ jet i d p T = N events ∆ k f k (cid:88) j (cid:16) M − (cid:17) unfolded, k reco, j g j (cid:16) N j reco − N j bkgd (cid:17) . (4)Here, the bin indices j and k are functions of both jet p T and rank, with k corresponding to the appropriate p T bin of the jet of rank i at particle level under consideration. The expression σ e µ b ¯ b d σ jet i d p T represents the13easured di ff erential cross-section, i.e. the final number of corrected jets per event in each bin dividedby ∆ k , the width of the p T bin in units of GeV. The number of events in data passing the e µ b ¯ b selectionrequirements is represented by N events . The raw data event count reconstructed in bin j is representedby N j reco . The estimated additional-jet background, N j bkgd , is subtracted from this raw distribution. Thefactor g j corrects for migration across the fiducial boundaries in p T and η ( e.g. cases where the recon-structed jet has p T >
25 GeV but the particle-level jet has p T <
25 GeV). The expression (cid:16) M − (cid:17) unfolded, k reco, j represents the application of an unfolding procedure mapping the number of jets reconstructed in bin j tothe number of jets in bin k at particle level in events which pass both the reconstruction- and particle-levelselections. The correction factor f k removes the bias in the unfolded additional-jet spectrum coming fromthe reconstruction-level selection, as discussed further below. ATLAS
Simulation
Reconstructed bin number P a r t i c l e - l e v e l b i n nu m be r D e t e c t o r r e s pon s e m a t r i x j e t j e t j e t j e t j e t (a) Bin number un f o l ded j e t s / N t r u t h j e t s N ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HWPowheg+HW
ATLAS unfoldedjets /N truthjets N ” f +Wttt | < 4.5 h | jet 1 jet 2 jet 3 jet 4 jet 5 (b) Figure 4: (a) Migration matrix between the particle-level and reconstructed number of additional jets in each bin,determined from the baseline t ¯ t + Wt simulation. Jets are binned according to both p T value and rank; (b) bin-by-bincorrection factor f i for the bias due to the e µ b ¯ b event selection, evaluated using both the baseline P owheg + P ythia The response matrix M unfolded, k reco, j encodes the fractions of jets in particle-level bin k which get reconstructedin bin j , with both k and j being obtained from the corresponding jet p T and rank. The matrix is filled fromsimulated events that pass both the reconstructed and particle-level selection requirements. Figure 4(a)provides a graphical representation of M unfolded, k reco, j . The matrix is largely diagonal, showing that jets aremost likely to be reconstructed with the correct p T and rank. However, there are significant numbersof particle-level subleading jets reconstructed as leading jets and particle-level leading jets reconstructedas subleading jets, particularly when several jets in the event have similar low p T values. This type ofmigration motivates the simultaneous binning in both rank and p T .A Bayesian iterative unfolding method [64] implemented in the RooUnfold [65] software package wasused. The response matrix M is not unitary because in mapping from particle to reconstruction level, someevents and objects are lost due to ine ffi ciencies and some are gained due to misreconstruction or migrationof objects from outside the fiducial acceptance into the reconstructed distribution. This results in the14esponse matrix being almost singular, and it is therefore not possible to obtain stable unfolded resultsby inverting the response matrix and applying it to the measured data. Instead, an assumed particle-leveldistribution (the ‘prior’) was chosen, the response matrix applied and the resulting trial reconstruction setwas compared to the observed reconstruction set. A new prior was then constructed from the old priorand the di ff erence between the trial and the observed distributions. The procedure was iterated until theresult became stable. For this analysis, two iterations were found to be su ffi cient, based on studies ofthe unfolding performance in simulated samples with reweighted jet p T distributions and from di ff erentgenerators.This unfolding procedure gives unbiased additional-jet distributions for events passing both the particle-level and reconstruction-level event selections. However, the reconstruction-level selection results inthe unfolded distributions di ff ering from those obtained using the particle-level selection alone. Anadditional contribution to the bias results from events where one of the two reconstructed b -taggedjets is actually a mistagged light jet. These biases were corrected using a bin-by-bin correction factor f k = N k truth / N k unfolded , where N k truth is the number of jets in bin k at particle level without the applicationof the reconstruction-level event selection. The correction was applied after the unfolding, as shown inEquation (4). Figure 4(b) shows the values of f for both the baseline and some alternative t ¯ t generat-ors. The corresponding systematic uncertainty was assessed as part of the t ¯ t modelling uncertainty asdiscussed in Section 5.The procedure described above provides the absolute numbers of additional jets in the number of eventspassing the e µ b ¯ b fiducial requirements ( N events ). This result was then normalised relative to N events toobtain the final distribution σ e µ b ¯ b d σ jet i d p T , which was finally integrated over jet p T to obtain the jet multiplicitydistributions. All systematic uncertainties were evaluated as full covariance matrices including bin-to-bin correlations.The majority of uncertainties from Section 5 are defined in terms of an RMS width, with the assumptionthat the true distribution is Gaussian with a mean at the nominal value. In these cases, the covariancematrix was calculated from pseudo-experiments drawn from this distribution. Each pseudo-experimentwas constructed by choosing the size of the systematic uncertainty randomly according to a Gaussiandistribution, calculating the resulting e ff ect at the reconstruction level and propagating it through theunfolding procedure. The covariance was then given by C i j ≡ N pseudo N pseudo (cid:88) x = (cid:16) N ix − (cid:68) N i (cid:69)(cid:17) (cid:16) N jx − (cid:68) N j (cid:69)(cid:17) , (5)where N pseudo is the number of pseudo-experiments (typically 1000), (cid:104) N i (cid:105) is the nominal number of jetsin bin i , and N ix is the number of jets in bin i for pseudo-experiment x . Some systematic uncertaintieswere evaluated by comparing an alternative model to the baseline. In these cases, the covariance wasapproximated by C i j ≡ δ i δ j , (6)where δ i is the bias in bin i . This bias was determined by analysing the alternative model using Equa-tion (4), with the response matrix and correction factors taken from the baseline.15he uncertainties calculated using Equation (5) include all detector modelling e ff ects ( e.g. jet energy scaleand resolution), PDFs, the Wt cross-section and statistical uncertainties associated with the simulatedsamples. Uncertainties evaluated using Equation (6) include generator, radiation, parton shower and had-ronisation contributions to the t ¯ t modelling uncertainty, and modelling of the unmatched jet background.Figure 5 shows the fractional uncertainties in the corrected jet distributions. In most bins, the statisticaluncertainty dominates, with the largest systematic uncertainty coming from the jet energy scale. p T spectra results Figures 6–7 show normalised distributions of the additional-jet multiplicity for di ff erent jet p T thresholds,and compare the data to the NLO generator configurations P owheg + P ythia h damp = ∞ or m t ,P owheg + P ythia
8, MC@NLO + H erwig and P owheg + H erwig . Figures 8–9 show the normalised di ff er-ential cross-sections σ e µ b ¯ b d σ jet i d p T for jets of rank i from one to four. In both cases, the expected contributionsfrom Wt events were subtracted from the event counts before normalising the distributions, based on thebaseline P owheg+ P ythia Wt simulation sample. The same data are presented numerically in Table 2,both with and without subtraction of the Wt contribution, and including two p T bins for the fifth jet. Thehighest p T bin for each jet rank includes overflows, but the di ff erential cross-sections are normalised usingthe bin widths ∆ derived from the upper p T bin limits listed in Table 2 and shown in Figures 8 and 9. Table 2: Normalised particle-level di ff erential jet cross-sections as a function of jet rank and p T , both without( σ t ¯ t + Wt ) and with ( σ t ¯ t ) the Wt contribution subtracted. The additional jets are required to have | η | < .
5, corres-ponding to the full pseudorapidity range . The boundaries of each bin are given, together with the mean jet p T ineach bin. The last bin for every jet rank includes overflows, but the di ff erential cross-section values are determinedusing the upper bin limit given for that bin. Bin Rank p T range [GeV] Avg. p T [GeV] σ d σ i d p T ( t ¯ t + Wt ) ± (stat.) ± (syst.)[10 − GeV − ] σ d σ i d p T ( t ¯ t ) ± (stat.) ± (syst.)[10 − GeV − ]1 1 25–30 27.4 144 . ± . ± . . ± . ± .
22 1 30–35 32.4 122 . ± . ± . . ± . ± .
53 1 35–40 37.4 101 . ± . ± . . ± . ± .
24 1 40–45 42.5 84 . ± . ± . . ± . ± .
25 1 45–50 47.4 70 . ± . ± . . ± . ± .
06 1 50–60 54.8 58 . ± . ± . . ± . ± .
37 1 60–70 64.8 46 . ± . ± . . ± . ± .
78 1 70–80 74.8 35 . ± . ± . . ± . ± .
29 1 80–90 84.8 27 . ± . ± . . ± . ± .
010 1 90–100 94.8 21 . ± . ± . . ± . ± .
811 1 100–125 111.5 16 . ± . ± . . ± . ± .
512 1 125–150 136.7 11 . ± . ± .
29 11 . ± . ± . . ± . ± .
22 6 . ± . ± . . ± . ± .
13 5 . ± . ± . . ± . ± .
14 3 . ± . ± . . ± . ± .
12 2 . ± . ± . + . ± . ± .
02 0 . ± . ± . Continued on next page
Continued from previous page
Bin Rank p T range [GeV] Avg. p T [GeV] σ d σ i d p T ( t ¯ t + Wt ) ± (stat.) ± (syst.)[10 − GeV − ] σ d σ i d p T ( t ¯ t ) ± (stat.) ± (syst.)[10 − GeV − ]18 2 25–30 27.4 110 . ± . ± . . ± . ± .
119 2 30–35 32.4 80 . ± . ± . . ± . ± .
220 2 35–40 37.4 59 . ± . ± . . ± . ± .
521 2 40–45 42.4 44 . ± . ± . . ± . ± .
122 2 45–50 47.4 35 . ± . ± . . ± . ± .
423 2 50–60 54.6 26 . ± . ± . . ± . ± .
824 2 60–70 64.6 17 . ± . ± . . ± . ± .
025 2 70–80 74.6 9 . ± . ± . . ± . ± .
726 2 80–90 84.7 5 . ± . ± .
43 5 . ± . ± . . ± . ± .
33 3 . ± . ± . . ± . ± .
15 2 . ± . ± . . ± . ± .
09 1 . ± . ± . + . ± . ± .
01 0 . ± . ± . . ± . ± . . ± . ± .
232 3 30–40 34.3 29 . ± . ± . . ± . ± .
433 3 40–50 44.4 12 . ± . ± . . ± . ± .
434 3 50–75 59.3 4 . ± . ± .
45 4 . ± . ± . + . ± . ± .
04 0 . ± . ± . . ± . ± . . ± . ± .
737 4 30–40 34.1 9 . ± . ± . . ± . ± .
438 4 40–50 44.2 3 . ± . ± .
50 3 . ± . ± . + . ± . ± .
08 0 . ± . ± . . ± . ± . . ± . ± .
641 5 30–50 + . ± . ± .
40 1 . ± . ± . t ¯ t process. Di ff erences among thegenerators become larger with increasing jet rank, where the prediction from the NLO generators isdetermined mainly by the parton shower. In this region, the generators predict significantly di ff erent ratesof additional-jet production. They also predict some di ff erences in the shapes of the jet p T spectra. TheMC@NLO + H erwig sample predicts the lowest rate of additional-jet production and underestimates thenumber of events with at least four additional jets by 40 %.The same fully corrected data are compared to the leading-order multi-leg generators A lpgen + P ythia lpgen + H erwig and M ad G raph + P ythia ff ects of the variations discussed in Section 3 for samplesgenerated with A cer MC + P ythia
6, A lpgen + P ythia ad G raph + P ythia
6. The measurement givesan uncertainty in the di ff erential cross-sections that is smaller than the range spanned by these variationsin the leading-order generators. 17 [GeV] T Jet p100 200 300 400 500 F r a c t i ona l U n c e r t a i n t y -0.3-0.2-0.100.10.20.3 Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC)
ATLAS -1 =8 TeV, 20.3 fbs ordered extra jet T (a) [GeV] T Jet p50 100 150 200 250 300 F r a c t i ona l U n c e r t a i n t y -0.3-0.2-0.100.10.20.3 Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC)
ATLAS -1 =8 TeV, 20.3 fbs ordered extra jet T (b) [GeV] T Jet p40 60 80 100 120 140 F r a c t i ona l U n c e r t a i n t y -0.3-0.2-0.100.10.20.3 Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC)
ATLAS -1 =8 TeV, 20.3 fbs ordered extra jet T (c) [GeV] T Jet p30 40 50 60 70 80 90 100 F r a c t i ona l U n c e r t a i n t y -0.3-0.2-0.100.10.20.3 Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC)
ATLAS -1 =8 TeV, 20.3 fbs ordered extra jet T (d) Figure 5: Envelope of fractional uncertainties in the first (a) to the fourth (d) additional-jet normalised di ff erentialcross-sections, as functions of the corresponding jet p T . The total uncertainties are shown, together with the separatecontributions from the data statistical uncertainty and various categories of systematic uncertainty. > 25 GeV T p extra jets N0 1 2 3 4 5 F r a c t i on o f e v en t s Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | > 25 GeV T p extra jets N M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= > 25 GeV T p extra jets N M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY > 25 GeV T p extra jets N M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q ‡ (a) > 30 GeV T p extra jets N0 1 2 3 4 5 F r a c t i on o f e v en t s Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | > 30 GeV T p extra jets N M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= > 30 GeV T p extra jets N M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY > 30 GeV T p extra jets N M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q ‡ (b) Figure 6: Unfolded normalised distributions of particle-level additional-jet multiplicity with p T > (a) 25 GeV and (b)30 GeV in selected e µ b ¯ b events. The data are shown as points with error bars indicating the statistical uncertainty,and are compared to simulation from several NLO t ¯ t generator configurations. The Wt contribution taken fromP owheg + P ythia ff erent simulation predictionsto data, with the shaded bands including both the statistical and systematic uncertainties of the data. > 40 GeV T p extra jets N0 1 2 3 4 F r a c t i on o f e v en t s Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | > 40 GeV T p extra jets N M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= > 40 GeV T p extra jets N M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY > 40 GeV T p extra jets N M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q ‡ (a) > 50 GeV T p extra jets N0 1 2 3 F r a c t i on o f e v en t s Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | > 50 GeV T p extra jets N M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= > 50 GeV T p extra jets N M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY > 50 GeV T p extra jets N M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q ‡ (b) Figure 7: Unfolded normalised distributions of particle-level additional-jet multiplicity with p T > (a) 40 GeV and (b)50 GeV in selected e µ b ¯ b events. The data are shown as points with error bars indicating the statistical uncertainty,and are compared to simulation from several NLO t ¯ t generator configurations. The Wt contribution taken fromP owheg + P ythia ff erent simulation predictionsto data, with the shaded bands including both the statistical and systematic uncertainties of the data. [GeV] T Jet p50 100 150 200 250 300 350 400 450 500 / G e V j e t s N e v en t s ( / N ) -4 -3 -2 Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | ordered extra jet T [GeV] T Jet p
50 100 150 200 250 300 350 400 450 500 M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= [GeV] T Jet p
50 100 150 200 250 300 350 400 450 500 M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY [GeV] T Jet p
50 100 150 200 250 300 350 400 450 500 M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q (a) [GeV] T Jet p50 100 150 200 250 300 / G e V j e t s N e v en t s ( / N ) -4 -3 -2 Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | ordered extra jet T [GeV] T Jet p
50 100 150 200 250 300 M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= [GeV] T Jet p
50 100 150 200 250 300 M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY [GeV] T Jet p
50 100 150 200 250 300 M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q (b)
Figure 8: Unfolded normalised distributions of particle-level jet p T for the first and second additional jet in selected e µ b ¯ b events. The data are shown as points with error bars indicating the statistical uncertainty, and are comparedto simulation from several NLO t ¯ t generator configurations. The Wt contribution taken from P owheg + P ythia ff erent simulation predictions to data, with theshaded bands including both the statistical and systematic uncertainties of the data. [GeV] T Jet p40 60 80 100 120 140 / G e V j e t s N e v en t s ( / N ) -4 -3 -2 Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | ordered extra jet T [GeV] T Jet p
40 60 80 100 120 140 M C / D a t a ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=m MC@NLO+HW ¥ Powheg+HW hdamp= [GeV] T Jet p
40 60 80 100 120 140 M C / D a t a Alpgen+HW Alpgen+PY MadGraph+PY [GeV] T Jet p
40 60 80 100 120 140 M C / D a t a AcerMC+PY6 RadHi AcerMC+PY6 RadLoAlpgen+PY6 RadHi Alpgen+PY6 RadLo down MadGraph+PY6 q up MadGraph+PY6 q (a) [GeV] T Jet p30 40 50 60 70 80 90 100 / G e V j e t s N e v en t s ( / N ) -4 -3 -2 Data 2012 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
ATLAS -1 =8 TeV, 20.3 fbs t| < 4.5, t h | ordered extra jet T [GeV] T Jet p
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Figure 9: Unfolded normalised distributions of particle-level jet p T for the third and fourth additional jet in selected e µ b ¯ b events. The data are shown as points with error bars indicating the statistical uncertainty, and are comparedto simulation from several NLO t ¯ t generator configurations. The Wt contribution taken from P owheg + P ythia ff erent simulation predictions to data, with theshaded bands including both the statistical and systematic uncertainties of the data. χ p -valueP owheg + P ythia h damp = ∞ × − P owheg + P ythia h damp = m t × − P owheg + P ythia h damp = m t × − MC@NLO + H erwig × − P owheg + H erwig h damp = ∞ × − A lpgen + H erwig × − A lpgen + P ythia × − M ad G raph + P ythia × − A cer MC + P ythia × − A cer MC + P ythia × − A lpgen + P ythia × − A lpgen + P ythia × − M ad G raph + P ythia q down 50.2 1.5 × − M ad G raph + P ythia q up 78.7 3.6 × − Table 3: Values of χ for the comparison of the full set of additional-jet p T spectra in data with the predictions fromvarious t ¯ t generator configurations, including both the statistical and systematic uncertainties. The additional jetscorrespond to the full pseudorapidity range ( | η | < . χ and p -values correspond to 41 degrees of freedom. The level of agreement between the generator predictions and the data was assessed quantitatively usinga χ test taking into account all bins of the measured jet p T distributions with rank one to five. Sincethe systematic uncertainties and unfolding corrections induce large correlations between bins, the χ wascalculated from the full covariance matrix. Table 3 presents the resulting χ values. Among the NLO gen-erators, P owheg + H erwig , and P owheg + P ythia h damp = ∞ or m t , agree reasonably well with thedata. P owheg + P ythia + H erwig gives a very poor description of the data.The leading-order multi-leg generators A lpgen + P ythia ad G raph + P ythia lpgen + H erwig is slightly disfavoured. Of the three variations of A lpgen + P ythia ad -G raph + P ythia q down’ tune, which corresponds to more radiation thanthe baseline tune, agrees best with data. The A cer MC + P ythia The gap fraction f ( Q ) as defined in Equation (2) was measured by using the analogous definition forreconstructed jets, counting the number of selected e µ b ¯ b events N and the number n ( Q ) of them thathave no additional jets with p T > Q within the rapidity interval ∆ y : f reco ( Q ) ≡ n ( Q ) N (7)and similarly for the gap fraction based on Q sum . The values of N and n were first corrected to remove thebackground contributions estimated from simulation, including the Wt contribution, as this study focuses23n the comparison of measured gap fractions with the predictions from the t ¯ t generators discussed inSection 3. The measured gap fraction f reco ( Q ) was then multiplied by a correction factor C ( Q ) to obtainthe particle-level gap fraction f part ( Q ) defined as in Equation (2) using the particle-level definitions givenin Section 4.1. The correction factor was evaluated using the values of f reco ( Q ) and f part ( Q ) obtainedfrom the baseline P owheg + P ythia t ¯ t simulation sample: C ( Q ) ≡ f part ( Q ) f reco ( Q ) . (8)Systematic uncertainties arise in this procedure from the uncertainties in C ( Q ) and the backgroundssubtracted before the calculation of N and n .The gap fractions f ( Q ) and f ( Q sum ) were measured for the same rapidity regions as used in Ref. [2],namely | y | < .
8, 0 . < | y | < .
5, 1 . < | y | < . | y | < .
1. The sets of Q and Q sum threshold values chosen also correspond to those in Ref. [2], and the steps correspondapproximately to one standard deviation of the jet energy resolution. The values of the correction factor C ( Q ) (and similarly for Q sum ) deviate by at most 5 % from unity at low Q and Q sum , and approach unityat higher threshold values. The small corrections reflect the high selection e ffi ciency and high purity ofthe event samples; at each threshold Q , the baseline simulation predicts that around 80 % of the selectedreconstructed events that do not have a jet with p T > Q also have no particle-level jet with p T > Q .Therefore, a simple bin-by-bin correction method is adequate, rather than a full unfolding as used for thedi ff erential jet cross-section measurement.The systematic uncertainties in the gap fraction measurements were evaluated as discussed in Section 5,and the uncertainties from di ff erent sources added in quadrature. The results are shown in Figure 10 asrelative uncertainties ∆ f / f in the measured gap fraction for two illustrative rapidity intervals, | y | < . | y | < . Figures 11 and 12 show the resulting measurements of the gap fraction f ( Q ) in data, corrected to theparticle level. Figure 13 shows the analogous results for f ( Q sum ), for the | y | < . | y | < . lpgen + P ythia
6, A lpgen + H erwig and M ad G raph + P ythia
6. Thelower ratio plots compare the data to A cer MC + P ythia
6, A lpgen + P ythia ad G raph + P ythia Q in Table 4 and as a function of Q sum inTable 5, together with the values predicted by the generators shown in the upper plots of Figures 11, 12and 13. The matrix of statistical and systematic correlations is shown in Figure 14 for the gap fractionmeasurement at di ff erent values of Q for the full central | y | < . Q are highly correlated, while well-separated Q points are less correlated. The full covariance matrixincluding correlations was used to calculate a χ value for the consistency of each of the NLO generatorpredictions with the data in each veto region. The results are shown in Tables 6 and 7.All the NLO generators provide a reasonable description of the f ( Q ) distribution in the regions | y | < . . < | y | < .
5. All these generators are also consistent with the data in the most forward region(1 . < | y | < . √ s = [GeV] Q50 100 150 200 250 300 F r a c t i ona l U n c e r t a i n t y Total systematic systematic
ATLAS -1 =8 TeV, 20.3 fbs Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC) veto region: |y| < 0.8 Total systematic systematic (a) [GeV] Q50 100 150 200 250 300 F r a c t i ona l U n c e r t a i n t y Total systematic systematic
ATLAS -1 =8 TeV, 20.3 fbs Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC) veto region: |y| < 2.1 Total systematic systematic (b)
Figure 10: Envelope of fractional uncertainties ∆ f / f in the gap fraction f ( Q ) for (a) | y | < . | y | < .
1. Thestatistical uncertainty is shown by the hatched area, and the total uncertainty by the solid black line. The systematicuncertainty is shown broken down into several groups, each of which includes various individual components (seetext). f ( Q ) [%] Q [GeV] Data ± (stat.) ± (syst.) P owheg + P ythia h damp = ∞ P owheg + P ythia h damp = m t P owheg + P ythia h damp = m t MC@NLO + H erwig P owheg + H erwig h damp = ∞ ρ ij (stat. + syst.)veto region: | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = < | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = < | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = f ( Q ) for di ff erent veto-region rapidity intervals and Q values of 25, 75and 150 GeV in data compared to the predictions from various t ¯ t simulation samples. The combination of statisticaland systematic correlations between measurements at Q = i and Q = j is given as ρ ij . ( Q sum ) [%] Q sum [GeV] Data ± (stat.) ± (syst.) P owheg + P ythia h damp = ∞ P owheg + P ythia h damp = m t P owheg + P ythia h damp = m t MC@NLO + H erwig P owheg + H erwig h damp = ∞ ρ ij (stat. + syst.)veto region: | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = < | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = < | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = f ( Q sum ) for di ff erent veto-region rapidity intervals and Q sum values of55, 150 and 300 GeV in data compared to the predictions from various t ¯ t simulation samples. The combination ofstatistical and systematic correlations between measurements at Q sum = i and Q sum = j is given as ρ ij . Q | y | < . . < | y | < . . < | y | < . | y | < . χ p -value χ p -value χ p -value χ p -valueP owheg+ P ythia h damp = ∞ × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − MC@NLO + H erwig × − × − × − × − P owheg+ H erwig h damp = ∞ × − × − × − × − A lpgen+ H erwig × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia q down 17.8 4.7 × − × − × − × − M ad G raph+ P ythia q up 21.0 2.8 × − × − × − × − Table 6: Values of χ for the comparison of the measured gap fraction distributions with the predictions from various t ¯ t generator configurations, for the four rapidity regions as a function of Q . The χ and p -values correspond to 18degrees of freedom. [GeV] Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: |y| < 0.8 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (a) [GeV] Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: 0.8 < |y| < 1.5 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (b)
Figure 11: The measured gap fraction f ( Q ) as a function of Q in di ff erent veto-region rapidity intervals ∆ y , for(a) | y | < . . < | y | < .
5. The data are shown by the points with error bars indicating the total uncertainty,and compared to the predictions from various t ¯ t simulation samples (see text) shown as smooth curves. The lowerplots show the ratio of predictions to data, with the data uncertainty being indicated by the shaded band, and the Q thresholds corresponding to the left edges of the histogram bins, except for the first bin. [GeV] Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: 1.5 < |y| < 2.1 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (a) [GeV] Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: |y| < 2.1 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (b)
Figure 12: The measured gap fraction f ( Q ) as a function of Q in di ff erent veto-region rapidity intervals ∆ y , for(a) 1 . < | y | < . | y | < .
1. The data are shown by the points with error bars indicating the total uncertainty,and compared to the predictions from various t ¯ t simulation samples (see text) shown as smooth curves. The lowerplots show the ratio of predictions to data, with the data uncertainty being indicated by the shaded band, and the Q thresholds corresponding to the left edges of the histogram bins, except for the first bin. [GeV] sum Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: |y| < 0.8 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] sum Q
50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (a) [GeV] sum Q pa r t gap f Graph -1 =8 TeV, 20.3 fbs ATLAS veto region: |y| < 2.1 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] sum Q
50 100 150 200 250 300 350 400 450 500 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (b)
Figure 13: The measured gap fraction f ( Q sum ) as a function of Q sum in di ff erent veto-region rapidity intervals ∆ y ,for (a) | y | < . | y | < .
1. The data are shown by the points with error bars indicating the total uncertainty,and compared to the predictions from various t ¯ t simulation samples (see text) shown as smooth curves. The lowerplots show the ratio of predictions to data, with the data uncertainty being indicated by the shaded band, and the Q sum thresholds corresponding to the left edges of the histogram bins, except for the first bin. [GeV] Q
50 100 150 200 250 300 [ G e V ] Q Stat.+Syst. Correlation
ATLAS -1 =8 TeV, 20.3 fbsveto region: |y| < 2.1 Figure 14: The correlation matrix (including statistical and systematic correlations) for the gap fraction measure-ment at di ff erent values of Q for the full central rapidity region | y | < . Q sum | y | < . . < | y | < . . < | y | < . | y | < . χ p -value χ p -value χ p -value χ p -valueP owheg+ P ythia h damp = ∞ × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − MC@NLO + H erwig × − × − × − × − P owheg+ H erwig h damp = ∞ × − × − × − × − A lpgen+ H erwig × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia q down 22.5 4.3 × − × − × − × − M ad G raph+ P ythia q up 25.0 3.0 × − × − × − × − Table 7: Values of χ for the comparison of the measured gap fraction distributions with the predictions from various t ¯ t generator configurations, for the four rapidity regions as a function of Q sum . The χ and p -values correspond to22 degrees of freedom. | y | < . owheg + P ythia owheg + P ythia h damp = m t and MC@NLO + H erwig pre-dict slightly less radiation, and P owheg + P ythia h damp = ∞ and P owheg + H erwig predict slightlymore. P owheg + P ythia | y | regions. The res-ults for f ( Q sum ), which are sensitive to all the additional jets within the rapidity interval, show some-what larger di ff erences between the generators than those for f ( Q ). Over the rapidity region | y | < . owheg + P ythia h damp = m t and MC@NLO + H erwig are disfavoured. The latter generator com-bination also performs poorly for the di ff erential cross-section measurements discussed in Section 6.The leading-order generators A lpgen + P ythia
6, A lpgen + H erwig and M ad G raph + P ythia Q and Q sum . The pairs of samples withincreased / decreased radiation also bracket the data in all rapidity regions, except for A cer MC + P ythia Q and Q sum . As in the di ff erential cross-section measurements, the data show a clear preference for the ‘RadLo’ variation for A lpgen + P ythia q down’ variation for M ad G raph + P ythia
6, across all rapidity regions. These data should there-fore allow the uncertainties due to radiation modelling in t ¯ t events to be significantly reduced, once themodels are tuned to these more precise √ s = √ s = e µ b ¯ b mass regions The gap fraction was also measured over the full rapidity veto region | y | < . m e µ b ¯ b . The distribution of reconstructed m e µ b ¯ b in the selected e µ b ¯ b eventsis shown in Figure 15, and is reasonably well-reproduced by the baseline t ¯ t simulation sample. Thedistribution was divided into four regions at both reconstruction and particle level: m e µ b ¯ b <
300 GeV,300 < m e µ b ¯ b <
425 GeV, 425 < m e µ b ¯ b <
600 GeV and m e µ b ¯ b >
600 GeV. These boundaries were chosento minimise migration between the regions; in the baseline simulation, around 85 % of the reconstructedevents in each m e µ b ¯ b region come from the corresponding region at particle level. The corresponding cor-rection factors C m ( Q ) which translate the measured gap fraction in the reconstruction-level m e µ b ¯ b regionto the corresponding particle-level gap fractions f m ( Q ) and f m ( Q sum ), are of similar size to C ( Q ), withthe exception of the highest m e µ b ¯ b region, where they reach about 1.1 at low Q . The systematic uncer-tainties in the gap fraction measurement in two m e µ b ¯ b regions are shown in Figure 16. The magnitudes ofthe systematic uncertainties are comparable to those in the full m e µ b ¯ b range, except for the highest m e µ b ¯ b region where they are significantly larger.Figures 17 and 18 show the resulting measurements of the gap fractions as a function of Q in the four m e µ b ¯ b regions in data, compared to the same set of predictions as shown in Figures 11, 12 and 13. Tables 8and 9 show the gap fractions at selected Q and Q sum values in each invariant mass region, again comparedto predictions from the first set of generators. Figure 19 gives an alternative presentation of the gapfraction f m ( Q ) as a function of m e µ b ¯ b for four di ff erent Q values. The χ values for the consistencyof the prediction from each NLO generator with data in the four mass regions are given in Tables 10and 11.In general, the di ff erent generator configurations provide a good model of the evolution of the gap frac-tion distributions with m e µ b ¯ b , and similar trends in the predictions of individual generators are seen asfor the inclusive | y | < . [GeV] bb m e m E v en t s / G e V Mass distribution, variable binning
ATLAS -1 =8 TeV, 20.3 fbs ¥ Powheg+PY6 hdamp = t Powheg+PY6 hdamp = m t Powheg+PY8 hdamp = mMC@NLO+HW ¥ Powheg+HW hdamp = Stat. uncertainty veto region: |y| < 2.1
Mass distribution, variable binning [GeV] bb m e m0 100 200 300 400 500 600 700 800 900 1000 M C / D a t a h_ratio050h_ratio050 Figure 15: Distribution of the reconstructed invariant mass of the e µ b ¯ b system m e µ b ¯ b in data, compared to simulationusing various t ¯ t generators. The shaded band represents the statistical uncertainty in data. The lower plot shows theratio of the distribution of invariant mass in data to that in each of the simulation samples. f m ( Q ) [%] Q [GeV] Data ± (stat.) ± (syst.) P owheg + P ythia h damp = ∞ P owheg + P ythia h damp = m t P owheg + P ythia h damp = m t MC@NLO + H erwig P owheg + H erwig h damp = ∞ ρ ij (stat. + syst.)veto region: | y | < . m e µ b ¯ b <
300 GeV25 56.0 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < .
1, 300 < m e µ b ¯ b <
425 GeV25 54.4 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < .
1, 425 < m e µ b ¯ b <
600 GeV25 47.6 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < . m e µ b ¯ b >
600 GeV25 45.9 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = f m ( Q ) for the veto region | y | < . Q values of 25, 75 and 150 GeV in data compared to the predictions from various t ¯ t simulation samples. Thecombination of statistical and systematic correlations between measurements at Q = i and Q = j is given as ρ ij . m ( Q sum ) [%] Q sum [GeV] Data ± (stat.) ± (syst.) P owheg + P ythia h damp = ∞ P owheg + P ythia h damp = m t P owheg + P ythia h damp = m t MC@NLO + H erwig P owheg + H erwig h damp = ∞ ρ ij (stat. + syst.)veto region: | y | < . m e µ b ¯ b <
300 GeV55 75.0 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < .
1, 300 < m e µ b ¯ b <
425 GeV55 72.8 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < .
1, 425 < m e µ b ¯ b <
600 GeV55 67.4 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = | y | < . m e µ b ¯ b >
600 GeV55 63.2 ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = ± ± . ± ± ± ± ± ρ = f m ( Q sum ) for the veto region | y | < . Q sum values of 55, 150 and 300 GeV in data compared to the predictions from various t ¯ t simulation samples.The combination of statistical and systematic correlations between measurements at Q sum = i and Q sum = j is givenas ρ ij . [GeV] Q50 100 150 200 250 300 F r a c t i ona l U n c e r t a i n t y Total Uncertainty
ATLAS -1 =8 TeV, 20.3 fbs Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC) veto region: |y| < 2.1 < 300 GeV bb m e m Total Uncertainty (a) [GeV] Q50 100 150 200 250 300 F r a c t i ona l U n c e r t a i n t y Total Uncertainty
ATLAS -1 =8 TeV, 20.3 fbs Total Uncertainty Stat. Uncertainty (Data)Jet Energy Scale Jet Resolution/EfficiencyOther Detector Effects JVF/Unmatched JetsBackground Processes ModellingttPDF Modelling Stat. Uncertainty (MC) veto region: |y| < 2.1 > 600 GeV bb m e m Total Uncertainty (b) Figure 16: Envelope of fractional uncertainties ∆ f / f in the gap fraction f m ( Q ) for (a) m e µ b ¯ b <
300 GeV and (b) m e µ b ¯ b >
600 GeV. The statistical uncertainty is shown by the hatched area, and the total systematic uncertainty bythe solid black line. The systematic uncertainty is also shown broken down into several groups, each of whichincludes various individual components (see text). [GeV] Q pa r t gap f Graph veto region: |y| < 2.1 < 300 GeV bb m e m -1 =8 TeV, 20.3 fbs ATLAS ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
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50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (a) [GeV] Q pa r t gap f Graph veto region: |y| < 2.1 < 425 GeV bb m e
300 < m -1 =8 TeV, 20.3 fbs ATLAS ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
Graph
50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (b)
Figure 17: The measured gap fraction f m ( Q ) as a function of Q in the veto region | y | < . m e µ b ¯ b <
300 GeV and (b) 300 < m e µ b ¯ b <
425 GeV. The data are shown by the points with error barsindicating the total uncertainty, and compared to the predictions from various t ¯ t simulation samples (see text) shownas smooth curves. The lower plots show the ratio of predictions to data, with the data uncertainty being indicatedby the shaded band, and the Q thresholds corresponding to the left edges of the histogram bins, except for the firstbin. [GeV] Q pa r t gap f Graph veto region: |y| < 2.1 < 600 GeV bb m e
425 < m -1 =8 TeV, 20.3 fbs ATLAS ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
Graph
50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (a) [GeV] Q pa r t gap f Graph veto region: |y| < 2.1 > 600 GeV bb m e m -1 =8 TeV, 20.3 fbs ATLAS ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp=Total uncertainty
Graph
50 100 150 200 250 300 M C / D a t a h_ratio050 ¥ Powheg+PY6 hdamp= t Powheg+PY6 hdamp=m t Powheg+PY8 hdamp=mMC@NLO+HW ¥ Powheg+HW hdamp= h_ratio050
50 100 150 200 250 300 M C / D a t a h_ratio440 Alpgen+HW Alpgen+PY MadGraph+PY h_ratio440 [GeV] Q
50 100 150 200 250 300 M C / D a t a h_ratio209 AcerMC+PY RadHi Alpgen+PY RadHi down MadGraph+PY qAcerMC+PY RadLo Alpgen+PY RadLo up MadGraph+PY q h_ratio209 (b)
Figure 18: The measured gap fraction f m ( Q ) as a function of Q in the veto region | y | < . < m e µ b ¯ b <
600 GeV and (b) m e µ b ¯ b >
600 GeV. The data are shown by the points with error barsindicating the total uncertainty, and compared to the predictions from various t ¯ t simulation samples (see text) shownas smooth curves. The lower plots show the ratio of predictions to data, with the data uncertainty being indicatedby the shaded band, and the Q thresholds corresponding to the left edges of the histogram bins, except for the firstbin. [GeV] bb m e m0 100 200 300 400 500 600 700 800 900 1000 pa r t gap f FGap vs Mass, Q0=25 GeV -1 =8 TeV, 20.3 fbsveto region: |y| < 2.1 ATLAS =25 QGeV=40 QGeV=70 QGeV=100 QGeV ¥ Powheg+PY6 hdamp = t Powheg+PY6 hdamp = m t Powheg+PY8 hdamp = mMC@NLO+HW ¥ Powheg+HW hdamp = Total uncertainty
FGap vs Mass, Q0=25 GeV
Figure 19: The gap fraction measurement f m ( Q ) as a function of the invariant mass m e µ b ¯ b , for several di ff erentvalues of Q . The data are shown as points with error bars indicating the statistical uncertainties and shaded boxesthe total uncertainties. The data are compared to the predictions from various t ¯ t simulation samples. Q m <
300 GeV 300 < m <
425 GeV 425 < m <
600 GeV m >
600 GeVGenerator χ p -value χ p -value χ p -value χ p -valueP owheg+ P ythia h damp = ∞ × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − MC@NLO + H erwig × − × − × − × − P owheg+ H erwig h damp = ∞ × − × − × − × − A lpgen+ H erwig × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia q down 24.1 1.5 × − × − × − × − M ad G raph+ P ythia q up 27.6 6.9 × − × − × − × − Table 10: Values of χ for the comparison of the measured gap fraction distributions with the predictions fromvarious t ¯ t generator configurations, for the four invariant mass m e µ b ¯ b regions as a function of Q . The χ and p -values correspond to 18 degrees of freedom. sum m <
300 GeV 300 < m <
425 GeV 425 < m <
600 GeV m >
600 GeVGenerator χ p -value χ p -value χ p -value χ p -valueP owheg+ P ythia h damp = ∞ × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − P owheg+ P ythia h damp = m t × − × − × − × − MC@NLO + H erwig × − × − × − × − P owheg+ H erwig h damp = ∞ × − × − × − × − A lpgen+ H erwig × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A cer MC + P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − A lpgen+ P ythia × − × − × − × − M ad G raph+ P ythia q down 37.2 2.3 × − × − × − × − M ad G raph+ P ythia q up 40.2 1.0 × − × − × − × − Table 11: Values of χ for the comparison of the measured gap fraction distributions with the predictions fromvarious t ¯ t generator configurations, for the four invariant mass m e µ b ¯ b regions as a function of Q sum . The χ and p -values correspond to 22 degrees of freedom. and 19 that in the 425 < m e µ b ¯ b <
600 GeV region, the NLO generator predictions split into two groups,with P owheg + H erwig and P owheg + P ythia h damp = ∞ being consistent with the data, andP owheg + P ythia h damp = m t , P owheg + P ythia + H erwig predicting a slightlylarger gap fraction (and hence less radiation). In the region with m e µ b ¯ b >
600 GeV, the measurementuncertainties are too large to discriminate between the predictions.
Studies of the additional jet activity in dileptonic t ¯ t events with an opposite-sign e µ pair and two b -tagged jets have been presented, using 20.3 fb − of √ s = pp collision data collected by the ATLASdetector at the LHC. The measurements were corrected to the particle level and defined in a fiducial regioncorresponding closely to the experimental acceptance, facilitating comparisons with the predictions ofdi ff erent Monte Carlo t ¯ t event generators. The additional-jet multiplicity for various jet p T thresholdshas been measured in the pseudorapidity region | η | < .
5, together with the normalised di ff erential cross-sections as a function of the first to the fourth jet p T . The gap fraction, the fraction of events with noadditional jet above a certain p T threshold, has also been measured in the central rapidity region | y | < . y region, and as a function of the invariant mass of the e µ b ¯ b system. Taken together,these measurements can help to characterise the production of additional jets in t ¯ t events, an importanttest of QCD and a significant source of systematic uncertainty in many measurements and searches fornew physics at the LHC. The results will be made available in the H ep D ata repository and through theR ivet analysis framework.The measurements are generally well-described by the predictions of the next-to-leading-order gener-ators used in ATLAS physics analyses. Both P owheg (interfaced to P ythia
6, P ythia erwig ) andMC@NLO + H erwig give good descriptions of the p T spectrum of the first additional jet, althoughMC@NLO + H erwig does not describe higher jet multiplicities, or the gap fraction as a function of athreshold on the sum of the p T of all additional jets. The leading-order multi-leg generators A lpgen , in-terfaced to P ythia erwig , and M ad G raph interfaced to P ythia
6, are also generally compatible with37he data. The predictions of these generators are sensitive to the choice of QCD scale and parton showerparameters, and tuning to the precise measurements presented here o ff ers considerable scope for reducingthe range of parameter variations which need to be considered when evaluating t ¯ t modelling uncertain-ties, compared to the ranges derived from previous analyses based on smaller √ s = Acknowledgements
We thank CERN for the very successful operation of the LHC, as well as the support sta ff from ourinstitutions without whom ATLAS could not be operated e ffi ciently.We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW andFWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI,Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMTCR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DSM / IRFU, France; GNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, HongKong 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, Por-tugal; 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 andWallenberg 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 Ontario Innovation Trust, Canada; EPLANET, ERC, FP7, Ho-rizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex andIdex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Ger-many; 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; theRoyal Society and Leverhulme Trust, United Kingdom.The crucial computing support from all WLCG partners is acknowledged gratefully, in particular fromCERN, 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), the Tier-2 facilities worldwide and large non-WLCG resource pro-viders. Major contributors of computing resources are listed in Ref. [66].
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Benhar Noccioli , J. Benitez , D.P. Benjamin , J.R. Bensinger , S. Bentvelsen ,L. Beresford , M. Beretta , D. Berge , E. Bergeaas Kuutmann , N. Berger , J. Beringer ,S. Berlendis , N.R. Bernard , C. Bernius , F.U. Bernlochner , T. Berry , P. Berta , C. Bertella ,G. Bertoli , F. Bertolucci , I.A. Bertram , C. Bertsche , D. Bertsche , G.J. Besjes ,O. Bessidskaia Bylund , M. Bessner , N. Besson , C. Betancourt , S. Bethke ,A.J. Bevan , R.M. Bianchi , L. Bianchini , M. Bianco , O. Biebel , D. Biedermann ,R. Bielski , N.V. Biesuz , M. Biglietti , J. Bilbao De Mendizabal , T.R.V. Billoud ,H. Bilokon , M. Bindi , S. Binet , A. Bingul , C. Bini , S. Biondi , D.M. Bjergaard ,C.W. Black , J.E. Black , K.M. Black , D. Blackburn , R.E. Blair , J.-B. Blanchard ,J.E. Blanco , T. Blazek , I. Bloch , C. Blocker , W. Blum , ∗ , U. Blumenschein , S. Blunier ,43.J. Bobbink , V.S. Bobrovnikov , c , S.S. Bocchetta , A. Bocci , C. Bock , M. Boehler ,D. Boerner , J.A. Bogaerts , D. Bogavac , A.G. Bogdanchikov , C. Bohm , V. Boisvert ,P. Bokan , T. Bold , A.S. Boldyrev , M. Bomben , M. Bona , M. Boonekamp ,A. Borisov , G. Borissov , J. Bortfeldt , D. Bortoletto , V. Bortolotto , K. Bos ,D. Boscherini , M. Bosman , J.D. Bossio Sola , J. Boudreau , J. Bou ff ard ,E.V. Bouhova-Thacker , D. Boumediene , C. Bourdarios , S.K. Boutle , A. Boveia , J. Boyd ,I.R. Boyko , J. Bracinik , A. Brandt , G. Brandt , O. Brandt , U. Bratzler , B. Brau ,J.E. Brau , H.M. Braun , ∗ , W.D. Breaden Madden , K. Brendlinger , A.J. Brennan ,L. Brenner , R. Brenner , S. Bressler , T.M. Bristow , D. Britton , D. Britzger , F.M. Brochu ,I. Brock , R. Brock , G. Brooijmans , T. Brooks , W.K. Brooks , J. Brosamer , E. Brost ,J.H Broughton , P.A. Bruckman de Renstrom , D. Bruncko , R. Bruneliere , A. Bruni ,G. Bruni , L.S. Bruni , BH Brunt , M. Bruschi , N. Bruscino , P. Bryant , L. Bryngemark ,T. Buanes , Q. Buat , P. Buchholz , A.G. Buckley , I.A. Budagov , F. Buehrer , M.K. Bugge ,O. Bulekov , D. 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Casper , E. Castaneda-Miranda , R. Castelijn , A. Castelli ,V. Castillo Gimenez , N.F. Castro , i , A. Catinaccio , J.R. Catmore , A. Cattai , J. Caudron ,V. Cavaliere , E. Cavallaro , D. Cavalli , M. Cavalli-Sforza , V. Cavasinni ,F. Ceradini , L. Cerda Alberich , B.C. Cerio , A.S. Cerqueira , A. Cerri , L. Cerrito ,F. Cerutti , M. Cerv , A. Cervelli , S.A. Cetin , A. Chafaq , D. Chakraborty , S.K. Chan ,Y.L. Chan , P. Chang , J.D. Chapman , D.G. Charlton , A. Chatterjee , C.C. Chau ,C.A. Chavez Barajas , S. Che , S. Cheatham , A. Chegwidden , S. Chekanov ,S.V. Chekulaev , G.A. Chelkov , j , M.A. Chelstowska , C. Chen , H. Chen , K. Chen ,S. Chen , S. Chen , X. Chen , Y. Chen , H.C. Cheng , H.J Cheng , Y. Cheng ,A. Cheplakov , E. Cheremushkina , R. Cherkaoui El Moursli , V. Chernyatin , ∗ , E. Cheu ,L. Chevalier , V. Chiarella , G. Chiarelli , G. Chiodini , A.S. Chisholm , A. Chitan ,M.V. Chizhov , K. Choi , A.R. Chomont , S. Chouridou , B.K.B. Chow , V. Christodoulou ,D. Chromek-Burckhart , J. Chudoba , A.J. Chuinard , J.J. Chwastowski , L. Chytka ,G. Ciapetti , A.K. Ciftci , D. Cinca , V. Cindro , I.A. Cioara , C. Ciocca , A. Ciocio ,F. Cirotto , Z.H. Citron , M. Citterio , M. Ciubancan , A. Clark , B.L. Clark ,M.R. Clark , P.J. Clark , R.N. Clarke , C. Clement , Y. Coadou , M. Cobal ,A. Coccaro , J. Cochran , L. Co ff ey , L. Colasurdo , B. Cole , A.P. Colijn , J. Collot ,T. Colombo , G. Compostella , P. Conde Muiño , E. Coniavitis , S.H. Connell ,I.A. Connelly , V. Consorti , S. Constantinescu , G. Conti , F. Conventi , k , M. Cooke ,B.D. Cooper , A.M. Cooper-Sarkar , K.J.R. Cormier , T. Cornelissen , M. Corradi ,F. Corriveau , l , A. Corso-Radu , A. Cortes-Gonzalez , G. Cortiana , G. Costa , M.J. Costa ,D. Costanzo , G. Cottin , G. Cowan , B.E. Cox , K. Cranmer , S.J. Crawley , G. Cree ,44. Crépé-Renaudin , F. Crescioli , W.A. Cribbs , M. Crispin Ortuzar , M. Cristinziani ,V. Croft , G. Crosetti , A. Cueto , T. Cuhadar Donszelmann , J. Cummings , M. Curatolo ,J. Cúth , C. Cuthbert , H. Czirr , P. Czodrowski , G. D’amen , S. D’Auria , M. D’Onofrio ,M.J. Da Cunha Sargedas De Sousa , C. Da Via , W. Dabrowski , T. Dado , T. Dai ,O. Dale , F. Dallaire , C. Dallapiccola , M. Dam , J.R. Dandoy , N.P. Dang , A.C. Daniells ,N.S. Dann , M. Danninger , M. Dano Ho ff mann , V. Dao , G. Darbo , S. Darmora ,J. Dassoulas , A. Dattagupta , W. Davey , C. David , T. Davidek , M. Davies , P. Davison ,E. Dawe , I. Dawson , R.K. Daya-Ishmukhametova , K. De , R. de Asmundis ,A. De Benedetti , S. De Castro , S. De Cecco , N. De Groot , P. de Jong , H. De la Torre ,F. De Lorenzi , A. De Maria , D. De Pedis , A. De Salvo , U. De Sanctis , A. De Santo ,J.B. De Vivie De Regie , W.J. Dearnaley , R. Debbe , C. Debenedetti , D.V. Dedovich ,N. Dehghanian , I. Deigaard , M. Del Gaudio , J. Del Peso , T. Del Prete ,D. Delgove , F. Deliot , C.M. Delitzsch , M. Deliyergiyev , A. Dell’Acqua , L. Dell’Asta ,M. Dell’Orso , M. Della Pietra , k , D. della Volpe , M. Delmastro , P.A. Delsart ,D.A. DeMarco , S. Demers , M. Demichev , A. Demilly , S.P. Denisov , D. Denysiuk ,D. Derendarz , J.E. Derkaoui , F. Derue , P. Dervan , K. Desch , C. Deterre , K. Dette ,P.O. Deviveiros , A. Dewhurst , S. Dhaliwal , A. Di Ciaccio , L. Di Ciaccio ,W.K. Di Clemente , C. Di Donato , A. Di Girolamo , B. Di Girolamo , B. Di Micco ,R. Di Nardo , A. Di Simone , R. Di Sipio , D. Di Valentino , C. Diaconu , M. Diamond ,F.A. Dias , M.A. Diaz , E.B. Diehl , J. Dietrich , S. Diglio , A. Dimitrievska , J. Dingfelder ,P. Dita , S. Dita , F. Dittus , F. Djama , T. Djobava , J.I. Djuvsland , M.A.B. do Vale ,D. Dobos , M. Dobre , C. Doglioni , T. Dohmae , J. Dolejsi , Z. Dolezal ,B.A. Dolgoshein , ∗ , M. Donadelli , S. Donati , P. Dondero , J. Donini , J. Dopke ,A. Doria , M.T. Dova , A.T. Doyle , E. Drechsler , M. Dris , Y. Du , J. Duarte-Campderros ,E. Duchovni , G. Duckeck , O.A. Ducu , m , D. Duda , A. Dudarev , E.M. Du ffi eld ,L. Duflot , L. Duguid , M. Dührssen , M. Dumancic , M. Dunford , H. Duran Yildiz ,M. Düren , A. Durglishvili , D. Duschinger , B. Dutta , M. Dyndal , C. Eckardt , K.M. Ecker ,R.C. Edgar , N.C. Edwards , T. Eifert , G. Eigen , K. Einsweiler , T. Ekelof , M. El Kacimi ,V. Ellajosyula , M. Ellert , S. Elles , F. Ellinghaus , A.A. Elliot , N. Ellis , J. Elmsheuser ,M. Elsing , D. Emeliyanov , Y. Enari , O.C. Endner , M. Endo , J.S. Ennis , J. Erdmann ,A. Ereditato , G. Ernis , J. Ernst , M. Ernst , S. Errede , E. Ertel , M. Escalier , H. Esch ,C. Escobar , B. Esposito , A.I. Etienvre , E. Etzion , H. Evans , A. Ezhilov , F. Fabbri ,L. Fabbri , G. Facini , R.M. Fakhrutdinov , S. Falciano , R.J. Falla , J. Faltova , Y. Fang ,M. Fanti , A. Farbin , A. Farilla , C. Farina , E.M. Farina , T. Farooque , S. Farrell ,S.M. Farrington , P. Farthouat , F. Fassi , P. Fassnacht , D. Fassouliotis , M. Faucci Giannelli ,A. Favareto , W.J. Fawcett , L. Fayard , O.L. Fedin , n , W. Fedorko , S. Feigl ,L. Feligioni , C. Feng , E.J. Feng , H. Feng , A.B. Fenyuk , L. Feremenga ,P. Fernandez Martinez , S. Fernandez Perez , J. Ferrando , A. Ferrari , P. Ferrari , R. Ferrari ,D.E. Ferreira de Lima , A. Ferrer , D. Ferrere , C. Ferretti , A. Ferretto Parodi , F. Fiedler ,A. Filipˇciˇc , M. Filipuzzi , F. Filthaut , M. Fincke-Keeler , K.D. Finelli ,M.C.N. Fiolhais , L. Fiorini , A. Firan , A. Fischer , C. Fischer , J. Fischer , W.C. Fisher ,N. Flaschel , I. Fleck , P. Fleischmann , G.T. Fletcher , R.R.M. Fletcher , T. Flick ,A. Floderus , L.R. Flores Castillo , M.J. Flowerdew , G.T. Forcolin , A. Formica , A. Forti ,A.G. Foster , D. Fournier , H. Fox , S. Fracchia , P. Francavilla , M. Franchini ,D. Francis , L. Franconi , M. Franklin , M. Frate , M. Fraternali , D. Freeborn ,S.M. Fressard-Batraneanu , F. Friedrich , D. Froidevaux , J.A. Frost , C. Fukunaga ,E. Fullana Torregrosa , T. Fusayasu , J. Fuster , C. Gabaldon , O. Gabizon , A. Gabrielli ,45. Gabrielli , G.P. Gach , S. Gadatsch , S. Gadomski , G. Gagliardi , L.G. Gagnon ,P. Gagnon , C. Galea , B. Galhardo , E.J. Gallas , B.J. Gallop , P. Gallus , G. Galster ,K.K. Gan , J. Gao , Y. Gao , Y.S. Gao , f , F.M. Garay Walls , C. García ,J.E. García Navarro , M. Garcia-Sciveres , R.W. Gardner , N. Garelli , V. Garonne ,A. Gascon Bravo , C. Gatti , A. Gaudiello , G. Gaudio , B. Gaur , L. Gauthier ,I.L. Gavrilenko , C. Gay , G. Gaycken , E.N. Gazis , Z. Gecse , C.N.P. Gee ,Ch. Geich-Gimbel , M. Geisen , M.P. Geisler , C. Gemme , M.H. Genest , C. Geng , o ,S. Gentile , C. Gentsos , S. George , D. Gerbaudo , A. Gershon , S. Ghasemi ,H. Ghazlane , M. Ghneimat , B. Giacobbe , S. Giagu , P. Giannetti , B. Gibbard ,S.M. Gibson , M. Gignac , M. Gilchriese , T.P.S. Gillam , D. Gillberg , G. Gilles ,D.M. Gingrich , d , N. Giokaris , M.P. Giordani , F.M. Giorgi , F.M. Giorgi , P.F. Giraud ,P. Giromini , D. Giugni , F. Giuli , C. Giuliani , M. Giulini , B.K. Gjelsten , S. Gkaitatzis ,I. Gkialas , E.L. Gkougkousis , L.K. Gladilin , C. Glasman , J. Glatzer , P.C.F. Glaysher ,A. Glazov , M. Goblirsch-Kolb , J. Godlewski , S. Goldfarb , T. Golling , D. Golubkov ,A. Gomes , R. Gonçalo , J. Goncalves Pinto Firmino Da Costa , G. Gonella ,L. Gonella , A. Gongadze , S. González de la Hoz , G. Gonzalez Parra , S. Gonzalez-Sevilla ,L. Goossens , P.A. Gorbounov , H.A. Gordon , I. Gorelov , B. Gorini , E. Gorini ,A. Gorišek , E. Gornicki , A.T. Goshaw , C. Gössling , M.I. Gostkin , C.R. Goudet ,D. Goujdami , A.G. Goussiou , N. Govender , p , E. Gozani , L. Graber ,I. Grabowska-Bold , P.O.J. Gradin , P. Grafström , J. Gramling , E. Gramstad ,S. Grancagnolo , V. Gratchev , P.M. Gravila , H.M. Gray , E. Graziani , Z.D. Greenwood , q ,C. Grefe , K. Gregersen , I.M. Gregor , P. Grenier , K. Grevtsov , J. Gri ffi ths , A.A. Grillo ,K. Grimm , S. Grinstein , r , Ph. Gris , J.-F. Grivaz , S. Groh , J.P. Grohs , E. Gross ,J. Grosse-Knetter , G.C. Grossi , Z.J. Grout , L. Guan , W. Guan , J. Guenther , F. Guescini ,D. Guest , O. Gueta , E. Guido , T. Guillemin , S. Guindon , U. Gul , C. Gumpert ,J. Guo , Y. Guo , o , R. Gupta , S. Gupta , G. Gustavino , P. Gutierrez ,N.G. Gutierrez Ortiz , C. Gutschow , C. Guyot , C. Gwenlan , C.B. Gwilliam , A. Haas ,C. Haber , H.K. Hadavand , N. Haddad , A. Hadef , P. Haefner , S. Hageböck , Z. Hajduk ,H. Hakobyan , ∗ , M. Haleem , J. Haley , G. Halladjian , G.D. Hallewell , K. Hamacher ,P. Hamal , K. Hamano , A. Hamilton , G.N. Hamity , P.G. Hamnett , L. Han ,K. Hanagaki , s , K. Hanawa , M. Hance , B. Haney , S. Hanisch , P. Hanke , R. Hanna ,J.B. Hansen , J.D. Hansen , M.C. Hansen , P.H. Hansen , K. Hara , A.S. Hard ,T. Harenberg , F. Hariri , S. Harkusha , R.D. Harrington , P.F. Harrison , F. Hartjes ,N.M. Hartmann , M. Hasegawa , Y. Hasegawa , A. Hasib , S. Hassani , S. Haug ,R. Hauser , L. Hauswald , M. Havranek , C.M. Hawkes , R.J. Hawkings , D. Hayden ,C.P. Hays , J.M. Hays , H.S. Hayward , S.J. Haywood , S.J. Head , T. Heck , V. Hedberg ,L. Heelan , S. Heim , T. Heim , B. Heinemann , J.J. Heinrich , L. Heinrich , C. Heinz ,J. Hejbal , L. Helary , S. Hellman , C. Helsens , J. Henderson , R.C.W. Henderson ,Y. Heng , S. Henkelmann , A.M. Henriques Correia , S. Henrot-Versille , G.H. Herbert ,Y. Hernández Jiménez , G. Herten , R. Hertenberger , L. Hervas , G.G. Hesketh , N.P. Hessey ,J.W. Hetherly , R. Hickling , E. Higón-Rodriguez , E. Hill , J.C. Hill , K.H. Hiller ,S.J. Hillier , I. Hinchli ff e , E. Hines , R.R. Hinman , M. Hirose , D. Hirschbuehl , J. Hobbs ,N. Hod , M.C. Hodgkinson , P. Hodgson , A. Hoecker , M.R. Hoeferkamp , F. Hoenig ,D. Hohn , T.R. Holmes , M. Homann , T.M. Hong , B.H. Hooberman , W.H. Hopkins ,Y. Horii , A.J. Horton , J-Y. Hostachy , S. Hou , A. Hoummada , J. Howarth ,M. Hrabovsky , I. Hristova , J. Hrivnac , T. Hryn’ova , A. Hrynevich , C. Hsu , P.J. Hsu , t ,S.-C. Hsu , D. Hu , Q. Hu , Y. Huang , Z. Hubacek , F. Hubaut , F. Huegging ,46.B. Hu ff man , E.W. Hughes , G. Hughes , M. Huhtinen , P. Huo , N. Huseynov , b , J. Huston ,J. Huth , G. Iacobucci , G. Iakovidis , I. Ibragimov , L. Iconomidou-Fayard , E. Ideal ,Z. Idrissi , P. Iengo , O. Igonkina , u , T. Iizawa , Y. Ikegami , M. Ikeno , Y. Ilchenko ,v ,D. Iliadis , N. Ilic , T. Ince , G. Introzzi , P. Ioannou , ∗ , M. Iodice , K. Iordanidou ,V. Ippolito , N. Ishijima , M. Ishino , M. Ishitsuka , R. Ishmukhametov , C. Issever ,S. Istin , F. Ito , J.M. Iturbe Ponce , R. Iuppa , W. Iwanski , H. Iwasaki , J.M. Izen ,V. Izzo , S. Jabbar , B. Jackson , M. Jackson , P. Jackson , V. Jain , K.B. Jakobi , K. Jakobs ,S. Jakobsen , T. Jakoubek , D.O. Jamin , D.K. Jana , E. Jansen , R. Jansky , J. Janssen ,M. Janus , G. Jarlskog , N. Javadov , b , T. Jav˚urek , F. Jeanneau , L. Jeanty , J. Jejelava ,w ,G.-Y. Jeng , D. Jennens , P. Jenni , x , J. Jentzsch , C. Jeske , S. Jézéquel , H. Ji , J. Jia ,H. Jiang , Y. Jiang , S. Jiggins , J. Jimenez Pena , S. Jin , A. Jinaru , O. Jinnouchi ,P. Johansson , K.A. Johns , W.J. Johnson , K. Jon-And , G. Jones , R.W.L. Jones ,S. Jones , T.J. Jones , J. Jongmanns , P.M. Jorge , J. Jovicevic , X. Ju ,A. Juste Rozas , r , M.K. Köhler , A. Kaczmarska , M. Kado , H. Kagan , M. Kagan ,S.J. Kahn , E. Kajomovitz , C.W. Kalderon , A. Kaluza , S. Kama , A. Kamenshchikov ,N. Kanaya , S. Kaneti , L. Kanjir , V.A. Kantserov , J. Kanzaki , B. Kaplan , L.S. Kaplan ,A. Kapliy , D. Kar , K. Karakostas , A. Karamaoun , N. Karastathis , M.J. Kareem ,E. Karentzos , M. Karnevskiy , S.N. Karpov , Z.M. Karpova , K. Karthik , V. Kartvelishvili ,A.N. Karyukhin , K. Kasahara , L. Kashif , R.D. Kass , A. Kastanas , Y. Kataoka ,C. Kato , A. Katre , J. Katzy , K. Kawagoe , T. Kawamoto , G. Kawamura , S. Kazama ,V.F. Kazanin , c , R. Keeler , R. Kehoe , J.S. Keller , J.J. Kempster , K Kentaro ,H. Keoshkerian , O. Kepka , B.P. Kerševan , S. Kersten , R.A. Keyes , M. Khader ,F. Khalil-zada , A. Khanov , A.G. Kharlamov , c , T.J. Khoo , V. Khovanskiy , E. Khramov ,J. Khubua ,y , S. Kido , H.Y. Kim , S.H. Kim , Y.K. Kim , N. Kimura , O.M. Kind ,B.T. King , M. King , S.B. King , J. Kirk , A.E. Kiryunin , T. Kishimoto , D. Kisielewska ,F. Kiss , K. Kiuchi , O. Kivernyk , E. Kladiva , M.H. Klein , M. Klein , U. Klein ,K. Kleinknecht , P. Klimek , A. Klimentov , R. Klingenberg , J.A. Klinger , T. Klioutchnikova ,E.-E. Kluge , P. Kluit , S. Kluth , J. Knapik , E. Kneringer , E.B.F.G. Knoops , A. Knue ,A. Kobayashi , D. Kobayashi , T. Kobayashi , M. Kobel , M. Kocian , P. Kodys , T. Ko ff as ,E. Ko ff eman , T. Koi , H. Kolanoski , M. Kolb , I. Koletsou , A.A. Komar , ∗ , Y. Komori ,T. Kondo , N. Kondrashova , K. Köneke , A.C. König , T. Kono , z , R. Konoplich , aa ,N. Konstantinidis , R. Kopeliansky , S. Koperny , L. Köpke , A.K. Kopp , K. Korcyl ,K. Kordas , A. Korn , A.A. Korol , c , I. Korolkov , E.V. Korolkova , O. Kortner ,S. Kortner , T. Kosek , V.V. Kostyukhin , A. Kotwal , A. Kourkoumeli-Charalampidi ,C. Kourkoumelis , V. Kouskoura , A.B. Kowalewska , R. Kowalewski , T.Z. Kowalski ,C. Kozakai , W. Kozanecki , A.S. Kozhin , V.A. Kramarenko , G. Kramberger ,D. Krasnopevtsev , M.W. Krasny , A. Krasznahorkay , J.K. Kraus , A. Kravchenko , M. Kretz ,J. Kretzschmar , K. Kreutzfeldt , P. Krieger , K. Krizka , K. Kroeninger , H. Kroha ,J. Kroll , J. Kroseberg , J. Krstic , U. Kruchonak , H. Krüger , N. Krumnack , A. Kruse ,M.C. Kruse , M. Kruskal , T. Kubota , H. Kucuk , S. Kuday , J.T. Kuechler , S. Kuehn ,A. Kugel , F. Kuger , A. Kuhl , T. Kuhl , V. Kukhtin , R. Kukla , Y. Kulchitsky ,S. Kuleshov , M. Kuna , T. Kunigo , A. Kupco , H. Kurashige , Y.A. Kurochkin ,V. Kus , E.S. Kuwertz , M. Kuze , J. Kvita , T. Kwan , D. Kyriazopoulos , A. La Rosa ,J.L. La Rosa Navarro , L. La Rotonda , C. Lacasta , F. Lacava , J. Lacey , H. Lacker ,D. Lacour , V.R. Lacuesta , E. Ladygin , R. Lafaye , B. Laforge , T. Lagouri , S. Lai ,S. Lammers , W. Lampl , E. Lançon , U. Landgraf , M.P.J. Landon , M.C. Lanfermann ,V.S. Lang , J.C. Lange , A.J. Lankford , F. Lanni , K. Lantzsch , A. Lanza , S. Laplace ,47. Lapoire , J.F. Laporte , T. Lari , F. Lasagni Manghi , M. Lassnig , P. Laurelli ,W. Lavrijsen , A.T. Law , P. Laycock , T. Lazovich , M. Lazzaroni , B. Le , O. Le Dortz ,E. Le Guirriec , E.P. Le Quilleuc , M. LeBlanc , T. LeCompte , F. Ledroit-Guillon , C.A. Lee ,S.C. Lee , L. Lee , G. Lefebvre , M. Lefebvre , F. Legger , C. Leggett , A. Lehan ,G. Lehmann Miotto , X. Lei , W.A. Leight , A. Leisos , ab , A.G. Leister , M.A.L. Leite ,R. Leitner , D. Lellouch , B. Lemmer , K.J.C. Leney , T. Lenz , B. Lenzi , R. Leone ,S. Leone , C. Leonidopoulos , S. Leontsinis , G. Lerner , C. Leroy , A.A.J. Lesage ,C.G. Lester , M. Levchenko , J. Levêque , D. Levin , L.J. Levinson , M. Levy , D. Lewis ,A.M. Leyko , M. Leyton , B. Li , o , H. Li , H.L. Li , L. Li , L. Li , Q. Li , S. Li , X. Li ,Y. Li , Z. Liang , B. Liberti , A. Liblong , P. Lichard , K. Lie , J. Liebal , W. Liebig ,A. Limosani , S.C. Lin , ac , T.H. Lin , B.E. Lindquist , A.E. Lionti , E. Lipeles ,A. Lipniacka , M. Lisovyi , T.M. Liss , A. Lister , A.M. Litke , B. Liu , ad , D. Liu ,H. Liu , H. Liu , J. Liu , J.B. Liu , K. Liu , L. Liu , M. Liu , M. Liu , Y.L. Liu , Y. Liu ,M. Livan , A. Lleres , J. Llorente Merino , S.L. Lloyd , F. Lo Sterzo , E. Lobodzinska ,P. Loch , W.S. Lockman , F.K. Loebinger , A.E. Loevschall-Jensen , K.M. Loew ,A. Loginov , ∗ , T. Lohse , K. Lohwasser , M. Lokajicek , B.A. Long , J.D. Long , R.E. Long ,L. Longo , K.A. Looper , L. Lopes , D. Lopez Mateos , B. Lopez Paredes , I. Lopez Paz ,A. Lopez Solis , J. Lorenz , N. Lorenzo Martinez , M. Losada , P.J. Lösel , X. Lou ,A. Lounis , J. Love , P.A. Love , H. Lu , N. Lu , H.J. Lubatti , C. Luci , A. Lucotte ,C. Luedtke , F. Luehring , W. Lukas , L. Luminari , O. Lundberg , B. Lund-Jensen ,P.M. Luzi , D. Lynn , R. Lysak , E. Lytken , V. Lyubushkin , H. Ma , L.L. Ma , Y. Ma ,G. Maccarrone , A. Macchiolo , C.M. Macdonald , B. Maˇcek , J. Machado Miguens ,D. Mada ff ari , R. Madar , H.J. Maddocks , W.F. Mader , A. Madsen , J. Maeda , S. Maeland ,T. Maeno , A. Maevskiy , E. Magradze , J. Mahlstedt , C. Maiani , C. Maidantchik ,A.A. Maier , T. Maier , A. Maio , S. Majewski , Y. Makida , N. Makovec ,B. Malaescu , Pa. Malecki , V.P. Maleev , F. Malek , U. Mallik , D. Malon , C. Malone ,S. Maltezos , S. Malyukov , J. Mamuzic , G. Mancini , B. Mandelli , L. Mandelli , I. Mandi´c ,J. Maneira , L. Manhaes de Andrade Filho , J. Manjarres Ramos , A. Mann ,A. Manousos , B. Mansoulie , J.D. Mansour , R. Mantifel , M. Mantoani , S. Manzoni ,L. Mapelli , G. Marceca , L. March , G. Marchiori , M. Marcisovsky , M. Marjanovic ,D.E. Marley , F. Marroquim , S.P. Marsden , Z. Marshall , S. Marti-Garcia , B. Martin ,T.A. Martin , V.J. Martin , B. Martin dit Latour , M. Martinez , r , V.I. Martinez Outschoorn ,S. Martin-Haugh , V.S. Martoiu , A.C. Martyniuk , M. Marx , A. Marzin , L. Masetti ,T. Mashimo , R. Mashinistov , J. Masik , A.L. Maslennikov , c , I. Massa , L. Massa ,P. Mastrandrea , A. Mastroberardino , T. Masubuchi , P. Mättig , J. Mattmann , J. Maurer ,S.J. Maxfield , D.A. Maximov , c , R. Mazini , S.M. Mazza , N.C. Mc Fadden ,G. Mc Goldrick , S.P. Mc Kee , A. McCarn , R.L. McCarthy , T.G. McCarthy ,L.I. McClymont , E.F. McDonald , J.A. Mcfayden , G. Mchedlidze , S.J. McMahon ,R.A. McPherson , l , M. Medinnis , S. Meehan , S. Mehlhase , A. Mehta , K. Meier ,C. Meineck , B. Meirose , D. Melini , B.R. Mellado Garcia , M. Melo , F. Meloni ,A. Mengarelli , S. Menke , E. Meoni , S. Mergelmeyer , P. Mermod , L. Merola ,C. Meroni , F.S. Merritt , A. Messina , J. Metcalfe , A.S. Mete , C. Meyer , C. Meyer ,J-P. Meyer , J. Meyer , H. Meyer Zu Theenhausen , F. Miano , R.P. Middleton ,S. Miglioranzi , L. Mijovi´c , G. Mikenberg , M. Mikestikova , M. Mikuž , M. Milesi ,A. Milic , D.W. Miller , C. Mills , A. Milov , D.A. Milstead , A.A. Minaenko ,Y. Minami , I.A. Minashvili , A.I. Mincer , B. Mindur , M. Mineev , Y. Ming , L.M. Mir ,K.P. Mistry , T. Mitani , J. Mitrevski , V.A. Mitsou , A. Miucci , P.S. Miyagawa ,48.U. Mjörnmark , T. Moa , K. Mochizuki , S. Mohapatra , S. Molander ,R. Moles-Valls , R. Monden , M.C. Mondragon , K. Mönig , J. Monk , E. Monnier ,A. Montalbano , J. Montejo Berlingen , F. Monticelli , S. Monzani , R.W. Moore ,N. Morange , D. Moreno , M. Moreno Llácer , P. Morettini , D. Mori , T. Mori , M. Morii ,M. Morinaga , V. Morisbak , S. Moritz , A.K. Morley , G. Mornacchi , J.D. Morris ,S.S. Mortensen , L. Morvaj , M. Mosidze , J. Moss , K. Motohashi , R. Mount ,E. Mountricha , S.V. Mouraviev , ∗ , E.J.W. Moyse , S. Muanza , R.D. Mudd , F. Mueller ,J. Mueller , R.S.P. Mueller , T. Mueller , D. Muenstermann , P. Mullen , G.A. Mullier ,F.J. Munoz Sanchez , J.A. Murillo Quijada , W.J. Murray , H. Musheghyan , M. Muškinja ,A.G. Myagkov , ae , M. Myska , B.P. Nachman , O. Nackenhorst , K. Nagai , R. Nagai , z ,K. Nagano , Y. Nagasaka , K. Nagata , M. Nagel , E. Nagy , A.M. Nairz , Y. Nakahama ,K. Nakamura , T. Nakamura , I. Nakano , H. Namasivayam , R.F. Naranjo Garcia ,R. Narayan , D.I. Narrias Villar , I. Naryshkin , T. Naumann , G. Navarro , R. Nayyar ,H.A. Neal , P.Yu. Nechaeva , T.J. Neep , P.D. Nef , A. Negri , M. Negrini ,S. Nektarijevic , C. Nellist , A. Nelson , S. Nemecek , P. Nemethy , A.A. Nepomuceno ,M. Nessi , a f , M.S. Neubauer , M. Neumann , R.M. Neves , P. Nevski , P.R. Newman ,D.H. Nguyen , T. Nguyen Manh , R.B. Nickerson , R. Nicolaidou , J. Nielsen , A. Nikiforov ,V. Nikolaenko , ae , I. Nikolic-Audit , K. Nikolopoulos , J.K. Nilsen , P. Nilsson , Y. Ninomiya ,A. Nisati , R. Nisius , T. Nobe , M. Nomachi , I. Nomidis , T. Nooney , S. Norberg ,M. Nordberg , N. Norjoharuddeen , O. Novgorodova , S. Nowak , M. Nozaki , L. Nozka ,K. Ntekas , E. Nurse , F. Nuti , F. O’grady , D.C. O’Neil , A.A. O’Rourke , V. O’Shea ,F.G. Oakham , d , H. Oberlack , T. Obermann , J. Ocariz , A. Ochi , I. Ochoa ,J.P. Ochoa-Ricoux , S. Oda , S. Odaka , H. Ogren , A. Oh , S.H. Oh , C.C. Ohm ,H. Ohman , H. Oide , H. Okawa , Y. Okumura , T. Okuyama , A. Olariu ,L.F. Oleiro Seabra , S.A. Olivares Pino , D. Oliveira Damazio , A. Olszewski , J. Olszowska ,A. Onofre , K. Onogi , P.U.E. Onyisi ,v , M.J. Oreglia , Y. Oren , D. Orestano ,N. Orlando , R.S. Orr , B. Osculati , R. Ospanov , G. Otero y Garzon , H. Otono ,M. Ouchrif , F. Ould-Saada , A. Ouraou , K.P. Oussoren , Q. Ouyang , M. Owen ,R.E. Owen , V.E. Ozcan , N. Ozturk , K. Pachal , A. Pacheco Pages , L. Pacheco Rodriguez ,C. Padilla Aranda , M. Pagáˇcová , S. Pagan Griso , F. Paige , P. Pais , K. Pajchel ,G. Palacino , S. Palestini , M. Palka , D. Pallin , A. Palma , E.St. Panagiotopoulou ,C.E. Pandini , J.G. Panduro Vazquez , P. Pani , S. Panitkin , D. Pantea , L. Paolozzi ,Th.D. Papadopoulou , K. Papageorgiou , A. Paramonov , D. Paredes Hernandez , A.J. Parker ,M.A. Parker , K.A. Parker , F. Parodi , J.A. Parsons , U. Parzefall , V.R. Pascuzzi ,E. Pasqualucci , S. Passaggio , Fr. Pastore , G. Pásztor , a g , S. Pataraia , J.R. Pater , T. Pauly ,J. Pearce , B. Pearson , L.E. Pedersen , M. Pedersen , S. Pedraza Lopez , R. Pedro ,S.V. Peleganchuk , c , D. Pelikan , O. Penc , C. Peng , H. Peng , J. Penwell , B.S. Peralva ,M.M. Perego , D.V. Perepelitsa , E. Perez Codina , L. Perini , H. Pernegger ,S. Perrella , R. Peschke , V.D. Peshekhonov , K. Peters , R.F.Y. Peters , B.A. Petersen ,T.C. Petersen , E. Petit , A. Petridis , C. Petridou , P. Petro ff , E. Petrolo , M. Petrov ,F. Petrucci , N.E. Pettersson , A. Peyaud , R. Pezoa , P.W. Phillips , G. Piacquadio ,E. Pianori , A. Picazio , E. Piccaro , M. Piccinini , M.A. Pickering , R. Piegaia ,J.E. Pilcher , A.D. Pilkington , A.W.J. Pin , M. Pinamonti , ah , J.L. Pinfold , A. Pingel ,S. Pires , H. Pirumov , M. Pitt , L. Plazak , M.-A. Pleier , V. Pleskot , E. Plotnikova ,P. Plucinski , D. Pluth , R. Poettgen , L. Poggioli , D. Pohl , G. Polesello , A. Poley ,A. Policicchio , R. Polifka , A. Polini , C.S. Pollard , V. Polychronakos , K. Pommès ,L. Pontecorvo , B.G. Pope , G.A. Popeneciu , D.S. Popovic , A. Poppleton , S. Pospisil ,49. Potamianos , I.N. Potrap , C.J. Potter , C.T. Potter , G. Poulard , J. Poveda ,V. Pozdnyakov , M.E. Pozo Astigarraga , P. Pralavorio , A. Pranko , S. Prell , D. Price ,L.E. Price , M. Primavera , S. Prince , K. Prokofiev , F. Prokoshin , S. Protopopescu ,J. Proudfoot , M. Przybycien , D. Puddu , M. Purohit , ai , P. Puzo , J. Qian , G. Qin ,Y. Qin , A. Quadt , W.B. Quayle , M. Queitsch-Maitland , D. Quilty , S. Raddum ,V. Radeka , V. Radescu , S.K. Radhakrishnan , P. Radlo ff , P. Rados , F. Ragusa ,G. Rahal , J.A. Raine , S. Rajagopalan , M. Rammensee , C. Rangel-Smith , M.G. Ratti ,F. Rauscher , S. Rave , T. Ravenscroft , I. Ravinovich , M. Raymond , A.L. Read ,N.P. Readio ff , M. Reale , D.M. Rebuzzi , A. Redelbach , G. Redlinger , R. Reece ,K. Reeves , L. Rehnisch , J. Reichert , H. Reisin , C. Rembser , H. Ren , M. Rescigno ,S. Resconi , O.L. Rezanova , c , P. Reznicek , R. Rezvani , R. Richter , S. Richter ,E. Richter-Was , O. Ricken , M. Ridel , P. Rieck , C.J. Riegel , J. Rieger , O. Rifki ,M. Rijssenbeek , A. Rimoldi , M. Rimoldi , L. Rinaldi , B. Risti´c , E. Ritsch , I. Riu ,F. Rizatdinova , E. Rizvi , C. Rizzi , S.H. Robertson , l , A. Robichaud-Veronneau , D. Robinson ,J.E.M. Robinson , A. Robson , C. Roda , Y. Rodina , A. Rodriguez Perez ,D. Rodriguez Rodriguez , S. Roe , C.S. Rogan , O. Røhne , A. Romaniouk , M. Romano ,S.M. Romano Saez , E. Romero Adam , N. Rompotis , M. Ronzani , L. Roos , E. Ros ,S. Rosati , K. Rosbach , P. Rose , O. Rosenthal , N.-A. Rosien , V. Rossetti ,E. Rossi , L.P. Rossi , J.H.N. Rosten , R. Rosten , M. Rotaru , I. Roth , J. Rothberg ,D. Rousseau , C.R. Royon , A. Rozanov , Y. Rozen , X. Ruan , F. Rubbo ,M.S. Rudolph , F. Rühr , A. Ruiz-Martinez , Z. Rurikova , N.A. Rusakovich , A. Ruschke ,H.L. Russell , J.P. Rutherfoord , N. Ruthmann , Y.F. Ryabov , M. Rybar , G. Rybkin , S. Ryu ,A. Ryzhov , G.F. Rzehorz , A.F. Saavedra , G. Sabato , S. Sacerdoti , H.F-W. Sadrozinski ,R. Sadykov , F. Safai Tehrani , P. Saha , M. Sahinsoy , M. Saimpert , T. Saito ,H. Sakamoto , Y. Sakurai , G. Salamanna , A. Salamon , J.E. Salazar Loyola ,D. Salek , P.H. Sales De Bruin , D. Salihagic , A. Salnikov , J. Salt , D. Salvatore ,F. Salvatore , A. Salvucci , A. Salzburger , D. Sammel , D. Sampsonidis , A. Sanchez ,J. Sánchez , V. Sanchez Martinez , H. Sandaker , R.L. Sandbach , H.G. Sander ,M. Sandho ff , C. Sandoval , R. Sandstroem , D.P.C. Sankey , M. Sannino , A. Sansoni ,C. Santoni , R. Santonico , H. Santos , I. Santoyo Castillo , K. Sapp , A. Sapronov ,J.G. Saraiva , B. Sarrazin , O. Sasaki , Y. Sasaki , K. Sato , G. Sauvage , ∗ , E. Sauvan ,G. Savage , P. Savard , d , C. Sawyer , L. Sawyer , q , J. Saxon , C. Sbarra , A. Sbrizzi ,T. Scanlon , D.A. Scannicchio , M. Scarcella , V. Scarfone , J. Schaarschmidt ,P. Schacht , B.M. Schachtner , D. Schaefer , R. Schaefer , J. Schae ff er , S. Schaepe ,S. Schaetzel , U. Schäfer , A.C. Scha ff er , D. Schaile , R.D. Schamberger , V. Scharf ,V.A. Schegelsky , D. Scheirich , M. Schernau , C. Schiavi , S. Schier , C. Schillo ,M. Schioppa , S. Schlenker , K.R. Schmidt-Sommerfeld , K. Schmieden , C. Schmitt ,S. Schmitt , S. Schmitz , B. Schneider , U. Schnoor , L. Schoe ff el , A. Schoening ,B.D. Schoenrock , E. Schopf , M. Schott , J. Schovancova , S. Schramm , M. Schreyer ,N. Schuh , A. Schulte , M.J. Schultens , H.-C. Schultz-Coulon , H. Schulz , M. Schumacher ,B.A. Schumm , Ph. Schune , A. Schwartzman , T.A. Schwarz , Ph. Schwegler ,H. Schweiger , Ph. Schwemling , R. Schwienhorst , J. Schwindling , T. Schwindt , G. Sciolla ,F. Scuri , F. Scutti , J. Searcy , P. Seema , S.C. Seidel , A. Seiden , F. Seifert ,J.M. Seixas , G. Sekhniaidze , K. Sekhon , S.J. Sekula , D.M. Seliverstov , ∗ ,N. Semprini-Cesari , C. Serfon , L. Serin , L. Serkin , M. Sessa , R. Seuster ,H. Severini , T. Sfiligoj , F. Sforza , A. Sfyrla , E. Shabalina , N.W. Shaikh , L.Y. Shan ,R. Shang , J.T. Shank , M. Shapiro , P.B. Shatalov , K. Shaw , S.M. Shaw ,50. Shcherbakova , C.Y. Shehu , P. Sherwood , L. Shi , a j , S. Shimizu , C.O. Shimmin ,M. Shimojima , M. Shiyakova , ak , A. Shmeleva , D. Shoaleh Saadi , M.J. Shochet ,S. Shojaii , S. Shrestha , E. Shulga , M.A. Shupe , P. Sicho , A.M. Sickles , P.E. Sidebo ,O. Sidiropoulou , D. Sidorov , A. Sidoti , F. Siegert , Dj. Sijacki , J. Silva ,S.B. Silverstein , V. Simak , O. Simard , Lj. Simic , S. Simion , E. Simioni , B. Simmons ,D. Simon , M. Simon , P. Sinervo , N.B. Sinev , M. Sioli , G. Siragusa ,S.Yu. Sivoklokov , J. Sjölin , M.B. Skinner , H.P. Skottowe , P. Skubic , M. Slater ,T. Slavicek , M. Slawinska , K. Sliwa , R. Slovak , V. Smakhtin , B.H. Smart , L. Smestad ,J. Smiesko , S.Yu. Smirnov , Y. Smirnov , L.N. Smirnova , al , O. Smirnova , M.N.K. Smith ,R.W. Smith , M. Smizanska , K. Smolek , A.A. Snesarev , S. Snyder , R. Sobie , l , F. Socher ,A. So ff er , D.A. Soh , G. Sokhrannyi , C.A. Solans Sanchez , M. Solar , E.Yu. Soldatov ,U. Soldevila , A.A. Solodkov , A. Soloshenko , O.V. Solovyanov , V. Solovyev , P. Sommer ,H. Son , H.Y. Song , am , A. Sood , A. Sopczak , V. Sopko , V. Sorin , D. Sosa ,C.L. Sotiropoulou , R. Soualah , A.M. Soukharev , c , D. South , B.C. Sowden ,S. Spagnolo , M. Spalla , M. Spangenberg , F. Spanò , D. Sperlich , F. Spettel ,R. Spighi , G. Spigo , L.A. Spiller , M. Spousta , R.D. St. Denis , ∗ , A. Stabile , R. Stamen ,S. Stamm , E. Stanecka , R.W. Stanek , C. Stanescu , M. Stanescu-Bellu , M.M. Stanitzki ,S. Stapnes , E.A. Starchenko , G.H. Stark , J. Stark , P. Staroba , P. Starovoitov , S. Stärz ,R. Staszewski , P. Steinberg , B. Stelzer , H.J. Stelzer , O. Stelzer-Chilton , H. Stenzel ,G.A. Stewart , J.A. Stillings , M.C. Stockton , M. Stoebe , G. Stoicea , P. Stolte , S. Stonjek ,A.R. Stradling , A. Straessner , M.E. Stramaglia , J. Strandberg , S. Strandberg ,A. Strandlie , M. Strauss , P. Strizenec , R. Ströhmer , D.M. Strom , R. Stroynowski ,A. Strubig , S.A. Stucci , B. Stugu , N.A. Styles , D. Su , J. Su , S. Suchek , Y. Sugaya ,M. Suk , V.V. Sulin , S. Sultansoy , T. Sumida , S. Sun , X. Sun , J.E. Sundermann ,K. Suruliz , G. Susinno , M.R. Sutton , S. Suzuki , M. Svatos , M. Swiatlowski ,I. Sykora , T. Sykora , D. Ta , C. Taccini , K. Tackmann , J. Taenzer , A. Ta ff ard ,R. Tafirout , N. Taiblum , H. Takai , R. Takashima , T. Takeshita , Y. Takubo , M. Talby ,A.A. Talyshev , c , K.G. Tan , J. Tanaka , R. Tanaka , S. Tanaka , B.B. Tannenwald ,S. Tapia Araya , S. Tapprogge , S. Tarem , G.F. Tartarelli , P. Tas , M. Tasevsky ,T. Tashiro , E. Tassi , A. Tavares Delgado , Y. Tayalati , A.C. Taylor , G.N. Taylor ,P.T.E. Taylor , W. Taylor , F.A. Teischinger , P. Teixeira-Dias , K.K. Temming , D. Temple ,H. Ten Kate , P.K. Teng , J.J. Teoh , F. Tepel , S. Terada , K. Terashi , J. Terron , S. Terzo ,M. Testa , R.J. Teuscher , l , T. Theveneaux-Pelzer , J.P. Thomas , J. Thomas-Wilsker ,E.N. Thompson , P.D. Thompson , A.S. Thompson , L.A. Thomsen , E. Thomson ,M. Thomson , M.J. Tibbetts , R.E. Ticse Torres , V.O. Tikhomirov , an , Yu.A. Tikhonov , c ,S. Timoshenko , P. Tipton , S. Tisserant , K. Todome , T. Todorov , ∗ , S. Todorova-Nova ,J. Tojo , S. Tokár , K. Tokushuku , E. Tolley , L. Tomlinson , M. Tomoto , L. Tompkins , ao ,K. Toms , B. Tong , E. Torrence , H. Torres , E. Torró Pastor , J. Toth , ap , F. Touchard ,D.R. Tovey , T. Trefzger , A. Tricoli , I.M. Trigger , S. Trincaz-Duvoid , M.F. Tripiana ,W. Trischuk , B. Trocmé , A. Trofymov , C. Troncon , M. Trottier-McDonald , M. Trovatelli ,L. Truong , M. Trzebinski , A. Trzupek , J.C-L. Tseng , P.V. Tsiareshka , G. Tsipolitis ,N. Tsirintanis , S. Tsiskaridze , V. Tsiskaridze , E.G. Tskhadadze , K.M. Tsui , I.I. Tsukerman ,V. Tsulaia , S. Tsuno , D. Tsybychev , A. Tudorache , V. Tudorache , A.N. Tuna ,S.A. Tupputi , S. Turchikhin , al , D. Turecek , D. Turgeman , R. Turra , A.J. Turvey ,P.M. Tuts , M. Tyndel , G. Ucchielli , I. Ueda , M. Ughetto , F. Ukegawa ,G. Unal , A. Undrus , G. Unel , F.C. Ungaro , Y. Unno , C. Unverdorben , J. Urban ,P. Urquijo , P. Urrejola , G. Usai , A. Usanova , L. Vacavant , V. Vacek , B. Vachon ,51. Valderanis , E. Valdes Santurio , N. Valencic , S. Valentinetti , A. Valero ,L. Valery , S. Valkar , S. Vallecorsa , J.A. Valls Ferrer , W. Van Den Wollenberg ,P.C. Van Der Deijl , R. van der Geer , H. van der Graaf , N. van Eldik , P. van Gemmeren ,J. Van Nieuwkoop , I. van Vulpen , M.C. van Woerden , M. Vanadia , W. Vandelli ,R. Vanguri , A. Vaniachine , P. Vankov , G. Vardanyan , R. Vari , E.W. Varnes , T. Varol ,D. Varouchas , A. Vartapetian , K.E. Varvell , J.G. Vasquez , F. Vazeille ,T. Vazquez Schroeder , J. Veatch , L.M. Veloce , F. Veloso , S. Veneziano ,A. Ventura , M. Venturi , N. Venturi , A. Venturini , V. Vercesi , M. Verducci ,W. Verkerke , J.C. Vermeulen , A. Vest , aq , M.C. Vetterli , d , O. Viazlo , I. Vichou , ∗ ,T. Vickey , O.E. Vickey Boeriu , G.H.A. Viehhauser , S. Viel , L. Vigani , M. Villa ,M. Villaplana Perez , E. Vilucchi , M.G. Vincter , V.B. Vinogradov , C. Vittori ,I. Vivarelli , S. Vlachos , M. Vlasak , M. Vogel , P. Vokac , G. Volpi , M. Volpi ,H. von der Schmitt , E. von Toerne , V. Vorobel , K. Vorobev , M. Vos , R. Voss ,J.H. Vossebeld , N. Vranjes , M. Vranjes Milosavljevic , V. Vrba , M. Vreeswijk ,R. Vuillermet , I. Vukotic , Z. Vykydal , P. Wagner , W. Wagner , H. Wahlberg ,S. Wahrmund , J. Wakabayashi , J. Walder , R. Walker , W. Walkowiak , V. Wallangen ,C. Wang , C. Wang , F. Wang , H. Wang , H. Wang , J. Wang , J. Wang , K. Wang ,R. Wang , S.M. Wang , T. Wang , T. Wang , W. Wang , X. Wang , C. Wanotayaroj ,A. Warburton , C.P. Ward , D.R. Wardrope , A. Washbrook , P.M. Watkins , A.T. Watson ,M.F. Watson , G. Watts , S. Watts , B.M. Waugh , S. Webb , M.S. Weber , S.W. Weber ,J.S. Webster , A.R. Weidberg , B. Weinert , J. Weingarten , C. Weiser , H. Weits , P.S. Wells ,T. Wenaus , T. Wengler , S. Wenig , N. Wermes , M. Werner , M.D. Werner , P. Werner ,M. Wessels , J. Wetter , K. Whalen , N.L. Whallon , A.M. Wharton , A. White , M.J. White ,R. White , D. Whiteson , F.J. Wickens , W. Wiedenmann , M. Wielers , P. Wienemann ,C. Wiglesworth , L.A.M. Wiik-Fuchs , A. Wildauer , F. Wilk , H.G. Wilkens , H.H. Williams ,S. Williams , C. Willis , S. Willocq , J.A. Wilson , I. Wingerter-Seez , F. Winklmeier ,O.J. Winston , B.T. Winter , M. Wittgen , J. Wittkowski , T.M.H. Wolf , M.W. Wolter ,H. Wolters , S.D. Worm , B.K. Wosiek , J. Wotschack , M.J. Woudstra , K.W. Wozniak ,M. Wu , M. Wu , S.L. Wu , X. Wu , Y. Wu , T.R. Wyatt , B.M. Wynne , S. Xella , D. Xu ,L. Xu , B. Yabsley , S. Yacoob , R. Yakabe , D. Yamaguchi , Y. Yamaguchi ,A. Yamamoto , S. Yamamoto , T. Yamanaka , K. Yamauchi , Y. Yamazaki , Z. Yan ,H. Yang , H. Yang , Y. Yang , Z. Yang , W-M. Yao , Y.C. Yap , Y. Yasu , E. Yatsenko ,K.H. Yau Wong , J. Ye , S. Ye , I. Yeletskikh , A.L. Yen , E. Yildirim , K. Yorita , R. Yoshida ,K. Yoshihara , C. Young , C.J.S. Young , S. Youssef , D.R. Yu , J. Yu , J.M. Yu , J. Yu ,L. Yuan , S.P.Y. Yuen , I. Yusu ff , ar , B. Zabinski , R. Zaidan , A.M. Zaitsev , ae ,N. Zakharchuk , J. Zalieckas , A. Zaman , S. Zambito , L. Zanello , D. Zanzi ,C. Zeitnitz , M. Zeman , A. Zemla , J.C. Zeng , Q. Zeng , K. Zengel , O. Zenin ,T. Ženiš , D. Zerwas , D. Zhang , F. Zhang , G. Zhang , am , H. Zhang , J. Zhang ,L. Zhang , R. Zhang , R. Zhang , as , X. Zhang , Z. Zhang , X. Zhao , Y. Zhao , Z. Zhao ,A. Zhemchugov , J. Zhong , B. Zhou , C. Zhou , L. Zhou , L. Zhou , M. Zhou , N. Zhou ,C.G. Zhu , H. Zhu , J. Zhu , Y. Zhu , X. Zhuang , K. Zhukov , A. Zibell , D. Zieminska ,N.I. Zimine , C. Zimmermann , S. Zimmermann , Z. Zinonos , M. Zinser , M. Ziolkowski ,L. Živkovi´c , G. Zobernig , A. Zoccoli , M. zur Nedden , L. Zwalinski . Department of Physics, University of Adelaide, Adelaide, Australia Physics Department, SUNY Albany, Albany NY, United States of America Department of Physics, University of Alberta, Edmonton AB, Canada52 ( a ) Department of Physics, Ankara University, Ankara; ( b ) Istanbul Aydin University, Istanbul; ( c ) Division of Physics, TOBB University of Economics and Technology, Ankara, Turkey LAPP, CNRS / IN2P3 and Université Savoie Mont Blanc, Annecy-le-Vieux, France High Energy Physics Division, Argonne National Laboratory, Argonne IL, United States of America Department of Physics, University of Arizona, Tucson AZ, United States of America Department of Physics, The University of Texas at Arlington, Arlington TX, United States of America Physics Department, University of Athens, Athens, Greece Physics Department, National Technical University of Athens, Zografou, Greece Department of Physics, The University of Texas at Austin, Austin TX, United States of America Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology,Barcelona, Spain, Spain Institute of Physics, University of Belgrade, Belgrade, Serbia Department for Physics and Technology, University of Bergen, Bergen, Norway Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA,United States of America Department of Physics, Humboldt University, Berlin, Germany Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics, Universityof Bern, Bern, Switzerland School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom
20 ( a ) Department of Physics, Bogazici University, Istanbul; ( b ) Department of Physics Engineering,Gaziantep University, Gaziantep; ( d ) Istanbul Bilgi University, Faculty of Engineering and NaturalSciences, Istanbul,Turkey; ( e ) Bahcesehir University, Faculty of Engineering and Natural Sciences,Istanbul, Turkey, Turkey Centro de Investigaciones, Universidad Antonio Narino, Bogota, Colombia
22 ( a ) INFN Sezione di Bologna; ( b ) Dipartimento di Fisica e Astronomia, Università di Bologna,Bologna, Italy Physikalisches Institut, University of Bonn, Bonn, Germany Department of Physics, Boston University, Boston MA, United States of America Department of Physics, Brandeis University, Waltham MA, United States of America
26 ( a ) Universidade Federal do Rio De Janeiro COPPE / EE / IF, Rio de Janeiro; ( b ) Electrical CircuitsDepartment, Federal University of Juiz de Fora (UFJF), Juiz de Fora; ( c ) Federal University of Sao Joaodel Rei (UFSJ), Sao Joao del Rei; ( d ) Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil Physics Department, Brookhaven National Laboratory, Upton NY, United States of America
28 ( a ) Transilvania University of Brasov, Brasov, Romania; ( b ) National Institute of Physics and NuclearEngineering, Bucharest; ( c ) National Institute for Research and Development of Isotopic and MolecularTechnologies, Physics Department, Cluj Napoca; ( d ) University Politehnica Bucharest, Bucharest; ( e ) West University in Timisoara, Timisoara, Romania Departamento de Física, Universidad de Buenos Aires, Buenos Aires, Argentina Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom Department of Physics, Carleton University, Ottawa ON, Canada CERN, Geneva, Switzerland Enrico Fermi Institute, University of Chicago, Chicago IL, United States of America
34 ( a ) Departamento de Física, Pontificia Universidad Católica de Chile, Santiago; ( b ) Departamento deFísica, Universidad Técnica Federico Santa María, Valparaíso, Chile
35 ( a ) Institute of High Energy Physics, Chinese Academy of Sciences, Beijing; ( b ) Department ofModern Physics, University of Science and Technology of China, Anhui; ( c ) Department of Physics,53anjing University, Jiangsu; ( d ) School of Physics, Shandong University, Shandong; ( e ) Department ofPhysics and Astronomy, Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai JiaoTong University, Shanghai; (also a ffi liated with PKU-CHEP); ( f ) Physics Department, TsinghuaUniversity, Beijing 100084, China Laboratoire de Physique Corpusculaire, Clermont Université and Université Blaise Pascal andCNRS / IN2P3, Clermont-Ferrand, France Nevis Laboratory, Columbia University, Irvington NY, United States of America Niels Bohr Institute, University of Copenhagen, Kobenhavn, Denmark
39 ( a ) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; ( b ) Dipartimento di Fisica,Università della Calabria, Rende, Italy
40 ( a ) AGH University of Science and Technology, Faculty of Physics and Applied Computer Science,Krakow; ( b ) Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland Institute of Nuclear Physics Polish Academy of Sciences, Krakow, Poland Physics Department, Southern Methodist University, Dallas TX, United States of America Physics Department, University of Texas at Dallas, Richardson TX, United States of America DESY, Hamburg and Zeuthen, Germany Institut für Experimentelle Physik IV, Technische Universität Dortmund, Dortmund, Germany Institut für Kern- und Teilchenphysik, Technische Universität Dresden, Dresden, Germany Department of Physics, Duke University, Durham NC, United States of America SUPA - School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom INFN Laboratori Nazionali di Frascati, Frascati, Italy Fakultät für Mathematik und Physik, Albert-Ludwigs-Universität, Freiburg, Germany Section de Physique, Université de Genève, Geneva, Switzerland
52 ( a ) INFN Sezione di Genova; ( b ) Dipartimento di Fisica, Università di Genova, Genova, Italy
53 ( a ) E. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; ( b ) HighEnergy Physics Institute, Tbilisi State University, Tbilisi, Georgia II Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany SUPA - School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS / IN2P3,Grenoble, France Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States ofAmerica
59 ( a ) Kirchho ff -Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; ( b ) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg; ( c ) ZITI Institut fürtechnische Informatik, Ruprecht-Karls-Universität Heidelberg, Mannheim, Germany Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan
61 ( a ) Department of Physics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; ( b ) Department of Physics, The University of Hong Kong, Hong Kong; ( c ) Department of Physics, TheHong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China Department of Physics, Indiana University, Bloomington IN, United States of America Institut für Astro- und Teilchenphysik, Leopold-Franzens-Universität, Innsbruck, Austria University of Iowa, Iowa City IA, United States of America Department of Physics and Astronomy, Iowa State University, Ames IA, United States of America Joint Institute for Nuclear Research, JINR Dubna, Dubna, Russia KEK, High Energy Accelerator Research Organization, Tsukuba, Japan Graduate School of Science, Kobe University, Kobe, Japan54 Faculty of Science, Kyoto University, Kyoto, Japan Kyoto University of Education, Kyoto, Japan Department of Physics, Kyushu University, Fukuoka, Japan Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET, La Plata, Argentina Physics Department, Lancaster University, Lancaster, United Kingdom
74 ( a ) INFN Sezione di Lecce; ( b ) Dipartimento di Matematica e Fisica, Università del Salento, Lecce,Italy Oliver Lodge Laboratory, University of Liverpool, Liverpool, United Kingdom Department of Physics, Jožef Stefan Institute and University of Ljubljana, Ljubljana, Slovenia School of Physics and Astronomy, Queen Mary University of London, London, United Kingdom Department of Physics, Royal Holloway University of London, Surrey, United Kingdom Department of Physics and Astronomy, University College London, London, United Kingdom Louisiana Tech University, Ruston LA, United States of America Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université Paris-Diderot andCNRS / IN2P3, Paris, France Fysiska institutionen, Lunds universitet, Lund, Sweden Departamento de Fisica Teorica C-15, Universidad Autonoma de Madrid, Madrid, Spain Institut für Physik, Universität Mainz, Mainz, Germany School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom CPPM, Aix-Marseille Université and CNRS / IN2P3, Marseille, France Department of Physics, University of Massachusetts, Amherst MA, United States of America Department of Physics, McGill University, Montreal QC, Canada School of Physics, University of Melbourne, Victoria, Australia Department of Physics, The University of Michigan, Ann Arbor MI, United States of America Department of Physics and Astronomy, Michigan State University, East Lansing MI, United States ofAmerica
92 ( a ) INFN Sezione di Milano; ( b ) Dipartimento di Fisica, Università di Milano, Milano, Italy B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic ofBelarus National Scientific and Educational Centre for Particle and High Energy Physics, Minsk, Republic ofBelarus Group of Particle Physics, University of Montreal, Montreal QC, Canada P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia National Research Nuclear University MEPhI, Moscow, Russia D.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow,Russia
Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany
Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany
Nagasaki Institute of Applied Science, Nagasaki, Japan
Graduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan
104 ( a ) INFN Sezione di Napoli; ( b ) Dipartimento di Fisica, Università di Napoli, Napoli, Italy
Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United Statesof America
Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen / Nikhef,Nijmegen, Netherlands
Nikhef National Institute for Subatomic Physics and University of Amsterdam, Amsterdam,55etherlands
Department of Physics, Northern Illinois University, DeKalb IL, United States of America
Budker Institute of Nuclear Physics, SB RAS, Novosibirsk, Russia
Department of Physics, New York University, New York NY, United States of America
Ohio State University, Columbus OH, United States of America
Faculty of Science, Okayama University, Okayama, Japan
Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman OK,United States of America
Department of Physics, Oklahoma State University, Stillwater OK, United States of America
Palacký University, RCPTM, Olomouc, Czech Republic
Center for High Energy Physics, University of Oregon, Eugene OR, United States of America
LAL, Univ. Paris-Sud, CNRS / IN2P3, Université Paris-Saclay, Orsay, France
Graduate School of Science, Osaka University, Osaka, Japan
Department of Physics, University of Oslo, Oslo, Norway
Department of Physics, Oxford University, Oxford, United Kingdom
121 ( a ) INFN Sezione di Pavia; ( b ) Dipartimento di Fisica, Università di Pavia, Pavia, Italy
Department of Physics, University of Pennsylvania, Philadelphia PA, United States of America
National Research Centre "Kurchatov Institute" B.P.Konstantinov Petersburg Nuclear PhysicsInstitute, St. Petersburg, Russia
124 ( a ) INFN Sezione di Pisa; ( b ) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States ofAmerica
126 ( a ) Laboratório de Instrumentação e Física Experimental de Partículas - LIP, Lisboa; ( b ) Faculdade deCiências, Universidade de Lisboa, Lisboa; ( c ) Department of Physics, University of Coimbra, Coimbra; ( d ) Centro de Física Nuclear da Universidade de Lisboa, Lisboa; ( e ) Departamento de Fisica,Universidade do Minho, Braga; ( f ) Departamento de Fisica Teorica y del Cosmos and CAFPE,Universidad de Granada, Granada (Spain); ( g ) Dep Fisica and CEFITEC of Faculdade de Ciencias eTecnologia, Universidade Nova de Lisboa, Caparica, Portugal
Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic
Czech Technical University in Prague, Praha, Czech Republic
Faculty of Mathematics and Physics, Charles University in Prague, Praha, Czech Republic
State Research Center Institute for High Energy Physics (Protvino), NRC KI, Russia
Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom
132 ( a ) INFN Sezione di Roma; ( b ) Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy
133 ( a ) INFN Sezione di Roma Tor Vergata; ( b ) Dipartimento di Fisica, Università di Roma Tor Vergata,Roma, Italy
134 ( a ) INFN Sezione di Roma Tre; ( b ) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma,Italy
135 ( a ) Faculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies -Université Hassan II, Casablanca; ( b ) Centre National de l’Energie des Sciences Techniques Nucleaires,Rabat; ( c ) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech; ( d ) Faculté desSciences, Université Mohamed Premier and LPTPM, Oujda; ( e ) Faculté des sciences, UniversitéMohammed V, Rabat, Morocco
DSM / IRFU (Institut de Recherches sur les Lois Fondamentales de l’Univers), CEA Saclay(Commissariat à l’Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France
Santa Cruz Institute for Particle Physics, University of California Santa Cruz, Santa Cruz CA, UnitedStates of America 56 Department of Physics, University of Washington, Seattle WA, United States of America
Department of Physics and Astronomy, University of She ffi eld, She ffi eld, United Kingdom Department of Physics, Shinshu University, Nagano, Japan
Fachbereich Physik, Universität Siegen, Siegen, Germany
Department of Physics, Simon Fraser University, Burnaby BC, Canada
SLAC National Accelerator Laboratory, Stanford CA, United States of America
144 ( a ) Faculty of Mathematics, Physics & Informatics, Comenius University, Bratislava; ( b ) Departmentof Subnuclear Physics, Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice,Slovak Republic
145 ( a ) Department of Physics, University of Cape Town, Cape Town; ( b ) Department of Physics,University of Johannesburg, Johannesburg; ( c ) School of Physics, University of the Witwatersrand,Johannesburg, South Africa
146 ( a ) Department of Physics, Stockholm University; ( b ) The Oskar Klein Centre, Stockholm, Sweden
Physics Department, Royal Institute of Technology, Stockholm, Sweden
Departments of Physics & Astronomy and Chemistry, Stony Brook University, Stony Brook NY,United States of America
Department of Physics and Astronomy, University of Sussex, Brighton, United Kingdom
School of Physics, University of Sydney, Sydney, Australia
Institute of Physics, Academia Sinica, Taipei, Taiwan
Department of Physics, Technion: Israel Institute of Technology, Haifa, Israel
Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv,Israel
Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
International Center for Elementary Particle Physics and Department of Physics, The University ofTokyo, Tokyo, Japan
Graduate School of Science and Technology, Tokyo Metropolitan University, Tokyo, Japan
Department of Physics, Tokyo Institute of Technology, Tokyo, Japan
Department of Physics, University of Toronto, Toronto ON, Canada
159 ( a ) TRIUMF, Vancouver BC; ( b ) Department of Physics and Astronomy, York University, TorontoON, Canada
Faculty of Pure and Applied Sciences, and Center for Integrated Research in Fundamental Scienceand Engineering, University of Tsukuba, Tsukuba, Japan
Department of Physics and Astronomy, Tufts University, Medford MA, United States of America
Department of Physics and Astronomy, University of California Irvine, Irvine CA, United States ofAmerica
163 ( a ) INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; ( b ) ICTP, Trieste; ( c ) Dipartimento diChimica, Fisica e Ambiente, Università di Udine, Udine, Italy
Department of Physics and Astronomy, University of Uppsala, Uppsala, Sweden
Department of Physics, University of Illinois, Urbana IL, United States of America
Instituto de Fisica Corpuscular (IFIC) and Departamento de Fisica Atomica, Molecular y Nuclearand Departamento de Ingeniería Electrónica and Instituto de Microelectrónica de Barcelona(IMB-CNM), University of Valencia and CSIC, Valencia, Spain
Department of Physics, University of British Columbia, Vancouver BC, Canada
Department of Physics and Astronomy, University of Victoria, Victoria BC, Canada
Department of Physics, University of Warwick, Coventry, United Kingdom
Waseda University, Tokyo, Japan
Department of Particle Physics, The Weizmann Institute of Science, Rehovot, Israel57 Department of Physics, University of Wisconsin, Madison WI, United States of America
Fakultät für Physik und Astronomie, Julius-Maximilians-Universität, Würzburg, Germany
Fakultät für Mathematik und Naturwissenschaften, Fachgruppe Physik, Bergische UniversitätWuppertal, Wuppertal, Germany
Department of Physics, Yale University, New Haven CT, United States of America
Yerevan Physics Institute, Yerevan, Armenia
Centre de Calcul de l’Institut National de Physique Nucléaire et de Physique des Particules (IN2P3),Villeurbanne, France a Also at Department of Physics, King’s College London, London, United Kingdom b Also at Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan c Also at Novosibirsk State University, Novosibirsk, Russia d Also at TRIUMF, Vancouver BC, Canada e Also at Department of Physics & Astronomy, University of Louisville, Louisville, KY, United States ofAmerica f Also at Department of Physics, California State University, Fresno CA, United States of America g Also at Department of Physics, University of Fribourg, Fribourg, Switzerland h Also at Departament de Fisica de la Universitat Autonoma de Barcelona, Barcelona, Spain i Also at Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Portugal j Also at Tomsk State University, Tomsk, Russia k Also at Universita di Napoli Parthenope, Napoli, Italy l Also at Institute of Particle Physics (IPP), Canada m Also at National Institute of Physics and Nuclear Engineering, Bucharest, Romania n Also at Department of Physics, St. Petersburg State Polytechnical University, St. Petersburg, Russia o Also at Department of Physics, The University of Michigan, Ann Arbor MI, United States of America p Also at Centre for High Performance Computing, CSIR Campus, Rosebank, Cape Town, South Africa q Also at Louisiana Tech University, Ruston LA, United States of America r Also at Institucio Catalana de Recerca i Estudis Avancats, ICREA, Barcelona, Spain s Also at Graduate School of Science, Osaka University, Osaka, Japan t Also at Department of Physics, National Tsing Hua University, Taiwan u Also at Institute for Mathematics, Astrophysics and Particle Physics, Radboud UniversityNijmegen / Nikhef, Nijmegen, Netherlands v Also at Department of Physics, The University of Texas at Austin, Austin TX, United States of America w Also at Institute of Theoretical Physics, Ilia State University, Tbilisi, Georgia x Also at CERN, Geneva, Switzerland y Also at Georgian Technical University (GTU),Tbilisi, Georgia z Also at Ochadai Academic Production, Ochanomizu University, Tokyo, Japan aa Also at Manhattan College, New York NY, United States of America ab Also at Hellenic Open University, Patras, Greece ac Also at Academia Sinica Grid Computing, Institute of Physics, Academia Sinica, Taipei, Taiwan ad Also at School of Physics, Shandong University, Shandong, China ae Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia a f
Also at Section de Physique, Université de Genève, Geneva, Switzerland a g Also at Eotvos Lorand University, Budapest, Hungary ah Also at International School for Advanced Studies (SISSA), Trieste, Italy ai Also at Department of Physics and Astronomy, University of South Carolina, Columbia SC, UnitedStates of America a j
Also at School of Physics and Engineering, Sun Yat-sen University, Guangzhou, China58 k Also at Institute for Nuclear Research and Nuclear Energy (INRNE) of the Bulgarian Academy ofSciences, Sofia, Bulgaria al Also at Faculty of Physics, M.V.Lomonosov Moscow State University, Moscow, Russia am Also at Institute of Physics, Academia Sinica, Taipei, Taiwan an Also at National Research Nuclear University MEPhI, Moscow, Russia ao Also at Department of Physics, Stanford University, Stanford CA, United States of America ap Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest,Hungary aq Also at Flensburg University of Applied Sciences, Flensburg, Germany ar Also at University of Malaya, Department of Physics, Kuala Lumpur, Malaysia as Also at CPPM, Aix-Marseille Université and CNRS / IN2P3, Marseille, France ∗∗