DOI 10.1140/epjc/s10052-012-2043-9 Regular Article - Experimental Physics
Measurement of t
¯t production with a veto on additional central jet
activity in pp collisions at
√
s
= 7 TeV using the ATLAS detector
The ATLAS Collaboration
CERN, 1211 Geneva 23, Switzerland
Received: 22 March 2012 / Revised: 23 May 2012 / Published online: 21 June 2012
© CERN for the benefit of the ATLAS collaboration 2012. This article is published with open access at Springerlink.com
Abstract A measurement of the jet activity in t¯t events pro-duced in proton–proton collisions at a centre-of-mass energy of 7 TeV is presented, using 2.05 fb−1of integrated lumi-nosity collected by the ATLAS detector at the Large Hadron Collider. The t¯t events are selected in the dilepton decay channel with two identified b-jets from the top quark de-cays. Events are vetoed if they contain an additional jet with transverse momentum above a threshold in a central rapid-ity interval. The fraction of events surviving the jet veto is presented as a function of this threshold for four different central rapidity interval definitions. An alternate measure-ment is also performed, in which events are vetoed if the scalar transverse momentum sum of the additional jets in each rapidity interval is above a threshold. In both measure-ments, the data are corrected for detector effects and com-pared to the theoretical models implemented in MC@NLO, POWHEG, ALPGENand SHERPA. The experimental uncer-tainties are often smaller than the spread of theoretical pre-dictions, allowing deviations between data and theory to be observed in some regions of phase space.
1 Introduction
Measurements of the top quark provide an important test of the Standard Model (SM) and any observed deviation from the SM predictions could indicate the presence of new physics. However, many top quark measurements have large uncertainties that arise from the theoretical description of quark and gluon radiation in the standard Monte Carlo (MC) event generators. Recent measurements that are affected by such modelling uncertainties include the t¯t production cross-section [1–4], the spin correlations in t¯t events [5], the charge asymmetry [6,7] and the top quark mass [4]. In ad-dition, a significant disagreement between data and the pre-diction from MC@NLO [8,9] was observed by the D0 Col-laboration in the transverse momentum distribution of the
e-mail:atlas.publications@cern.ch
t¯t system [10]. This disagreement obscures the interpreta-tion of the observed forward-backward asymmetry in terms of a deviation from SM predictions. Measurements sensitive to the theoretical description of quark and gluon radiation in events containing a t¯t final state are therefore needed in order to constrain the modelling and reduce the impact on future experimental measurements.
In this article, a jet veto is used to quantify the jet activ-ity that arises from quark and gluon radiation produced in association with the t¯t system. The events are selected in the dilepton decay channel so that the additional jets can be easily distinguished from the t¯t decay products (two leptons and two jets originating from b-quarks). The variable of in-terest is the ‘gap fraction’, defined as
f (Q0)=
n(Q0)
N , (1)
where N is the number of selected t¯t events and n(Q0)is
the subset of these events that do not contain an additional jet with transverse momentum, pT, above a threshold, Q0,
in a central rapidity1interval. The minimum jet pT used in
the measurement is 25 GeV. The measurement is corrected for detector effects and presented in a fiducial region. The gap fraction can then be written as
f (Q0)=
σ (Q0)
σ , (2)
where σ is the fiducial cross section for inclusive t¯t pro-duction and σ (Q0)is the fiducial cross section for t¯t events
produced in the absence of an additional jet with pT> Q0in
1ATLAS uses a right-handed coordinate system with the z-axis along
the beam line. Cylindrical coordinates (r, φ) are used in the trans-verse plane, φ being the azimuthal angle. Pseudorapidity is defined in terms of the polar angle θ as η= − ln[tan(θ/2)]. Rapidity is defined as
y= 0.5 ln[(E + pz)/(E− pz)] where E denotes the energy and pzis the component of the momentum along the beam direction. Transverse momentum and energy are defined as pT= p sin θ and ET= E sin θ,
the rapidity interval. The gap fraction is measured for multi-ple values of Q0and for four jet rapidity intervals:|y| < 0.8,
0.8≤ |y| < 1.5, 1.5 ≤ |y| < 2.1 and |y| < 2.1.
The veto criterion can be extended to probe jet activity beyond the leading additional jet. An alternate definition of the gap fraction is used in this case,
f (Qsum)=
n(Qsum)
N ≡
σ (Qsum)
σ , (3)
where n(Qsum)is the number of t¯t events, and σ (Qsum)is
the cross section, in which the scalar transverse momentum sum of the additional jets in the rapidity interval is less than Qsum. The gap fraction defined using Q0is mainly
sensi-tive to the leading-pTemission accompanying the t¯t system,
whereas the gap fraction defined using Qsumis sensitive to
all hard emissions accompanying the t¯t system.
Many of the experimental systematic uncertainties can-cel in the ratio, as observed in the ATLAS measurement of the gap fraction in dijet events [11]. The data are therefore expected to constrain the modelling of quark and gluon ra-diation in t¯t events and provide useful information about the general theoretical description of jet vetoes, which have been proposed as a tool to enhance new physics signals [12– 14], and to study the properties of new fundamental parti-cles [15–17].
2 ATLAS detector
The ATLAS detector [18] surrounds one of the proton– proton interaction points at the Large Hadron Collider. The inner tracking detector is composed of silicon pixel detec-tors, silicon microstrip detectors and a transition radiation tracking detector. The inner detector is surrounded by a su-perconducting solenoid that provides a 2 T magnetic field. This allows the momentum of charged particles that pass through the inner detector to be determined for |η| < 2.5. Outside the solenoid are liquid-argon electromagnetic sam-pling calorimeters (|η| < 3.2). Hadronic energy measure-ments are provided by a scintillator tile calorimeter in the central region (|η| < 1.7) and by liquid-argon calorimetry up to|η| < 4.9. The muon spectrometer system surrounds the calorimeter system and incorporates a toroidal mag-net system, with a field of approximately 0.5 and 1 T in the barrel and endcap regions respectively. The muon spec-trometer provides precision measurements of the momen-tum of muons up to|η| < 2.7, while the corresponding trig-ger chambers are limited to|η| < 2.4.
The data are collected using a three-level trigger system. The first level is implemented in hardware and reduces the data rate to less than 75 kHz. The following two software trigger levels reduce the rate to several hundred Hz. The data
passing the trigger selections are recorded for use in subse-quent analyses.
The measurements presented in this paper use data from proton–proton collisions at a centre-of-mass energy√s= 7 TeV, and rely on triggers designed to select events that contain high transverse momentum electrons or muons. The integrated luminosity of the data sample is 2.05± 0.08 fb−1 [19,20].
3 Theoretical predictions
The theoretical predictions for t¯t production are produced using the MC@NLO [8,9], POWHEG [21,22], ALPGEN
[23], SHERPA[24] and ACERMC [25,26] event generators. MC@NLO provides a calculation of t¯t production at next-to-leading order (NLO) accuracy and is interfaced to HERWIG[27] and JIMMY[28] for parton showering, hadro-nisation and underlying event from multiple partonic inter-actions. The parton distribution functions (PDF) chosen to generate the MC@NLO events are CTEQ6.6 [29] and the underlying event tune for HERWIG/JIMMYis chosen to be AUET1 [30]. POWHEG also produces the t¯t final state to NLO accuracy using the CTEQ6.6 PDF. The parton show-ering, hadronisation and underlying event are added by in-terfacing to either PYTHIA[31], with underlying event tune AMBT1 [32], or to HERWIG/JIMMY, with underlying event tune AUET1.
ALPGEN provides leading order (LO) matrix elements for t¯t production with up to three additional partons in the final state. The ALPGENevents are generated using the CTEQ6L1 PDF [29] and interfaced to HERWIG/JIMMYfor parton showering, hadronisation and underlying event (tune AUET1). The MLM matching procedure [33] is used to re-move double counting between partons produced by the ma-trix element and parton shower. SHERPAis also used to gen-erate t¯t events with up to three additional partons in the final state. This provides an independent LO matrix-element cal-culation with a different matching scheme (CKKW [34]) be-tween the matrix element and the parton shower. The events are generated with the default underlying event tune and the CTEQ6L1 PDF.
ACERMC consists of a LO matrix element for t¯t produc-tion and is interfaced to PYTHIA to provide the hadronic final state, using the MRST2007LO∗ PDF [35] and un-derlying event tune AMBT1. Three samples are produced with nominal, increased and decreased initial state radia-tion (ISR).2These samples have been previously used to as-sess ISR-based modelling uncertainties in ATLAS top quark measurements [1–3,5,6].
2The default ISR parameters in AMBT1 are PARP(67) = 4.0 and
PARP(64)= 1.0. To decrease ISR, the parameters are set to 0.5 and 4.0, respectively. To increase ISR, they are set to 6.0 and 0.25, respec-tively.
4 Simulation samples
In order to simulate the events observed in the detector, several MC samples are passed through the GEANT4 [36] simulation of the ATLAS detector [37] and are processed with the same reconstruction chain as used for the data. The MC@NLO and POWHEGsamples described in Sect.3are used to simulate the t¯t events. The background contribu-tion from single top, Z+jets and diboson produccontribu-tion is es-timated using MC@NLO [38], ALPGENand HERWIG, re-spectively. The hadronic final state for each of these back-grounds is generated using HERWIG/JIMMYwith underly-ing event tune AUET1. The MC samples are overlaid with additional minimum bias events generated with PYTHIAto simulate the effect of additional proton–proton interactions. The simulated events are re-weighted such that the average number of interactions per proton–proton bunch crossing, μ, is the same in data and MC simulation. This average varies between data-taking periods and is typically in the range 4 <μ < 8.
Corrections are applied to the simulation to reflect the ob-served performance in the data. The electron reconstruction efficiency, energy scale and energy resolution are corrected to match the observed distributions in W→ eν and Z → ee events [39]. The muon reconstruction efficiency, momentum scale and momentum resolution are corrected to match the observation in Z→ μμ events. The jet energy resolution is found to be larger in the data than predicted by the sim-ulation and additional smearing is applied to the simulated jets to ensure the resolution matches that in the data. The efficiency and rejection rate of the algorithm used to iden-tify jets that have originated from b-quarks is measured in the data and the simulation is corrected on a per-jet basis to match the observed performance. All these corrections have associated systematic uncertainties and the effect of these on the measurement of the gap fraction is discussed in Sect.7.
5 Event selection
The selection of t¯t events closely follows the selection used in the recent measurement of the t¯t production cross sec-tion [3]. Electrons are required to have transverse energy ET>25 GeV and|η| < 2.47, whereas muons are required
to have pT>20 GeV and|η| < 2.5. Electrons in the
tran-sition region between the barrel and endcap calorimeters (1.37 <|η| < 1.52) are excluded.
Jets are reconstructed using the anti-kt algorithm [40,
41], with a radius parameter R= 0.4, using clusters of adja-cent calorimeter cells calibrated at the electromagnetic (EM) energy scale. These jets are corrected for the calorimeter re-sponse and other detector effects using energy and pseudora-pidity dependent calibration factors derived from simulation
and validated using data [42]. The calibrated jets, j , used in the analysis are required to have pT>25 GeV,|y| < 2.4
and are required to be well separated from the selected lep-tons (electrons or muons) by
ΔR(j, )=Δφ (j, )2+Δη(j, )2>0.4. (4) Jets originating from b-quarks (b-jets) are identified using the IP3D+SV1 algorithm [43] and are referred to as b-tagged jets. This algorithm, based on impact parameter and secondary vertex information, has an average per-jet effi-ciency of 70 % for jets originating from b-quarks in sim-ulated t¯t events and rejects approximately 99 % of jets orig-inating from light quarks and gluons.
The scalar sum of visible transverse momentum, HT, is
calculated using the transverse momenta of all the recon-structed jets and leptons that satisfy the selection criteria defined above. The missing transverse momentum, ETmiss, is reconstructed from EM-scale clusters corrected according to the energy scale of associated jets/electrons and the mea-sured muon momenta.
To create a highly enriched t¯t sample, events are required to have two opposite sign high-pTleptons and at least two
b-tagged jets. The analysis is then divided into the three dilep-ton decay channels, ee, eμ and μμ, and additional channel-dependent selection criteria are applied to reduce back-grounds further. The background in the ee and μμ channels arising from Z→ ee/μμ events is suppressed by requiring EmissT >40 GeV and that the dilepton mass, m, is not in the range of the Z-boson mass, i.e.|m− 91 GeV| > 10 GeV. In addition, events are required to have m>15 GeV in order to reject backgrounds from vector-meson decays. The backgrounds in the eμ channel from Z→ ττ and diboson events are suppressed by requiring HT to be greater than
130 GeV. A summary of the event selection criteria is pre-sented in Table1.
The number of selected events in the three channels is 242 (ee), 436 (μμ) and 1095 (eμ). The dominant back-ground contributions after the selection requirements are single top (Wt) production and events in which at least one lepton originates from heavy flavour decay or jet misidenti-fication. The latter contribution consists of mainly W+jets and multijet events and is estimated from the data using a method described in reference [3]. The W t background is estimated using the MC sample discussed in Sect. 4. The total background contamination is estimated to be less than 6 %, which is smaller than the uncertainty on the the-oretical calculation of the t¯t cross section [44–46]. The ex-pected background contributions are not subtracted from the data, but are considered as a source of systematic uncertainty on the measurement. Figure1shows the distribution of the lepton and b-tagged jet pTfor the selected data events
com-pared with the prediction from the MC@NLO t¯t simula-tion. Good agreement is seen in all such distributions.
Table 1 Selection requirements applied to the three analysis channels
Selection Channel
ee μμ eμ
Electrons 2 with ET>25 GeV,
|η| < 2.47 – 1 with E|η| < 2.47T>25 GeV,
Muons – 2 with pT>20 GeV,
|η| < 2.5 1 with pT
>20 GeV,
|η| < 2.5
EmissT >40 GeV >40 GeV –
HT – – >130 GeV m >15 GeV, |m− 91 GeV| > 10 GeV >15 GeV, |m− 91 GeV| > 10 GeV –
b-tagged jets At least 2 with pT>25 GeV,|y| < 2.4, ΔR(j, ) > 0.4
Fig. 1 The distribution of (a) lepton pTand (b) b-tagged jet pTfor the
selected events compared to the MC@NLO simulation of t¯t events. The data is shown as closed (black) circles with the statistical
un-certainty. The MC@NLO prediction is normalised to the data and is shown as a solid (red) line. The overflow events at high pTare added
into the final bin of each histogram (Color figure online)
The gap fraction in each rapidity interval is computed us-ing the additional jets in the event. To suppress jets from overlapping proton–proton collisions, the additional jets are required to be fully contained within the inner detector ac-ceptance (|y| < 2.1) and the jet vertex fraction (JVF) al-gorithm is used to identify jets from the primary interac-tion. After associating tracks to jets (ΔR(jet, track) < 0.4), the JVF is defined as the scalar summed transverse mo-mentum of associated tracks from the primary vertex di-vided by the summed transverse momentum of associated tracks from all vertices. Each additional jet is required to satisfy JVF > 0.75. The transverse momentum and rapidity distributions for the highest-pTadditional jet in the region
|y| < 2.1 is shown in Fig.2. Reasonable agreement is seen between the data and the MC@NLO t¯t simulation.
6 Correction for detector effects
The data are corrected for detector effects to produce results at the particle level. The particle level t¯t events are defined in each channel using the same event selection criteria applied to the reconstructed data, as presented in Table1. Final state stable particles are defined as those that have a mean lifetime cτ >10 mm. Electrons are required to have ET>25 GeV
and|η| < 2.47, whereas muons are required to have pT>
20 GeV and|η| < 2.5.3Jets are reconstructed using the anti-ktalgorithm with R= 0.4, using all stable particles except
muons and neutrinos, and are required to have pT>25 GeV
and|y| < 2.4. Jets originating from b-quarks are defined as 3Changing the muon selection criteria to match the electron fiducial
region (pT>25 GeV and|η| < 2.47) was observed to have a negligible
Fig. 2 Distribution of (a) leading additional jet pTand (b) leading
ad-ditional jet rapidity in the selected events compared to the MC@NLO simulation of t¯t events. The data is shown as closed (black) circles with the statistical uncertainty. The MC@NLO prediction is normalised to the data and is shown as a solid (red) line. In the pTdistribution, the
overflow events at high pTare added into the final bin of the histogram.
In the rapidity distribution, variable bin sizes are used such that the bin edges match the rapidity intervals used to construct the gap fractions (Color figure online)
any jet that is within ΔR < 0.3 of a B-hadron, where the B-hadrons are required to have pT>5 GeV. HTis defined
as the scalar sum of jet and lepton transverse momenta and ETmissis defined using all final state neutrinos.
The correction factor, C, for the gap fraction at a specific value of x= Q0or Qsum, is defined as
C(x)=f
truth(x)
freco(x), (5)
where freco(x)is the reconstructed gap fraction and ftruth(x) is the particle level gap fraction. The use of simple correc-tion factors is justified because the purity of the selected events is greater than 70 % for each value of Q0 or Qsum.
The purity of the selected events is defined as the number of events that pass the event selection at both the recon-structed and particle level, divided by the number of events that pass the event selection at reconstructed level, using the MC@NLO simulation of t¯t events.
The MC@NLO simulation is also used to derive the baseline correction factors used in this measurement. These correction factors depend on the rapidity interval used to veto jet activity, with corrections of 2 %–5 % for Q0=
25 GeV that decrease with increasing Q0. The systematic
uncertainties on these correction factors due to physics and detector modelling are discussed in Sect.7.
7 Systematic uncertainties
Uncertainties related to the inclusive t¯t event selection were found to cancel in the gap fraction and are neglected in the
final systematic uncertainty. These include the uncertainties on the lepton momentum scale, momentum resolution and reconstruction efficiency, the b-jet energy scale, the trigger efficiency for each analysis channel and the integrated lu-minosity. The dominant sources of systematic uncertainty are those that directly affect the additional jets. These non-negligible sources of uncertainty are discussed in this sec-tion and a summary is presented in Fig.3.
The experimental aspects that affect the additional jets are the jet energy scale (JES), the jet energy resolution (JER), the jet reconstruction efficiency and the JVF selec-tion requirement. The uncertainty on the gap fracselec-tion due to the JES is estimated by rescaling the jet energies in the simu-lation by the known uncertainty [42]. The uncertainty on the JES includes the impact of soft energy added to jets from multiple proton–proton interactions. The uncertainty on the gap fraction due to jet reconstruction efficiency [42] and the jet energy resolution is estimated by varying each of these in the simulation within the allowed uncertainties determined from data. The relative uncertainty on the gap fraction due to the JES and JER uncertainties is 3.5 % or less if jets are vetoed in the full rapidity interval (|y| < 2.1), and 1.5 % or less if jets are vetoed in the smaller sub-intervals (e.g. |y| < 0.8). The uncertainty from the jet reconstruction ef-ficiency is found to be negligible compared to the JES and JER uncertainties for all four rapidity intervals.
The bias due to the JVF selection efficiency is estimated by performing the full analysis (selection plus correction for detector effects) with a relaxed requirement of JVF > 0.1. The relative difference between the results obtained with the
Fig. 3 Breakdown of the systematic uncertainties on the gap fraction as a function of Q0for (a)|y| < 0.8 and (b) |y| < 2.1. The step size
in Q0was chosen to be commensurate with the jet energy resolution.
The individual systematic uncertainties are shown as labelled lines of different styles and the total systematic uncertainty is shown as the outer solid line. The statistical uncertainty on the data is shown
as the shaded area. The breakdown of the systematic uncertainties above Q0= 200 GeV is consistent with the results at Q0= 200 GeV.
‘Pileup’ refers to the effect of jets produced in a different proton– proton interaction. ‘Unfolding’ refers to the procedure used to correct the measured gap fraction to particle level
standard and relaxed requirement is found to be up to 2 % at Q0= 25 GeV and is negligible above Q0of approximately
100 GeV. This difference is taken as the systematic uncer-tainty due to the JVF selection efficiency.
Jets produced by additional proton–proton interactions are suppressed by the JVF requirement. However, those jets that pass this requirement represent a potential bias in the measurement. The size of this bias is evaluated by removing those jets in the MC@NLO sample that are not matched to a particle level jet from the pp interaction that produces the t¯t event. The matching criterion is ΔR < 0.3 and the particle jet transverse momentum is allowed to be as low as 7 GeV, to avoid resolution effects in the matching procedure. The gap fraction is recalculated using this truth-matched sample and the difference to the nominal gap fraction is taken as the systematic uncertainty due to jets from additional proton– proton interactions. The relative uncertainty on the gap frac-tion is less than 1 % in each of the rapidity regions.
Background contamination is treated as a systematic un-certainty. For each background source, the expected events are subtracted from the data and the gap fraction is re-calculated. The relative difference with respect to the nomi-nal result is taken as the systematic uncertainty due to back-ground contamination; the largest effect is observed to be 0.5 % for Q0= 25 GeV.
The uncertainty on the efficiency and rejection capability of the b-tagging algorithm impacts upon the measurement if the additional jet is identified as a b-tagged jet instead of one of the b-jets originating from the top-quark decay. The sys-tematic uncertainty due to this effect is estimated by chang-ing the baseline efficiency and rejection corrections, which
are applied to the simulation, according to the b-tagging un-certainty (derived in calibration studies using inclusive lep-ton and multijet final states). The relative uncertainty on the gap fraction is less than 0.8 %.
The uncertainty on the procedure used to correct the data to particle level due to physics modelling is estimated by deriving alternative correction factors using the POWHEG
samples. The systematic uncertainty in the correction pro-cedure is taken to be the largest difference between the cor-rection factor obtained using the MC@NLO sample and the correction factor obtained using the two POWHEG sam-ples. In the case where this difference is smaller than the statistical uncertainty in the MC samples, the statistical un-certainty is taken as the estimate of the systematic uncer-tainty. The relative uncertainty on the correction factors is less than 2 % at Q0= 25 GeV for the region |y| < 2.1,
de-creasing to approximately 0.3 % at Q0= 150 GeV. The
sen-sitivity of the corrections to the physics modelling is further assessed by reweighting the additional jet pT spectrum in
the MC@NLO sample such that the pTdistribution has the
maximal change in shape that is consistent with the JES un-certainty bands. The difference in the correction factors was observed to be much smaller than the differences obtained by using different MC generators and is neglected in the fi-nal results.
Figure3shows the breakdown of the systematic uncer-tainties on the gap fraction as a function of Q0, for the veto
regions|y| < 0.8 and |y| < 2.1. This figure also shows the total systematic uncertainty, which is calculated by adding in quadrature all the individual systematic uncertainties. The
Fig. 4 The measured gap fraction as a function of Q0is compared
with the prediction from the NLO and multi-leg LO MC generators in the three rapidity regions, (a)|y| < 0.8, (b) 0.8 ≤ |y| < 1.5 and (c) 1.5≤ |y| < 2.1. Also shown, (d), is the gap fraction for the full ra-pidity range|y| < 2.1. The data is represented as closed (black) circles
with statistical uncertainties. The yellow band is the total experimental uncertainty on the data (statistical and systematic). The theoretical pre-dictions are shown as solid and dashed coloured lines. The gap fraction is shown until Q0= 300 GeV or until the gap fraction reaches one if
that occurs before Q0= 300 GeV (Color figure online)
total systematic uncertainty is largest at low Q0and is
domi-nated by the jet related uncertainties (JES, JER and JVF) and the uncertainty on the correction factors. The measurement is most precise in the central region, where the jet energy scale uncertainty is smallest. The breakdown of uncertain-ties for the gap fraction as a function of Qsumis similar, but
the uncertainties are slightly larger and fall more slowly as a function of Qsum. This is due to low transverse
momen-tum jets, which have the largest systematic uncertainties and therefore affect all values of Qsum.
8 Results and discussion
The gap fraction is measured for multiple values of Q0and
step size in Q0and Qsumwas chosen to be commensurate
with the jet energy resolution. The results are corrected to the particle level as described in Sect.6.
The measured gap fraction as a function of Q0 is
com-pared with the predictions from the multi-leg LO and NLO generators in Fig. 4. In general, all these generators are found to give a reasonable description of the data if the veto is applied to jets in the full rapidity interval,|y| < 2.1 (Fig. 4(d)). The difference between the MC@NLO and POWHEGpredictions is similar to the precision achieved in the measurement and as such the measurement is probing the different approaches to NLO plus parton-shower event generation.
In the most central rapidity interval, |y| < 0.8, the gap fraction predicted by MC@NLO is too large (Fig. 4(a)). The tendency of MC@NLO to produce fewer jets than ALPGEN at central rapidity has been discussed in the lit-erature [33] and the measurement presented here is sensitive to this difference. In the most forward rapidity interval, none of the predictions agrees with the data for all values of Q0
(Fig. 4(c)). In particular, although MC@NLO, POWHEG, ALPGENand SHERPAproduce similar predictions, the gap fraction is too small, implying that too much jet activity is produced by these event generators in the forward rapidity region.
The predictions from the ACERMC generator with the variations of the PYTHIA parton shower parameters are compared to the data in Fig.5 and are found to be in poor agreement with the data. The spread of the predicted gap
fraction due to the parameter variations is found to be much larger than the experimental uncertainty, indicating that the variations can be significantly reduced in light of the mea-surement presented in this article.
The measured gap fraction as a function of Qsumis
com-pared with the multi-leg LO and NLO generators in Fig.6. The gap fraction is lower than for the case of the Q0
vari-able, demonstrating that the measurement is probing quark and gluon radiation beyond the first emission. As expected, the largest change in the gap fraction occurs when jets are vetoed in the full rapidity interval,|y| < 2.1. However, the difference between the data and each theoretical prediction is found to be similar to the Q0case. This implies that, for
this variable, the parton shower approximations used for the subsequent emissions in MC@NLO and POWHEGare per-forming as well as the LO approximations used in ALPGEN
and SHERPA.
The gap fraction is a ratio of cross sections and all the events are used to evaluate this ratio at each value of Q0or
Qsum. This means that there is a statistical correlation
be-tween the measured gap fraction values in each rapidity in-terval. The correlation matrix is shown in Fig.7for the gap fraction at different values of Q0 for the|y| < 2.1 rapidity
region. Neighbouring Q0points have a significant
correla-tion, whereas well separated Q0points are less correlated.
The measured values of the gap fraction at Q0= 25,
75 and 150 GeV are presented in Table 2 for the differ-ent rapidity intervals used to veto jet activity. The statisti-cal correlations between these measurements and the
pre-Fig. 5 The measured gap fraction as a function of Q0for (a)|y| < 0.8
and (b)|y| < 2.1 is compared with the prediction from the ACERMC generator, where different settings of the PYTHIAparton shower
pa-rameters are used to produce samples with nominal, increased and de-creased initial state radiation (ISR). The data and theory predictions are represented in the same way as in Fig.4
Fig. 6 The measured gap fraction as a function of Qsumis compared
with the prediction from the NLO and multi-leg LO MC generators in the three rapidity regions, (a)|y| < 0.8, (b) 0.8 ≤ |y| < 1.5 and (c) 1.5≤ |y| < 2.1. Also shown, (d), is the gap fraction for the full
rapidity range|y| < 2.1. The data and theory predictions are repre-sented in the same way as in Fig.4. The gap fraction is shown until
Qsum= 420 GeV or until the gap fraction reaches one if that occurs
before Qsum= 420 GeV
dictions from the multi-leg LO and NLO generators are also given. The measured values of the gap fraction at Qsum=
55, 150 and 300 GeV are presented in Table3for the differ-ent rapidity intervals used to veto jet activity. The complete set of measurements presented in Figs.4–7have been com-piled in tables that can be obtained from HEPDATA.
The precision of the data, coupled with the large spread of theory predictions, implies that higher-order theory pre-dictions may be needed to describe the data in all regions
of phase space. For example, the NLO plus parton shower predictions provided by MC@NLO and POWHEGhave LO accuracy in the first parton emission and leading logarith-mic (LL) accuracy for subsequent emissions. Similarly, the ME plus parton shower predictions provided by SHERPA
and ALPGENare accurate to LO for the first three emissions and LL thereafter. Possible improvements on this accuracy include NLO calculations that account for the decay
prod-ucts of the top quarks [47,48] and calculations of t¯t + j(j) at NLO [49–54].
Fig. 7 The correlation matrix (statistical) for the gap fraction mea-surement at different values of Q0for|y| < 2.1
9 Conclusions
Precision measurements of the jet activity in t¯t events were performed using proton–proton collisions recorded by the ATLAS detector at the LHC. The t¯t events were selected in the dilepton decay channel with two identified b-jets. Events were subsequently vetoed if they contained an additional jet with transverse momentum above a threshold, Q0, in a
cen-tral rapidity interval. The fraction of t¯t events that survive the jet veto was presented as a function of Q0for four
dif-ferent central rapidity interval definitions. An alternate mea-surement was also performed, in which the t¯t events were vetoed if the scalar transverse momentum sum of the ad-ditional jets in each rapidity interval was above a defined threshold, Qsum.
The data were fully corrected for detector effects and compared to the predictions from state-of-the-art MC event generators. MC@NLO, POWHEG, ALPGEN and SHERPA
are observed to give a reasonable description of the data, when the additional jets are vetoed in the rapidity inter-val |y| < 2.1. However, all four generators predict too much jet activity in the most forward rapidity interval,
Table 2 The measured values of f (Q0)for Q0= 25, 75 and 150 GeV
for the different rapidity intervals used to veto jet activity are presented. The predictions from the NLO and multi-leg LO generators are also presented; the statistical uncertainty due to limited sample size is
shown if this uncertainty is larger than 0.1 %. In each rapidity interval, the statistical correlations (ρji) between measurements at Q0= i and
Q0= j are given
Q0[GeV] f (Q0)(%) ρji
Data± (stat.) ± (syst.) MC@NLO POWHEG
+ PYTHIA
POWHEG
+ HERWIG
SHERPA ALPGEN
+ HERWIG
veto region:|y| < 0.8
25 76.9± 1.1+2.0−2.1 79.5± 0.1 75.0± 0.3 74.3± 0.3 74.9± 0.3 76.7± 0.3 ρ7525= 0.52
75 92.3± 0.7 ± 0.5 94.3 91.8± 0.2 92.2± 0.2 93.4± 0.2 93.4± 0.2 ρ15075 = 0.51
150 97.8+0.3−0.4± 0.4 98.4 97.2± 0.1 97.6± 0.1 97.8± 0.1 98.0± 0.1 ρ25150= 0.27
veto region: 0.8≤ |y| < 1.5
25 80.4± 1.0 ± 1.7 82.0± 0.1 79.5± 0.2 79.5± 0.3 79.8± 0.3 81.3± 0.3 ρ7525= 0.49
75 93.9± 0.6+0.5−0.4 94.7 93.5± 0.2 93.8± 0.2 94.8± 0.1 94.7± 0.2 ρ15075 = 0.55
150 97.9+0.3−0.4± 0.2 98.4 97.7± 0.1 98.0± 0.1 98.4± 0.1 98.2± 0.1 ρ25150= 0.29
veto region: 1.5≤ |y| < 2.1
25 86.8+0.8−0.9+1.2−1.1 86.1± 0.1 85.4± 0.2 85.5± 0.2 85.6± 0.2 86.4± 0.2 ρ7525= 0.42
75 97.6± 0.4 ± 0.4 95.8 95.9± 0.1 96.0± 0.1 96.5± 0.1 95.9± 0.1 ρ15075 = 0.48
150 99.4+0.2−0.3± 0.2 98.8 98.7± 0.1 98.8± 0.1 98.9± 0.1 98.8± 0.1 ρ25150= 0.20
veto region:|y| < 2.1
25 56.4± 1.3+2.6−2.8 57.0± 0.1 52.7± 0.3 52.5± 0.3 54.0± 0.3 55.2± 0.3 ρ7525= 0.48
75 84.7± 0.9 ± 1.0 85.7± 0.1 82.7± 0.2 83.6± 0.2 86.0± 0.2 85.1± 0.2 ρ15075 = 0.50
Table 3 The measured values of f (Qsum)for Qsum= 55, 150 and
300 GeV for the different rapidity intervals used to veto jet activity are presented, excluding any measurements of f (Qsum)= 1.0. The
pre-dictions from the Monte Carlo event generators and the statistical cor-relations (ρi
j) between measurements are presented in the same way as in Table2
Qsum[GeV] f (Qsum)(%) ρji
Data± (stat.) ± (syst.) MC@NLO POWHEG
+ PYTHIA
POWHEG
+ HERWIG
SHERPA ALPGEN
+ HERWIG
veto region:|y| < 0.8
55 88.1+0.8−0.9+1.3−1.4 91.4± 0.1 88.0± 0.2 88.4± 0.2 89.9± 0.2 90.1± 0.2 ρ15055 = 0.45
150 97.4+0.4−0.5+0.8−0.9 98.4 97.2± 0.1 97.6± 0.1 97.8± 0.1 98.0± 0.1 ρ300150= 0.46
300 99.4+0.2−0.3± 0.3 99.7 99.4 99.6 99.6 99.6 ρ55300= 0.20
veto region: 0.8≤ |y| < 1.5
55 89.3± 0.8 ± 0.9 92.0 90.6± 0.2 91.1± 0.2 92.2± 0.2 92.0± 0.2 ρ15055 = 0.48
150 97.3± 0.4 ± 0.3 98.4 97.7± 0.1 98.0± 0.1 98.4± 0.1 98.2± 0.1 ρ150
300= 0.34
300 99.6+0.1−0.2± 0.1 99.8 99.6 99.6 99.7 99.6 ρ55300= 0.15
veto region: 1.5≤ |y| < 2.1
55 95.2+0.5−0.6± 0.6 93.8 93.6± 0.2 93.9± 0.2 94.6± 0.2 94.1± 0.2 ρ15055 = 0.40
150 99.3+0.2−0.3± 0.2 98.8 98.7± 0.1 98.8± 0.1 98.9± 0.1 98.8± 0.1 –
veto region:|y| < 2.1
55 72.7± 1.1+2.3−2.5 79.0± 0.1 75.3± 0.3 76.5± 0.3 79.6± 0.3 78.6± 0.3 ρ55
150= 0.47
150 92.1± 0.7 ± 0.8 95.6 93.9± 0.1 94.5± 0.1 95.3± 0.1 95.1± 0.1 ρ300150= 0.46
300 98.1+0.3−0.4+0.2−0.3 99.4 98.8± 0.1 99.1± 0.1 99.2± 0.1 99.1± 0.1 ρ55300= 0.21
1.5≤ |y| < 2.1. Furthermore, MC@NLO produces too lit-tle activity in the central region|y| < 0.8.
The data were compared to the predictions obtained after increasing (or decreasing) the amount of initial state radia-tion produced by the PYTHIAparton shower when applied to ACERMC events. These initial state parton shower vari-ations have been used to determine modelling uncertainties in previous ATLAS top quark measurements. Although the data are within the band of these predictions, the size of the band is a factor of two or more larger than the experi-mental precision. The results presented here can be used to constrain model-dependent uncertainties in future measure-ments.
Acknowledgements We thank CERN for the very successful oper-ation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.
We acknowledge the support of ANPCyT, Argentina; YerPhI, Ar-menia; ARC, Australia; BMWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIEN-CIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Repub-lic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET and ERC, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNAS, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Ger-many; GSRT, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slo-vakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN,
Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United King-dom; DOE and NSF, United States of America.
The crucial computing support from all WLCG partners is ac-knowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA) and in the Tier-2 facilities worldwide.
Open Access This article is distributed under the terms of the Cre-ative Commons Attribution License which permits any use, distribu-tion, and reproduction in any medium, provided the original author(s) and the source are credited.
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A.S. Chisholm17, R.T. Chislett77, M.V. Chizhov64, G. Choudalakis30, S. Chouridou137, I.A. Christidi77, A. Christov48, D. Chromek-Burckhart29, M.L. Chu151, J. Chudoba125, G. Ciapetti132a,132b, A.K. Ciftci3a, R. Ciftci3a, D. Cinca33, V. Cin-dro74, C. Ciocca19a, A. Ciocio14, M. Cirilli87, M. Citterio89a, M. Ciubancan25a, A. Clark49, P.J. Clark45, W. Cle-land123, J.C. Clemens83, B. Clement55, C. Clement146a,146b, R.W. Clifft129, Y. Coadou83, M. Cobal164a,164c, A.
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Cour-neyea169, G. Cowan76, C. Cowden27, B.E. Cox82, K. Cranmer108, F. Crescioli122a,122b, M. Cristinziani20, G. Crosetti36a,36b, R. Crupi72a,72b, S. Crépé-Renaudin55, C.-M. Cuciuc25a, C. Cuenca Almenar176, T. Cuhadar Donszelmann139, M. Curatolo47, C.J. Curtis17, C. Cuthbert150, P. Cwetanski60, H. Czirr141, P. Czodrowski43, Z. Czyczula176, S. D’Auria53, M. D’Onofrio73, A. D’Orazio132a,132b, P.V.M. Da Silva23a, C. Da Via82, W. Dabrowski37, A. Dafinca118, T. Dai87, C. Dallapiccola84, M. Dam35, M. Dameri50a,50b, D.S. Damiani137, H.O. Danielsson29, D. Dannheim99, V. Dao49, G. Darbo50a, G.L.
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Gous-siou138, C. Goy4, S. Gozpinar22, I. Grabowska-Bold37, P. Grafström29, K-J. Grahn41, F. Grancagnolo72a, S. Grancagnolo15, V. Grassi148, V. Gratchev121, N. Grau34, H.M. Gray29, J.A. Gray148, E. Graziani134a, O.G. Grebenyuk121, T. Greenshaw73, Z.D. Greenwood24,l, K. Gregersen35, I.M. Gregor41, P. Grenier143, J. Griffiths138, N. Grigalashvili64, A.A. Grillo137, S. Grin-stein11, Y.V. Grishkevich97, J.-F. Grivaz115, E. Gross172, J. Grosse-Knetter54, J. Groth-Jensen172, K. Grybel141, V.J. Guar-ino5, D. Guest176, C. Guicheney33, A. Guida72a,72b, S. Guindon54, H. Guler85,n, J. Gunther125, B. Guo158, J. Guo34, A. Gupta30, Y. Gusakov64, V.N. Gushchin128, P. Gutierrez111, N. Guttman153, O. Gutzwiller173, C. Guyot136, C. Gwenlan118, C.B. Gwilliam73, A. Haas143, S. Haas29, C. Haber14, H.K. Hadavand39, D.R. Hadley17, P. Haefner99, F. Hahn29, S. Haider29, Z. Hajduk38, H. Hakobyan177, D. Hall118, J. Haller54, K. Hamacher175, P. Hamal113, M. Hamer54, A. Hamilton145b,o, S. Hamilton161, H. Han32a, L. Han32b, K. Hanagaki116, K. Hanawa160, M. Hance14, C. Handel81, P. Hanke58a, J.R. Hansen35, J.B. Hansen35, J.D. Hansen35, P.H. Hansen35, P. Hansson143, K. Hara160, G.A. Hare137, T. Harenberg175, S. Harkusha90, D. Harper87, R.D. Harrington45, O.M. Harris138, K. Harrison17, J. Hartert48, F. Hartjes105, T. Haruyama65, A. Harvey56, S. Hasegawa101, Y. Hasegawa140, S. Hassani136, M. Hatch29, D. Hauff99, S. Haug16, M. Hauschild29, R. Hauser88, M. Havranek20, B.M. Hawes118, C.M. Hawkes17, R.J. Hawkings29, A.D. Hawkins79, D. Hawkins163, T. Hayakawa66, T. Hayashi160, D. Hayden76, H.S. Hayward73, S.J. Haywood129, E. Hazen21, M. He32d, S.J. Head17, V. Hedberg79, L. Heelan7, S. Heim88, B. Heinemann14, S. Heisterkamp35, L. Helary4, C. Heller98, M. Heller29, S. Hellman146a,146b, D. Hellmich20, C. Helsens11, R.C.W. Henderson71, M. Henke58a, A. Henrichs54, A.M. Henriques Correia29, S. Henrot-Versille115, F. Henry-Couannier83, C. Hensel54, T. Henß175, C.M. Hernandez7, Y. Hernández Jiménez167, R. Herrberg15, G. Herten48, R. Hertenberger98, L. Hervas29, G.G. Hesketh77, N.P. Hessey105, E. Higón-Rodriguez167, D. Hill5,*, J.C. Hill27, N. Hill5, K.H. Hiller41, S. Hillert20, S.J. Hillier17, I. Hinchliffe14, E. Hines120, M. Hirose116, F. Hirsch42, D. Hirschbuehl175, J. Hobbs148, N. Hod153, M.C. Hodgkinson139, P. Hodgson139, A. Hoecker29, M.R. Hoeferkamp103, J. Hoffman39, D. Hoff-mann83, M. Hohlfeld81, M. Holder141, S.O. Holmgren146a, T. Holy127, J.L. Holzbauer88, Y. Homma66, T.M. Hong120, L. Hooft van Huysduynen108, T. Horazdovsky127, C. Horn143, S. Horner48, J-Y. Hostachy55, S. Hou151, M.A. Houlden73, A. Hoummada135a, J. Howarth82, D.F. Howell118, I. Hristova15, J. Hrivnac115, I. Hruska125, T. Hryn’ova4, P.J. Hsu81, S.-C. Hsu14, G.S. Huang111, Z. Hubacek127, F. Hubaut83, F. Huegging20, A. Huettmann41, T.B. Huffman118, E.W. Hughes34, G. Hughes71, R.E. Hughes-Jones82, M. Huhtinen29, P. Hurst57, M. Hurwitz14, U. Husemann41, N. Huseynov64,p, J. Huston88, J. Huth57, G. Iacobucci49, G. Iakovidis9, M. Ibbotson82, I. Ibragimov141, R. Ichimiya66, L. Iconomidou-Fayard115, J. Idar-raga115, P. Iengo102a, O. Igonkina105, Y. Ikegami65, M. Ikeno65, Y. Ilchenko39, D. Iliadis154, N. Ilic158, M. Imori155, T. Ince20, J. Inigo-Golfin29, P. Ioannou8, M. Iodice134a, K. Iordanidou8, V. Ippolito132a,132b, A. Irles Quiles167, C. Isaksson166, A. Ishikawa66, M. Ishino67, R. Ishmukhametov39, C. Issever118, S. Istin18a, A.V. Ivashin128, W. Iwanski38, H. Iwasaki65, J.M. Izen40, V. Izzo102a, B. Jackson120, J.N. Jackson73, P. Jackson143, M.R. Jaekel29, V. Jain60, K. Jakobs48, S. Jakob-sen35, J. Jakubek127, D.K. Jana111, E. Jansen77, H. Jansen29, A. Jantsch99, M. Janus48, G. Jarlskog79, L. Jeanty57, K. Jelen37, I. Jen-La Plante30, P. Jenni29, A. Jeremie4, P. Jež35, S. Jézéquel4, M.K. Jha19a, H. Ji173, W. Ji81, J. Jia148, Y. Jiang32b, M. Jimenez Belenguer41, G. Jin32b, S. Jin32a, O. Jinnouchi157, M.D. Joergensen35, D. Joffe39, L.G. Johansen13, M. Johansen146a,146b, K.E. Johansson146a, P. Johansson139, S. Johnert41, K.A. Johns6, K. Jon-And146a,146b, G. Jones118, R.W.L. Jones71, T.W. Jones77, T.J. Jones73, O. Jonsson29, C. Joram29, P.M. Jorge124a, J. Joseph14, K.D. Joshi82, J. Jovice-vic147, T. Jovin12b, X. Ju173, C.A. Jung42, R.M. Jungst29, V. Juranek125, P. Jussel61, A. Juste Rozas11, V.V. Kabachenko128, S. Kabana16, M. Kaci167, A. Kaczmarska38, P. Kadlecik35, M. Kado115, H. Kagan109, M. Kagan57, S. Kaiser99, E. Ka-jomovitz152, S. Kalinin175, L.V. Kalinovskaya64, S. Kama39, N. Kanaya155, M. Kaneda29, S. Kaneti27, T. Kanno157, V.A. Kantserov96, J. Kanzaki65, B. Kaplan176, A. Kapliy30, J. Kaplon29, D. Kar53, M. Karagounis20, M. Karagoz118,
