6.10 Systematic uncertainties
6.10.2 Systematic uncertainties aecting the normalization and m t¯ t shape
aect the mt¯tshape: the electron identi cation, the electron energy scale and the electron energy resolution uncertainties. The electron identi cation uncertainty corresponds to the uncertainty on the electron identi cation scale factors (see Section 4.5.3). It varies with ηcluster and ET between 3% and 5% and is applied in an event by event basis. In order to take into account discrepancies between the electron energy resolution on simulation and data, the electron energy for simulation events is smeared. In addition, the electron energy in data was corrected to match the Z boson peak mass. Electron energy scale and resolution uncertainties of the order of 1% to 2% are applied to the simulated samples in an object by object basis.
Muons related uncertainties The uncertainties on the corresponding muon trigger, identi -cation and reconstruction scale factors are applied (see Section4.6.2). These uncertainties are of the order of 1%-1.5%. In release 16 there was an issue with the trigger information in Monte Carlo and the trigger matching requirement has not been applied. An additional 1.5% uncertainty is applied to account for this. Muon momentum resolution and energy scales are varied up and down within uncertainties as prescribed by the ATLAS Muon Combined Performance Group, taking into account properly the dierences between the corrections applied to ID and MS separately.
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(a) (b)
(c) (d) s
(e) (f)
Figure 6.26: Impact of pile-up on the reconstructed t¯t mass for the (a,b) SM t¯t background, the (c,d) Z0 mZ0 = 800 GeV and the (e,f) gKK mgKK = 1300 GeV sample in linear (left) and logarithmic (right) scale.
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Jets-related uncertainties There are ve uncertainties associated with jets: the jet energy scale (JES), the pile up, the b−jet energy scale, the jet energy resolution (JER) and the jet reconstruction e ciency uncertainties. The JES uncertainty is the systematic uncer-tainty on the EM+JES calibration resulting from uncertainties on calorimeter response, dead material description, calorimeter cell noise thresholds description, fragmentation and underlying event modeling, the topology and avour composition [3,116]. Without taking into account the avor composition contribution and for |η| < 2.5, the JES uncertainty varies from about 4% for high pTjets to about 9% for low pT jets. The quark/gluon avor composition contribution varies with the samples used. A pile-up uncertainty on the JES is also applied to account for dierences in the jet energy scale in pile-up conditions dierent from that simulated in the sample used to derive the EM+JES calibration. It varies from about 2% for high pT jets to about 5% for low pT jets. The b−jet energy scale uncertainty accounts for the dierence of the energy scale for b−jets with respect to light quark jets.
b−jets are scaled by a factor that varies from about 0.8% in the high pT region to about 2.5% in the low pT region. The pile-up and b−jet uncertainties are added in quadrature to the JES uncertainty. The JER uncertainty accounts for dierences in the resolution on the jet energy in data and in Monte Carlo [109]. It is y and pT-dependent. It is evaluated by oversmearing the jet energy up to the JER uncertainty and then it is symmetrized. Finally the jet reconstruction e ciency uncertainty is evaluated by randomly dropping jets from events with a pT and |η|-dependent probability of about 2% [109].
b−tagging uncertainty The uncertainties on the b−tagging, c−tagging, τ−tagging and mis-tagging scale factors determined by the Flavor Tagging Performance Group are applied. In release 16 the c−tagging e ciency is considered to be fully correlated with the b-tagging e ciency.
ETmiss Any variation in an object's px or py is propagated to the EmissT measurement. Two ETmiss related systematic uncertainties are applied [122]. The rst accounts for the energy scale and energy resolution eects propagated to the MET. In this case an uncertainty is applied on the energy scale of energy deposits not associated with any objects (cellout) and on the soft jets. The second one accounts for the pile-up eects. The uncertainty on ETmiss due to pile-up eects is a at 10% uncertainty on the contributions not associated with any objects.
LAr hole In data recorded during the period during which some of the front-end boards in LAr calorimeter could not be read out, events aected by the LAr hole are vetoed. Having oc-curred after the production of the used Monte Carlo samples, it was necessary to apply the same procedure to simulated events to correct the mismatch between data and simulated events. A systematic uncertainty corresponding to varying the jet energy threshold for jets considered as potentially being in the LAr hole by 4 GeV is applied.
t¯t background related uncertainties There are four sources of systematic uncertainties af-fecting the SM t¯t background that have been studied: the modeling of the hard process, the simulation of the ISR and FSR, the modeling of the parton shower and fragmentation and the PDF choice.
The systematic uncertainty associated to the modeling of the hard process is addressed by comparing the t¯t mass spectra using two dierent Monte Carlo generators: MC@NLO and POWHEG.
The impact of the ISR and FSR modelization is estimated by comparing the t¯t mass spectra between the nominal MC@NLO sample and samples generated with ACERMC
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and showered with PYTHIA where the ISR and FSR parameters were varied in order to produce less or more gluon radiation. Six samples were generated: more ISR, less ISR, more FSR, less ISR, more ISR and FSR and less ISR and FSR. The sample with the largest deviation from the nominal one is used, which in this case corresponds to the varied ISR only.
The impact of the parton shower and fragmentation model is estimated by a comparison of POWHEG+HERWIG with POWHEG+PYTHIA samples. These three uncertainties are determined as a function of generated t¯t mass and applied to the baseline t¯t and signal samples.
Finally, the dierence in shape between the predictions obtained using CTEQ66 and MSTW2008nlo is used to estimate the PDF shape uncertainty. The dependence of the reconstructed mt¯t spectra for dierent Monte Carlo samples generated with dierent val-ues of the top-quark mass was also studied. The results shown a small change in yield (+1.1%, −2.0% for a 1 GeV variation in mt) and no signi cant change in the spectrum within available statistics for mt¯t> 400GeV. Therefore, this uncertainty is not considered in the limit setting.
W+jets background related uncertainties The W +jets shape uncertainty is determined by modifying some generator parameters such as the function which gives the factorization scale for the PDF (iqopt) and the minimum pT to consider a parton as a hard parton (ptjmin) with respect to the nominal sample (see Section 3.2.2.3). The avor composition of the W +jets background is varied as described in Section 6.7.2.
Multijet background related uncertainties The shape uncertainty on the multijet back-ground is described in Section 6.7.3.
The impact of each systematic uncertainties aecting the normalization and mt¯t shape on the total expected background yield and for the Z0 samples with mZ0 = 1 TeV is presented in Table 6.9. The dominant sources of shape systematic uncertainties are the b−tagging e ciency, the JES, the modeling of ISR and FSR and the W c/W bb/W cc normalization. The impact of some of the shape systematic uncertainties in the reconstructed mt¯t mass spectra is shown in Figures D.6 andD.7 and FiguresE.6and E.7for electron and muon channel, respectively.