6.3 Event yields
7.1.1 QCD multi-jets background determination with a fit method
QCD multi-jets background is often determined by means of the data driven methods. Usu-ally, one extrapolates a background measurement in a control region into a signal region. The selection of events in these two regions has to be orthogonal. This means that the two regions do not share events. The background has to dominate in the control region. In order to ensure that the selected control region is really dominated by the background under study the reli-able Monte-Carlo simulation of the rest of the physics processes contributing into the control region is necessary. Besides, there is a very important requirement to data driven methods, which is the homogeneity of the control and signal regions under the observable used for discrimination of the background. In other words, the background estimate is a function (can be analytical or empirical) of some observable and this function is equivalently valid in both the control and the signal selection regions to describe the background. This requirement to data driven methods needs to be checked by auxiliary studies using Monte-Carlo simulation or data.
The idea of the proposed method is to use the triangular variable,E/T +mT(W), to define the control and signal regions. This variable was found to be the most helpful one to discrim-inate between theW-like events and others (see Section6.2). Figure7.1(left column) shows the triangular variable distribution after the pretag selection. The distributions correspond (from top to bottom) to1j/1cj/central,1j/1cj/sides,2j/1cj/centraland2j/1cj/sidesevents respectively after the pretag selection 1. Uncertainties in data counts are estimated from a Poisson distribution, while Monte-Carlo samples have Gaussian uncertainties due to the lim-ited sizes. Data minus Monte-Carlo distribution (QCD multi-jets templates) uncertainties are taken as Poissonian, since they are driven by the data uncertainties rather than the smal-ler statistical uncertainties of the Monte-Carlo samples. The same applies to all plots of this chapter, where the QCD multi-jets templates are presented. The predictions of Monte-Carlo simulation for the different physics processes are stacked on top of each other. These plots show that the lower kinetic region (<60GeV) of the triangular variable distribution is dom-inated by the QCD multi-jets background assuming the reliability of the Monte-Carlo predic-tions for the rest of background processes2. In contrast to that, a good matching of the
distri-1The notations for the event selection regions are defined in Section6.2.
2The assumption applies mostly to the overall normalization of the Monte-Carlo background samples rather than their distribution shapes.
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000 4000 5000
0 50 100 150 200
e+jets pretag selection
Jets total/central = 1/1
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(a)1j/1cj/central
/ ndf
χ2 3.9 / 3
Prob 0.27
Constant 2.6e+04 ± 3.0e+02 MPV 2.3e+04 ± 1.7e+02 Sigma 8.5e+03 ± 1.1e+02
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000 4000 5000
/ ndf
χ2 3.9 / 3
Prob 0.27
Constant 2.6e+04 ± 3.0e+02 MPV 2.3e+04 ± 1.7e+02 Sigma 8.5e+03 ± 1.1e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 1/1
|<1.37 ηe
| L = 35 pb-1
∫
(b)1j/1cj/central, data fit
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000 4000
0 50 100 150 200
e+jets pretag selection
Jets total/central = 1/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(c)1j/1cj/sides
/ ndf
χ2 2.6 / 3
Prob 0.46
Constant 2e+04 ± 2.75e+02 MPV 2.1e+04 ± 1.7e+02 Sigma 7.6e+03 ± 1.2e+02
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000
/ ndf
χ2 2.6 / 3
Prob 0.46
Constant 2e+04 ± 2.75e+02 MPV 2.1e+04 ± 1.7e+02 Sigma 7.6e+03 ± 1.2e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 1/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(d)1j/1cj/sides, data fit
[GeV]
ET
(W) + mT
Events
0 50 100 150 200
0 50 100 150 200
e+jets pretag selection
Jets total/central = 2/1
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(e)2j/1cj/central
/ ndf
χ2 0.73 / 3
Prob 0.87
Constant 1.1e+03 ± 5.2e+01 MPV 3e+04 ± 1.18e+03 Sigma 1.1e+04 ± 7.1e+02
[GeV]
ET
(W) + mT
Events
0 50 100 150 200 250
/ ndf
χ2 0.73 / 3
Prob 0.87
Constant 1.1e+03 ± 5.2e+01 MPV 3e+04 ± 1.18e+03 Sigma 1.1e+04 ± 7.1e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 2/1
|<1.37 ηe
| L = 35 pb-1
∫
(f)2j/1cj/central, data fit
[GeV]
ET
(W) + mT
Events
0 50 100 150 200
0 50 100 150 200
e+jets pretag selection
Jets total/central = 2/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(g)2j/1cj/sides
/ ndf
χ2 3.3 / 3
Prob 0.35
Constant 9.7e+02 ± 4.9e+01 MPV 3e+04 ± 1.33e+03 Sigma 1.2e+04 ± 8.9e+02
[GeV]
ET
(W) + mT
Events
0 50 100 150 200
/ ndf
χ2 3.3 / 3
Prob 0.35
Constant 9.7e+02 ± 4.9e+01 MPV 3e+04 ± 1.33e+03 Sigma 1.2e+04 ± 8.9e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 2/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(h)2j/1cj/sides, data fit
Figure 7.1: Triangular variable distributions in the different events after the pretag selection. Plots on the left column present stacked distribution of the Monte-Carlo simulated samples superimposed with the QCD multi-jets templates and data. Plots on the right column show the same distributions
/ ndf
χ2 44 / 3
Prob 1.8e-09
Constant 1.7e+04 ± 3.3e+02 MPV 1.9e+04 ± 2.1e+02 Sigma 6.5e+03 ± 1.3e+02
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000 4000 5000
/ ndf
χ2 44 / 3
Prob 1.8e-09
Constant 1.7e+04 ± 3.3e+02 MPV 1.9e+04 ± 2.1e+02 Sigma 6.5e+03 ± 1.3e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 1/1
|<1.37 ηe
| L = 35 pb-1
∫
(a)1j/1cj/central
/ ndf
χ2 21 / 3
Prob 0.00013
Constant 1.6e+04 ± 3.0e+02 MPV 1.8e+04 ± 1.9e+02 Sigma 6.4e+03 ± 1.2e+02
[GeV]
ET
(W) + mT
Events
0 1000 2000 3000
/ ndf
χ2 21 / 3
Prob 0.00013
Constant 1.6e+04 ± 3.0e+02 MPV 1.8e+04 ± 1.9e+02 Sigma 6.4e+03 ± 1.2e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 1/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(b)1j/1cj/sides
/ ndf
χ2 1.3 / 3
Prob 0.74
Constant 7.3e+02 ± 5.8e+01 MPV 2.6e+04 ± 1.5e+03 Sigma 9e+03 ± 8.83e+02
[GeV]
ET
(W) + mT
Events
0 100 200 300
/ ndf
χ2 1.3 / 3
Prob 0.74
Constant 7.3e+02 ± 5.8e+01 MPV 2.6e+04 ± 1.5e+03 Sigma 9e+03 ± 8.83e+02
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 2/1
|<1.37 ηe
| L = 35 pb-1
∫
(c)2j/1cj/central
/ ndf
χ2 2.9 / 3
Prob 0.41
Constant 5.5e+02 ± 5.1e+01 MPV 2.7e+04 ± 2.0e+03 Sigma 1.1e+04 ± 1.4e+03
[GeV]
ET
(W) + mT
Events
0 50 100 150 200 250
/ ndf
χ2 2.9 / 3
Prob 0.41
Constant 5.5e+02 ± 5.1e+01 MPV 2.7e+04 ± 2.0e+03 Sigma 1.1e+04 ± 1.4e+03
0 50 100 150 200
Data Data-MC e+jets pretag selection
Jets total/central = 2/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(d)2j/1cj/sides
Figure 7.2: Triangular variable distributions in the different events after the pretag selection. Data and the corresponding QCD multi-jets template are presented together on each plot. QCD multi-jets templates are fitted with a Landau distribution in theE/T +mT(W)<60GeV control region.
bution shapes in data and Monte-Carlo simulation in higher kinetic region (>60GeV) clearly indicates that the QCD multi-jets contribution is small in there. The right column of Figure 7.1 presents the plots with the triangular variable distributions in data and QCD multi-jets templates corresponding to the same events as those on the left column. It was found em-pirically that the lower region (<60GeV) of the distribution is well modeled by the Landau distribution. This can be seen from the fit results, which are included in the plots. The free parameters of the Landau fit function, the approximate most probable value (MPV) and the Landau density scale parameter (Sigma), are given in the MeV units. The Landau fit function is defined by Equation7.1[172],
L(x) = (
Constant·Rc+i∞
c−i∞ exp(xs+slog(s))ds Sigma6= 0
0 Sigma = 0 (7.1)
Where,s= (x−MPV)/Sigma. Equation7.1without the constant factor (also fit free para-meter) is a probability density function of a Landau distribution.
Since the fitted region is dominated by QCD multi-jets events, we assume that the triangu-lar variable in QCD multi-jets obeys the Landau distribution in the lower kinematic region (<60GeV). The assumption is extended to the higher kinematic region where the signal se-lection is done. It should be noted that the fit region has large contribution of the W+jets and Z+jets events as predicted by Monte-Carlo simulation. This fact should be taken into account when fitting. Figure 7.2 shows fit results of the QCD multi-jets templates. The templates are not well modeled by the Landau distribution. Especially, one can see this on the upper row plots, which correspond to 1j/1cj/centraland1j/1cj/sidesevent selection with larger numbers of events. The reason for this discrepancy might be that the true QCD multi-jets tribution is not the Landau distribution or the Monte-Carlo shapes of W+jets and Z+jets dis-tributions might be incorrectly modeled that affects the derived shapes of the QCD multi-jets templates. A more discriminative control region for QCD multi-jets event selection is needed.
In order to obtain a cleaner control region for QCD multi-jets, we explore events after the tag selection (pretag selection plus the b-jet requirement). Figure 7.3 shows the triangular variable distribution obtained after the events tag selection. Plots correspond (from top to bottom) to 1j/1cj/central, 1j/1cj/sides, 2j/1cj/central and 2j/1cj/sides events. The left column shows the distributions of the triangular variable in data and Monte-Carlo simulation as well as the QCD multi-jets templates obtained in the same way as before. Theb-tagged jet requirement significantly reduces the fraction of W+jets, Z+jets and other processes in the control region as predicted by Monte-Carlo simulation. The fractions of the total expected non QCD multi-jets processes below the60GeV threshold is less than10%,9%,15%and27%
in the1j/1cj/central,1j/1cj/sides,2j/1cj/centraland2j/1cj/sidesevents respectively. This makes the QCD multi-jets triangular distribution normalization and shape prediction much less sensitive to uncertainties of the predictions of Monte-Carlo simulation for W+jets and Z+jets. The QCD multi-jets templates are fitted with a Landau distribution in the control region,E/T +mT(W) <60GeV. The fit results are extrapolated into the signal region. These results are shown in the right column plots in Figure7.3.
We assumed that the triangular variable for QCD multi-jets continues to be Landau dis-tributed in the signal region. There is no physics reason that the true distribution should have more contribution in the signal region implying an existence of some peak structure.
This is expected due to the fact that in the QCD multi-jets events there is no internal physics constraints for a lepton pT, E/T and∆φbetween the lepton and E/T vectors like it is in the
[GeV]
ET
(W) + mT
Events
0 50 100 150
0 50 100 150 200
e+jets tag selection
Jets total/central = 1/1
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(a)1j/1cj/central
[GeV]
ET
(W) + mT
Events
0 50 100 150
/ ndf
χ2 6.2 / 3
Prob 0.1
Constant 7.7e+02 ± 54 MPV 1.9e+04 ± 7.9e+02 Sigma 6.6e+03 ± 4.1e+02
/ ndf
χ2 6.2 / 3
Prob 0.1
Constant 7.7e+02 ± 54 MPV 1.9e+04 ± 7.9e+02 Sigma 6.6e+03 ± 4.1e+02
0 50 100 150 200
Data-MC Fit extrap.
e+jets tag selection
Jets total/central = 1/1
|<1.37 ηe
| L = 35 pb-1
∫
(b)1j/1cj/central, fit result
[GeV]
ET
(W) + mT
Events
0 20 40 60
0 50 100 150 200
e+jets tag selection
Jets total/central = 1/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(c)1j/1cj/sides
[GeV]
ET
(W) + mT
Events
0 20 40 60
/ ndf
χ2 0.83 / 3
Prob 0.84
Constant 2.9e+02 ± 33 MPV 2.1e+04 ± 1.6e+03 Sigma 8e+03 ± 9.3e+02
/ ndf
χ2 0.83 / 3
Prob 0.84
Constant 2.9e+02 ± 33 MPV 2.1e+04 ± 1.6e+03 Sigma 8e+03 ± 9.3e+02
0 50 100 150 200
Data-MC Fit extrap.
e+jets tag selection
Jets total/central = 1/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(d)1j/1cj/sides, fit result
[GeV]
ET
(W) + mT
Events
0 5 10 15
0 50 100 150 200
e+jets tag selection
Jets total/central = 2/1
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(e)2j/1cj/central
[GeV]
ET
(W) + mT
Events
0 5 10
/ ndf
χ2 0.92 / 3
Prob 0.82
Constant 41 ± 12 MPV 3.1e+04 ± 5.8e+03 Sigma 9.8e+03 ± 4e+03
/ ndf
χ2 0.92 / 3
Prob 0.82
Constant 41 ± 12 MPV 3.1e+04 ± 5.8e+03 Sigma 9.8e+03 ± 4e+03
0 50 100 150 200
Data-MC Fit extrap.
e+jets tag selection
Jets total/central = 2/1
|<1.37 ηe
| L = 35 pb-1
∫
(f)2j/1cj/central, fit result
[GeV]
ET
(W) + mT
Events
0 2 4 6
0 50 100 150 200
e+jets tag selection
Jets total/central = 2/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(g)2j/1cj/sides
[GeV]
ET
(W) + mT
Events
0 2 4 6
/ ndf
χ2 1.4 / 3
Prob 0.71
Constant 16 ± 12 MPV 2.9e+04 ± 7.6e+03 Sigma 6.6e+03 ± 4e+03
/ ndf
χ2 1.4 / 3
Prob 0.71
Constant 16 ± 12 MPV 2.9e+04 ± 7.6e+03 Sigma 6.6e+03 ± 4e+03
0 50 100 150 200
Data-MC Fit extrap.
e+jets tag selection
Jets total/central = 2/1
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
(h)2j/1cj/sides, fit result
Figure 7.3: Triangular variable distributions in the different events after the tag selection. The left column shows the plots with data, the stacked samples of Monte-Carlo simulation and the derived QCD multi-jets template. The right column plots show the QCD multi-jets templates fitted with a
W-like and also to some extent in theZ-like events. Rather a monotonically falling behavior of the triangular variable distribution is expected in the QCD multi-jets events. Therefore, the Landau distribution, which describes well this variable in the control region can be consider as the optimal model of the QCD multi-jets contribution in the signal region. Later (see Sec-tion8.1.3), we also consider an exponential model of the distribution in order to explore the model dependence of the estimated contribution of the QCD multi-jets background into the signal selection.
[GeV]
ET
(W) + mT
Events
0 20 40 60 80 100 120 140
/ ndf
χ2 9.2 / 8
Prob 0.32
Fakes (SR, 1j/1cj, central) 84 ± 7.8 MPV [MeV] 2e+04 ± 7.2e+02 Sigma (limited) [MeV] 7e+03 ± 3.9e+02 Fakes (SR, 1j/1cj, sides) 36 ± 4.1
/ ndf
χ2 9.2 / 8
Prob 0.32
Fakes (SR, 1j/1cj, central) 84 ± 7.8 MPV [MeV] 2e+04 ± 7.2e+02 Sigma (limited) [MeV] 7e+03 ± 3.9e+02 Fakes (SR, 1j/1cj, sides) 36 ± 4.1
0 50 100 150 200 0 50 100 150 200 e+jets tag selection 1j/1cj
|<1.37 ηe
| 1.52<|ηe|<2.47
Data-MC Fit func.
Extrap., central Extrap., sides
Figure 7.4: Simultaneous fit of two concatenated QCD multi-jets templates of the triangular vari-able distribution with a Landau distribution. The templates correspond to the 1j/1cj/central and 1j/1cj/sidesevents after the tag selection. See the text for the description of the free fitparameters.
In order to improve results a simultaneous fit of the QCD multi-jets templates (Figure7.3, plots on the right column) is performed. The templates corresponding to the events with the same jet configuration but the different pseudo-rapidity regions of electrons are coupled in the fit. Figure7.4shows such a simultaneous fit with a Landau distribution of the QCD multi-jets templates corresponding to the1j/1cj/centraland1j/1cj/sidesevents after the tag selection.
The two distributions are concatenated. The control region parts of the two distributions are simultaneously fitted and the fit function is extrapolated in both signal regions. In the sim-ultaneous fit, the fit free parameters, MPV and Sigma, are the same for both concatenated distributions. The free normalization parameters (the first and the last ones on the plot) of the fit correspond to the integrals from the fit Landau function in the signal regions (>60GeV) of both concatenated distributions normalized to thex-range of integration. Thus, they are the QCD multi-jets contribution estimates obtained directly from the fit. These estimates depend on an upper limit of the integration of the Landau function. Here, the upper limit is chosen to be230GeV, which is suggested by data distribution itself3but remains ambiguous. As it will be shown later, the data weighting method, which uses the obtained Landau shapes of the QCD multi-jets background can be used to estimate this background in any range of the tri-angular variable distribution independently on the exact upper limit of the integration range.
3The upper limit of the highest bin of the corresponding distribution in data, which contains at least one entry is chosen as the upper limit of the integration.
[GeV]
ET
(W) + mT
Events
0 2 4 6 8 10 12
/ ndf
χ2 2.6 / 8
Prob 0.96
Fakes (SR, 2j/1cj, central) 10 ± 5.4
MPV [MeV] 3e+04 ± 4.5e+03
Sigma (limited) [MeV] 9e+03 ± 3.1e+03 Fakes (SR, 2j/1cj, sides) 3.2 ± 2.1
/ ndf
χ2 2.6 / 8
Prob 0.96
Fakes (SR, 2j/1cj, central) 10 ± 5.4
MPV [MeV] 3e+04 ± 4.5e+03
Sigma (limited) [MeV] 9e+03 ± 3.1e+03 Fakes (SR, 2j/1cj, sides) 3.2 ± 2.1
0 50 100 150 200 0 50 100 150 200 e+jets tag selection 2j/1cj
|<1.37 ηe
| 1.52<|ηe|<2.47
Data-MC Fit func.
Extrap., central Extrap., sides
Figure 7.5: Simultaneous fit of two concatenated QCD multi-jets templates of the triangular vari-able distribution with a Landau distribution. The templates correspond to the 2j/1cj/central and 2j/1cj/sidesevents after the tag selection. See the text for the description of the free fit parameters.
Figure 7.5 shows the results of the similar simultaneous fit of the concatenated triangular variable distributions in the2j/1cj/centraland2j/1cj/sidesevents after the tag selection.
The obtained Landau fit functions will be used to derive one-dimensional maps of the QCD multi-jets event weights. These weights are used to obtain the data driven distributions for the observables of interest (see Section7.1.3).
A similar measurement of the QCD multi-jets background is performed in those events with higher multiplicity of central jets, where the measurement is not restricted by the small amount of data. The control regions in the triangular distribution are plagued by a higher uncertainty level, since higher fractions of W+jets events are expected in the lower bins of the distribution. Figure7.6presents the triangular variable distribution plots after the tag selec-tion of events. The distribuselec-tions correspond to the2j/2cj/central,2j/2cj/sides,3j/2cj/central and3j/3cj/centralevents, where the available data allow to derive the QCD multi-jets tem-plates. The fit of these templates with a Landau distribution converges.
Figure7.7shows simultaneous fit results of the QCD multi-jets templates for their two com-binations,2j/2cj/centraltogether with2j/2cj/sidesevents (left plot) and2j/2cj/central to-gether with3j/2cj/centralevents (right plot). The results indicate that the method is valid for these events. It can be noted that the obtained Landau distribution shapes for QCD multi-jets events with 2 central jets have larger value for the sigma (limited) parameter than for the events with1central jet (see Figures7.4and7.5). In general, the estimates of sigma (limited) and MPV are higher for the events with higher multiplicity of jets. This fact causes a bad qual-ity of the simultaneous fit of the1j/1cj/centraland2j/2cj/centralevents shown on Figure 7.8. The template for the QCD multi-jets2j/2cj/centralevents is not well described by the fit function, which free parameters are mainly determined by the1j/1cj/centralevents.
[GeV]
ET
(W) + mT
Events
0 10 20 30 40
0 50 100 150 200
e+jets tag selection
Jets total/central = 2/2
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(a)2j/2cj/central
[GeV]
ET
(W) + mT
Events
0 5 10 15 20
0 50 100 150 200
e+jets tag selection
Jets total/central = 2/2
|<2.47 ηe
1.52<|
L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(b)2j/2cj/sides
[GeV]
ET
(W) + mT
Events
0 2 4 6 8 10
0 50 100 150 200
e+jets tag selection
Jets total/central = 3/2
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(c)3j/2cj/central
[GeV]
ET
(W) + mT
Events
0 5 10 15 20 25
0 50 100 150 200
e+jets tag selection
Jets total/central = 3/3
|<1.37 ηe
| L = 35 pb-1
∫
processes t-channel Wt di-bosons
t t W+Jets Z+Jets Data Data-MC
(d)3j/3cj/central
Figure 7.6: Triangular variable distributions in the different events after the tag selection. Data, the stacked samples from Monte-Carlo simulation and the QCD multi-jets templates are superimposed.
The QCD multi-jets templates are fitted with a Landau distribution in the control region.
[GeV]
ET
(W) + mT
Events
0 10 20 30 40 50
/ ndf
χ2 8 / 8
Prob 0.43
Fakes (SR, 2j/2cj, central) 48 ± 13 MPV [MeV] 3e+04 ± 2.9e+03 Sigma (limited) [MeV] 1.1e+04 ± 1.8e+03 Fakes (SR, 2j/2cj, sides) 23 ± 6.6
/ ndf
χ2 8 / 8
Prob 0.43
Fakes (SR, 2j/2cj, central) 48 ± 13 MPV [MeV] 3e+04 ± 2.9e+03 Sigma (limited) [MeV] 1.1e+04 ± 1.8e+03 Fakes (SR, 2j/2cj, sides) 23 ± 6.6
0 50 100 150 2000 50 100 150 200 e+jets tag selection 2j/2cj
|<1.37 ηe
| 1.52<|ηe|<2.47
Data-MC Fit func.
Extrap., central Extrap., sides
(a)2j/2cj/centraland2j/2cj/sides
[GeV]
ET
(W) + mT
Events
0 10 20 30 40 50
/ ndf
χ2 8 / 8
Prob 0.43
Fakes (SR, 2j/2cj, central) 48 ± 13 MPV [MeV] 3e+04 ± 2.9e+03 Sigma (limited) [MeV] 1.1e+04 ± 1.8e+03 Fakes (SR, 3j/2cj, central) 23 ± 6.6
/ ndf
χ2 8 / 8
Prob 0.43
Fakes (SR, 2j/2cj, central) 48 ± 13 MPV [MeV] 3e+04 ± 2.9e+03 Sigma (limited) [MeV] 1.1e+04 ± 1.8e+03 Fakes (SR, 3j/2cj, central) 23 ± 6.6
0 50 100 150 2000 50 100 150 200 e+jets tag selection |ηe|<1.37
2j/2cj 3j/2cj
Data-MC Fit func.
Extrap., central Extrap., sides
(b)2j/2cj/centraland3j/2cj/central
Figure 7.7: Simultaneous fit of two concatenated QCD multi-jets templates of the triangular variable distribution with a Landau distribution. The templates correspond to the different events after the tag selection. See the text for the description of the free fit parameters.
[GeV]
ET
(W) + mT
Events
0 20 40 60 80 100 120 140
/ ndf
χ2 23 / 8
Prob 0.0028
Fakes (SR, 1j/1cj, central) 87 ± 8.4
MPV [MeV] 2e+04 ± 7.8e+02
Sigma (limited) [MeV] 7.1e+03 ± 4.2e+02 Fakes (SR, 2j/2cj, central) 20 ± 3.2
/ ndf
χ2 23 / 8
Prob 0.0028
Fakes (SR, 1j/1cj, central) 87 ± 8.4
MPV [MeV] 2e+04 ± 7.8e+02
Sigma (limited) [MeV] 7.1e+03 ± 4.2e+02 Fakes (SR, 2j/2cj, central) 20 ± 3.2
0 50 100 150 200 0 50 100 150 200 e+jets tag selection |ηe|<1.37
1j/1cj 2j/2cj
Data-MC Fit func.
Extrap., central Extrap., sides
Figure 7.8: Simultaneous fit of two concatenated QCD multi-jets templates of the triangular vari-able distribution with a Landau function. The templates correspond to the 1j/1cj/central and 2j/2cj/centralevents after the tag selection. The fit fails to describe the2j/2cj/centralevents. See the text for the description of the free fit parameters.