14 |
|
region, |
15 |
|
for electrons and muons separately. |
16 |
|
|
17 |
< |
The choice to normalizing to the peak region of $M_T$ has the |
17 |
> |
The choice to normalize to the peak region of $M_T$ has the |
18 |
|
advantage that some uncertainties, e.g., luminosity, cancel. |
19 |
|
It does however introduce complications because it couples |
20 |
|
some of the uncertainties in non-trivial ways. For example, |
25 |
|
the $t\bar{t} \to$ dilepton BG estimate because it changes the |
26 |
|
$t\bar{t}$ normalization to the peak region (because some of the |
27 |
|
events in the peak region are from rare processes). These effects |
28 |
< |
are carefully accounted for. The contribution to the overall |
29 |
< |
uncertainty from each BG source is tabulated in |
28 |
> |
are carefully accounted for. The contribution to the overall |
29 |
> |
uncertainty from each background source is tabulated in |
30 |
|
Section~\ref{sec:bgunc-bottomline}. |
31 |
< |
First, however, we discuss the uncertainties one-by-one and we comment |
31 |
> |
Here we discuss the uncertainties one-by-one and comment |
32 |
|
on their impact on the overall result, at least to first order. |
33 |
|
Second order effects, such as the one described, are also included. |
34 |
|
|
37 |
|
These vary between 2\% and 20\%, depending on the signal region |
38 |
|
(different |
39 |
|
signal regions have different \met\ requirements, thus they also have |
40 |
< |
different $M_T$ regions used as control. |
40 |
> |
different $M_T$ regions used as control). |
41 |
|
Since |
42 |
< |
the major BG, eg, $t\bar{t}$ are normalized to the peak regions, this |
42 |
> |
the major backgrounds, eg, $t\bar{t}$ are normalized to the peak regions, this |
43 |
|
fractional uncertainty is pretty much carried through all the way to |
44 |
|
the end. There is also an uncertainty from the finite MC event counts |
45 |
|
in the $M_T$ peak regions. This is also included, but it is smaller. |
47 |
|
Normalizing to the $M_T$ peak has the distinct advantages that |
48 |
|
uncertainties on luminosity, cross-sections, trigger efficiency, |
49 |
|
lepton ID, cancel out. |
50 |
< |
For the low statistics regions with high \met requirements, the |
51 |
< |
price to pay in terms of event count statistical uncertainties starts |
50 |
> |
For the low statistics regions with high \met\ requirements, the |
51 |
> |
price to pay in terms of event count is that statistical uncertainties start |
52 |
|
to become significant. In the future we may consider a different |
53 |
|
normalization startegy in the low statistics regions. |
54 |
|
|
58 |
|
If the $M_T$ peak region is not well modelled, this would introduce an |
59 |
|
uncertainty. |
60 |
|
|
61 |
< |
We have tested this possibility by recalculating the post veto scale factors for a different |
61 |
> |
We have tested this possibility by recalculating the post-veto scale factors for a different |
62 |
|
choice |
63 |
|
of $M_T$ peak region ($40 < M_T < 100$ GeV instead of the default |
64 |
< |
$50 < M_T < 80$ GeV. This is shown in Table~\ref{tab:mtpeaksf2}. |
64 |
> |
$50 < M_T < 80$ GeV). This is shown in Table~\ref{tab:mtpeaksf2}. |
65 |
|
The two results for the scale factors are very compatible. |
66 |
|
We do not take any systematic uncertainty for this possible effect. |
67 |
|
|
111 |
|
\end{table} |
112 |
|
|
113 |
|
|
114 |
< |
\subsection{Uncertainty on the Wjets cross-section and the rare MC cross-sections} |
114 |
> |
\subsection{Uncertainty on the \wjets\ cross-section and the rare MC cross-sections} |
115 |
|
These are taken as 50\%, uncorrelated. |
116 |
|
The primary effect is to introduce a 50\% |
117 |
|
uncertainty |
125 |
|
scaled to the number of $t\bar{t}$ events in the peak, the $t\bar{t}$ |
126 |
|
BG goes down. |
127 |
|
|
128 |
< |
\subsection{Scale factors for the tail-to-peak ratios for lepton + |
128 |
> |
\subsection{Tail-to-peak ratios for lepton + |
129 |
|
jets top and W events} |
130 |
< |
These tail-to-peak ratios are described in Section~\ref{sec:ttp}. |
131 |
< |
They are studied in CR1 and CR2. The studies are described |
132 |
< |
in Sections~\ref{sec:cr1} and~\ref{sec:cr2}), respectively, where |
133 |
< |
we also give the uncertainty on the scale factors. See |
134 |
< |
Tables~\ref{tab:cr1yields} |
135 |
< |
and~\ref{tab:cr2yields}, scale factors $SFR_{wjet}$ and $SFR_{top})$. |
130 |
> |
The tail-to-peak ratios $R_{top}$ and $R_{wjet}$ are described in Section~\ref{sec:ttp}. |
131 |
> |
The data/MC scale factors are studied in CR1 and CR2 (Sections~\ref{sec:cr1} and~\ref{sec:cr2}). |
132 |
> |
Only the scale factor for \wjets, $SFR_{wjet}$, is used, and its |
133 |
> |
uncertainty is given in Table~\ref{tab:cr1yields}. |
134 |
> |
This uncertainty affects both $R_{wjet}$ and $R_{top}$. |
135 |
> |
The additional systematic uncertainty on $R_{top}$ from the variation between optimistic and pessimistic scenarios is given in Section~\ref{sec:ttp}. |
136 |
> |
|
137 |
|
|
138 |
|
\subsection{Uncertainty on extra jet radiation for dilepton |
139 |
|
background} |
143 |
|
dilepton MC is rescaled by the factors $K_3$ and $K_4$ to make |
144 |
|
it agree with the data. The 3\% uncertainties on $K_3$ and $K_4$ |
145 |
|
comes from data/MC statistics. This |
146 |
< |
result directly in a 3\% uncertainty on the dilepton BG, which is by far |
146 |
> |
results directly in a 3\% uncertainty on the dilepton background, which is by far |
147 |
|
the most important one. |
148 |
|
|
149 |
+ |
\subsection{Uncertainty from MC statistics} |
150 |
+ |
This affects mostly the \ttll\ background estimate, which is taken |
151 |
+ |
from |
152 |
+ |
Monte Carlo with appropriate correction factors. This uncertainty |
153 |
+ |
is negligible in the low \met\ signal regions, and grows to about |
154 |
+ |
15\% in SRG. |
155 |
|
|
149 |
– |
\subsection{Uncertainty on the \ttll\ Acceptance} |
156 |
|
|
157 |
+ |
\subsection{Uncertainty on the \ttll\ Background} |
158 |
+ |
\label{sec:ttdilbkgunc} |
159 |
|
The \ttbar\ background prediction is obtained from MC, with corrections |
160 |
|
derived from control samples in data. The uncertainty associated with |
161 |
< |
the theoretical modeling of the \ttbar\ production and decay is |
162 |
< |
estimated by comparing the background predictions obtained using |
161 |
> |
the \ttbar\ background is derived from the level of closure of the |
162 |
> |
background prediction in CR4 (Table~\ref{tab:cr4yields}) and |
163 |
> |
CR5 (Table~\ref{tab:cr5yields}). The results from these control region |
164 |
> |
checks are shown in Figure~\ref{fig:ttdlunc}. The uncertainties assigned |
165 |
> |
to the \ttdl\ background prediction based on these tests are |
166 |
> |
5\% (SRA), 10\% (SRB), 15\% (SRC), 25\% (SRD), 40\% (SRE-G). |
167 |
> |
|
168 |
> |
\begin{figure}[hbt] |
169 |
> |
\begin{center} |
170 |
> |
\includegraphics[width=0.6\linewidth]{plots/ttdilepton_uncertainty.pdf} |
171 |
> |
\caption{ |
172 |
> |
\label{fig:ttdlunc}%\protect |
173 |
> |
Results of the comparison of yields in the \mt\ tail comparing the MC prediction (after |
174 |
> |
applying SFs) to data for CR4 and CR5 for all the signal |
175 |
> |
region requirements considered (A-G). The bands indicate the |
176 |
> |
systematic uncertainties assigned based on these tests, |
177 |
> |
ranging from $5\%$ for SRA to $40\%$ for SRE-G.} |
178 |
> |
\end{center} |
179 |
> |
\end{figure} |
180 |
> |
|
181 |
> |
\clearpage |
182 |
> |
\subsubsection{Check of the impact of Signal Contamination} |
183 |
> |
|
184 |
> |
We examine the contribution of possible signal events in the \ttll\ |
185 |
> |
control regions (CR4 and CR5). It should be emphasized that these |
186 |
> |
regions are not used to apply data/MC SFs. They are used only to quantify |
187 |
> |
the level of data/MC agreement and assign a corresponding uncertainty. |
188 |
> |
As a result, if signal events were to populate these control regions |
189 |
> |
this would not lead to an increase in the predicted background. |
190 |
> |
|
191 |
> |
To illustrate how much signal is expected to populate these control |
192 |
> |
regions, we examine signal points near the edge of the analysis |
193 |
> |
sensitivity (m(stop) = 450 m($\chi^0$) = 0 for T2tt, m(stop) = 450 |
194 |
> |
m($\chi^0$) = 0, x=0.75 for T2bw) |
195 |
> |
Table~\ref{tab:signalcontamination} compares the expected signal |
196 |
> |
yields and the raw total MC background prediction in the control |
197 |
> |
regions with the \met\ and \mt\ requirements corresponding to SRB, SRC |
198 |
> |
and SRD (these are the signal regions that dominate the |
199 |
> |
sensitivity). The signal contamination is smaller than the uncertainty |
200 |
> |
on the dilepton background and smaller than the signal/background in |
201 |
> |
the signal regions. |
202 |
> |
Based on the fact that the CR4 and CR5 are not used to extract |
203 |
> |
data/MC scale factors and that we do not observe evidence for signal |
204 |
> |
contamination in these control regions (CR5, the control region with |
205 |
> |
larger statistical precision, actually shows a slight deficit of data w.r.t. MC), we |
206 |
> |
do not assign a correction for signal contamination in these control regions. |
207 |
> |
|
208 |
> |
\begin{table}[!h] |
209 |
> |
\begin{center} |
210 |
> |
{\small |
211 |
> |
\begin{tabular}{l l||c|c|c} |
212 |
> |
\hline |
213 |
> |
\multicolumn{2}{c||}{Sample} & CR B & CR C & CR D \\ |
214 |
> |
\hline |
215 |
> |
\hline |
216 |
> |
\multirow{4}{*}{CR4} & Raw MC & $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$ \\ |
217 |
> |
%\hline |
218 |
> |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $2.6 \pm 0.3$ $(2\%)$ & $2.0 \pm 0.2$ $(4\%)$ & $1.4 \pm 0.2$ $(7\%)$ \\ |
219 |
> |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $10.5 \pm 0.4$ $(6\%)$ &$6.1 \pm 0.3$ $(12\%)$ & $3.1 \pm 0.2$ $(16\%)$ \\ |
220 |
> |
\hline |
221 |
> |
\hline |
222 |
> |
\multirow{4}{*}{CR5} & Raw MC & $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$ \\ |
223 |
> |
%\hline |
224 |
> |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $10.6 \pm 0.6$ $(3\%)$ & $7.8 \pm 0.5$ $(8\%)$ & $5.4 \pm 0.4$ $(14\%)$ \\ |
225 |
> |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $17.3 \pm 0.5$ $(6\%)$ &$11.3 \pm 0.4$ $(11\%)$ & $6.2 \pm 0.3$ $(16\%)$\\ |
226 |
> |
\hline |
227 |
> |
\hline |
228 |
> |
\hline |
229 |
> |
\multirow{4}{*}{SIGNAL} & Raw MC & $486.3 \pm 7.8$& $164.3 \pm 4.5$& $61.5 \pm 2.8$ \\ |
230 |
> |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $65.3 \pm 1.4$ $(13\%)$& $48.8 \pm 1.2$ $(30\%)$& $32.9 \pm 1.0$ $(53\%)$ \\ |
231 |
> |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $69.3 \pm 1.0$ $(14\%)$& $47.3 \pm 0.8$ $(29\%)$& $27.3 \pm 0.6$ $(44\%)$ \\ |
232 |
> |
\hline |
233 |
> |
\end{tabular}} |
234 |
> |
\caption{ Yields in \mt\ tail comparing the raw SM MC prediction to the |
235 |
> |
yields for a few signal points on the edge of our sensitivity in the \ttll\ |
236 |
> |
control regions CR4, CR5 and in the corresponding signal region. |
237 |
> |
The numbers in parenthesis are the expected signal yield divided by |
238 |
> |
the total background. The uncertainties are statistical only. |
239 |
> |
\label{tab:signalcontamination}} |
240 |
> |
\end{center} |
241 |
> |
\end{table} |
242 |
> |
|
243 |
> |
%CR5 DUMP |
244 |
> |
%Total & $880.3 \pm 10.4$& $560.0 \pm 8.3$& $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$& $16.4 \pm 1.4$& $8.2 \pm 1.0$& $4.6 \pm 0.8$ \\ |
245 |
> |
%\hline |
246 |
> |
%\hline |
247 |
> |
%Data & $941$& $559$& $287$& $95$& $26$& $8$& $5$& $3$ \\ |
248 |
> |
%\hline |
249 |
> |
%T2tt m(stop) = 250 m($\chi^0$) = 0 & $84.3 \pm 9.2$& $61.9 \pm 7.9$& $35.7 \pm 6.0$& $5.9 \pm 2.4$& $1.0 \pm 1.0$& $1.0 \pm 1.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\ |
250 |
> |
%\hline |
251 |
> |
%T2tt m(stop) = 300 m($\chi^0$) = 50 & $61.4 \pm 4.7$& $53.6 \pm 4.4$& $42.0 \pm 3.9$& $14.3 \pm 2.3$& $7.2 \pm 1.6$& $1.8 \pm 0.8$& $0.7 \pm 0.5$& $0.0 \pm 0.0$ \\ |
252 |
> |
%\hline |
253 |
> |
%T2tt m(stop) = 300 m($\chi^0$) = 100 & $33.3 \pm 3.5$& $28.6 \pm 3.2$& $19.2 \pm 2.6$& $6.1 \pm 1.5$& $1.8 \pm 0.8$& $0.4 \pm 0.4$& $0.4 \pm 0.4$& $0.4 \pm 0.4$ \\ |
254 |
> |
%\hline |
255 |
> |
%T2tt m(stop) = 350 m($\chi^0$) = 0 & $33.4 \pm 2.2$& $29.8 \pm 2.1$& $27.3 \pm 2.0$& $15.3 \pm 1.5$& $5.6 \pm 0.9$& $1.9 \pm 0.5$& $0.3 \pm 0.2$& $0.0 \pm 0.0$ \\ |
256 |
> |
%\hline |
257 |
> |
%T2tt m(stop) = 450 m($\chi^0$) = 0 & $12.0 \pm 0.6$& $11.3 \pm 0.6$& $10.6 \pm 0.6$& $7.8 \pm 0.5$& $5.4 \pm 0.4$& $3.1 \pm 0.3$& $1.8 \pm 0.2$& $0.6 \pm 0.1$ \\ |
258 |
> |
%\hline |
259 |
> |
%T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0 & $48.5 \pm 1.9$& $40.2 \pm 1.7$& $33.0 \pm 1.5$& $14.4 \pm 1.0$& $5.7 \pm 0.6$& $2.7 \pm 0.4$& $1.3 \pm 0.3$& $0.5 \pm 0.2$ \\ |
260 |
> |
%\hline |
261 |
> |
%T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0 & $22.3 \pm 0.6$& $20.2 \pm 0.6$& $17.3 \pm 0.5$& $11.3 \pm 0.4$& $6.2 \pm 0.3$& $3.1 \pm 0.2$& $1.3 \pm 0.1$& $0.7 \pm 0.1$ \\ |
262 |
> |
%\hline |
263 |
> |
|
264 |
> |
%CR4 DUMP |
265 |
> |
%\hline |
266 |
> |
%Total & $510.1 \pm 8.0$& $324.2 \pm 6.3$& $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$& $7.8 \pm 1.0$& $2.6 \pm 0.6$& $1.1 \pm 0.3$ \\ |
267 |
> |
%\hline |
268 |
> |
%\hline |
269 |
> |
%Data & $462$& $289$& $169$& $45$& $10$& $7$& $5$& $3$ \\ |
270 |
> |
%\hline |
271 |
> |
%T2tt m(stop) = 250 m($\chi^0$) = 0 & $37.7 \pm 6.1$& $30.9 \pm 5.5$& $18.0 \pm 4.2$& $6.0 \pm 2.5$& $2.0 \pm 1.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\ |
272 |
> |
%\hline |
273 |
> |
%T2tt m(stop) = 300 m($\chi^0$) = 50 & $16.6 \pm 2.4$& $14.4 \pm 2.3$& $11.3 \pm 2.0$& $5.6 \pm 1.4$& $3.2 \pm 1.1$& $1.8 \pm 0.8$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\ |
274 |
> |
%\hline |
275 |
> |
%T2tt m(stop) = 300 m($\chi^0$) = 100 & $9.6 \pm 1.8$& $6.4 \pm 1.5$& $4.6 \pm 1.3$& $0.7 \pm 0.5$& $0.4 \pm 0.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\ |
276 |
> |
%\hline |
277 |
> |
%T2tt m(stop) = 350 m($\chi^0$) = 0 & $8.2 \pm 1.1$& $7.6 \pm 1.0$& $5.7 \pm 0.9$& $3.4 \pm 0.7$& $1.9 \pm 0.5$& $0.6 \pm 0.3$& $0.3 \pm 0.2$& $0.1 \pm 0.1$ \\ |
278 |
> |
%\hline |
279 |
> |
%T2tt m(stop) = 450 m($\chi^0$) = 0 & $3.1 \pm 0.3$& $2.9 \pm 0.3$& $2.6 \pm 0.3$& $2.0 \pm 0.2$& $1.4 \pm 0.2$& $1.0 \pm 0.2$& $0.4 \pm 0.1$& $0.2 \pm 0.1$ \\ |
280 |
> |
%\hline |
281 |
> |
%T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0 & $52.6 \pm 1.9$& $42.6 \pm 1.7$& $32.1 \pm 1.5$& $14.7 \pm 1.0$& $5.5 \pm 0.6$& $1.9 \pm 0.4$& $0.6 \pm 0.2$& $0.3 \pm 0.1$ \\ |
282 |
> |
%\hline |
283 |
> |
%T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0 & $16.9 \pm 0.5$& $14.9 \pm 0.5$& $10.5 \pm 0.4$& $6.1 \pm 0.3$& $3.1 \pm 0.2$& $1.5 \pm 0.1$& $0.6 \pm 0.1$& $0.3 \pm 0.1$ \\ |
284 |
> |
%\hline |
285 |
> |
|
286 |
> |
|
287 |
> |
\subsubsection{Check of the uncertainty on the \ttll\ Background} |
288 |
> |
|
289 |
> |
We check that the systematic uncertainty assigned to the \ttll\ background prediction |
290 |
> |
covers the uncertainty associated with |
291 |
> |
the theoretical modeling of the \ttbar\ production and decay |
292 |
> |
by comparing the background predictions obtained using |
293 |
|
alternative MC samples. It should be noted that the full analysis is |
294 |
|
performed with the alternative samples under consideration, |
295 |
|
including the derivation of the various data-to-MC scale factors. |
297 |
|
|
298 |
|
\begin{itemize} |
299 |
|
\item Top mass: The alternative values for the top mass differ |
300 |
< |
from the central value by $5~\GeV$: $m_{\mathrm{top}} = 178.5~\GeV$ and $m_{\mathrm{top}} |
300 |
> |
from the central value by $6~\GeV$: $m_{\mathrm{top}} = 178.5~\GeV$ and $m_{\mathrm{top}} |
301 |
|
= 166.5~\GeV$. |
302 |
|
\item Jet-parton matching scale: This corresponds to variations in the |
303 |
|
scale at which the Matrix Element partons from Madgraph are matched |
314 |
|
Tauola and is otherwise identical to the Powheg sample. |
315 |
|
This effect was studied earlier using 7~TeV samples and found to be negligible. |
316 |
|
\item The PDF uncertainty is estimated following the PDF4LHC |
317 |
< |
recommendations[CITE]. The events are reweighted using alternative |
317 |
> |
recommendations. The events are reweighted using alternative |
318 |
|
PDF sets for CT10 and MSTW2008 and the uncertainties for each are derived using the |
319 |
< |
alternative eigenvector variations and the ``master equation''. In |
320 |
< |
addition, the NNPDF2.1 set with 100 replicas. The central value is |
319 |
> |
alternative eigenvector variations and the ``master equation''. |
320 |
> |
The NNPDF2.1 set with 100 replicas is also used. The central value is |
321 |
|
determined from the mean and the uncertainty is derived from the |
322 |
|
$1\sigma$ range. The overall uncertainty is derived from the envelope of the |
323 |
|
alternative predictions and their uncertainties. |
385 |
|
statistics. |
386 |
|
\item Within the limited statistics, there is no evidence that the |
387 |
|
situation changes as we go from signal region A to signal region E. |
388 |
< |
Therefore, we assess a systematic based on the relatively high |
389 |
< |
statistics |
390 |
< |
test in signal region A, and apply the same systematic uncertainty |
391 |
< |
to all other regions. |
388 |
> |
%Therefore, we assess a systematic based on the relatively high |
389 |
> |
%statistics |
390 |
> |
%test in signal region A, and apply the same systematic uncertainty |
391 |
> |
%to all other regions. |
392 |
> |
\item In signal regions B and above, the uncertainties assigned in Section~\ref{sec:ttdilbkgunc} |
393 |
> |
fully cover the alternative MC variations. |
394 |
|
\item In order to fully (as opposed as 1$\sigma$) cover the |
395 |
|
alternative MC variations in region A we would have to take a |
396 |
|
systematic |
397 |
< |
uncertainty of $\approx 10\%$. This would be driven by the |
397 |
> |
uncertainty of $\approx 10\%$ instead of $5\%$. This would be driven by the |
398 |
|
scale up/scale down variations, see Table~\ref{tab:fracdiff}. |
399 |
|
\end{itemize} |
400 |
|
|
428 |
|
These are described below. |
429 |
|
|
430 |
|
The first piece of information is that the jet multiplicity in the scale |
431 |
< |
up/scale down sample is the most inconsistent with the data. This can be shown |
431 |
> |
up/scale down sample is the most inconsistent with the data. This is shown |
432 |
|
in Table~\ref{tab:njetskfactors_met100}, where we tabulate the |
433 |
< |
$K_3$ and $K_4$ factors of Section~\ref{tab:njetskfactors_met100} for |
433 |
> |
$K_3$ and $K_4$ factors of Section~\ref{sec:jetmultiplicity} for |
434 |
|
different \ttbar\ MC samples. The data/MC disagreement in the $N_{jets}$ |
435 |
|
distribution |
436 |
|
for the scale up/scale down samples is also shown in Fig.~\ref{fig:dileptonnjets_scaleup} |
491 |
|
up/scale |
492 |
|
down variations by a factor 2, we can see that a systematic |
493 |
|
uncertainty |
494 |
< |
of 6\% would fully cover all of the variations from different MC |
495 |
< |
samples in SRA and SRB. |
496 |
< |
{\bf Thus, we take a 6\% systematic uncertainty, constant as a |
497 |
< |
function of signal region, as the systematic due to alternative MC |
498 |
< |
models.}. |
499 |
< |
Note that this 6\% is also consistent with the level at which we are |
500 |
< |
able |
501 |
< |
to test the closure of the method in CR5 for the high statistics |
502 |
< |
regions |
503 |
< |
(Table~\ref{tab:hugecr5yields}). |
504 |
< |
|
494 |
> |
of 5\% covers the range of reasonable variations from different MC |
495 |
> |
models in SRA and SRB. |
496 |
> |
%The alternative MC models indicate that a 6\% systematic uncertainty |
497 |
> |
%covers the range of reasonable variations. |
498 |
> |
Note that this 5\% is also consistent with the level at which we are |
499 |
> |
able to test the closure of the method with alternative samples in CR5 for the high statistics |
500 |
> |
regions (Table~\ref{tab:hugecr5yields}). |
501 |
> |
The range of reasonable variations obtained with the alternative |
502 |
> |
samples are consistent with the uncertainties assigned for |
503 |
> |
the \ttll\ background based on the closure of the background |
504 |
> |
predictions and data in CR4 and CR5. |
505 |
|
|
506 |
|
|
507 |
|
|
732 |
|
$P_T > 10$ GeV in $|\eta| < 2.4$. This fraction is about 1/3, see |
733 |
|
Table~\ref{tab:trueisotrk}. |
734 |
|
The uncertainty for these events |
735 |
< |
is 6\% and is obtained from Tag and Probe studies of Section~\ref{sec:trkveto} |
735 |
> |
is 6\% and is obtained from tag-and-probe studies, see Section~\ref{sec:trkveto}. |
736 |
|
|
737 |
|
\begin{table}[!h] |
738 |
|
\begin{center} |
781 |
|
Second, hadronic tracks may undergo nuclear interactions and hence their tracks may not be reconstructed. |
782 |
|
As discussed above, independent studies show that the MC reproduces the hadronic tracking efficiency within 4\%, |
783 |
|
leading to a total background uncertainty of less than 0.5\% (after taking into account the fraction of the total background |
784 |
< |
due to hadronic $\tau$ decays with \pt\ $>$ 10 GeV tracks), and we hence regard this effect as neglgigible. |
784 |
> |
due to hadronic $\tau$ decays with \pt\ $>$ 10 GeV tracks), and we hence regard this effect as negligible. |
785 |
|
|
786 |
|
The tag-and-probe studies are performed in the full data sample, and compared with the DYJets madgraph sample. |
787 |
|
All events must contain a tag-probe pair (details below) with opposite-sign and satisfying the Z mass requirement 76--106 GeV. |
838 |
|
The absolute track isolation distributions for passing probes are displayed in Fig.~\ref{fig:tnp}. In general we observe |
839 |
|
good agreement between data and MC. To be more quantitative, we compare the data vs. MC efficiencies to satisfy |
840 |
|
absolute track isolation requirements varying from $>$ 1 GeV to $>$ 5 GeV, as summarized in Table~\ref{tab:isotrk}. |
841 |
< |
In the $\geq$0 and $\geq$1 jet bins where the efficiencies can be tested with statistical precision, the data and MC |
841 |
> |
In the $\geq 0$ and $\geq 1$ jet bins where the efficiencies can be tested with statistical precision, the data and MC |
842 |
|
efficiencies agree within 6\%, and we apply this as a systematic uncertainty on the isolated track veto efficiency. |
843 |
|
For the higher jet multiplicity bins the statistical precision decreases, but we do not observe any evidence for |
844 |
|
a data vs. MC discrepancy in the isolated track veto efficiency. |
871 |
|
|
872 |
|
\begin{table}[!ht] |
873 |
|
\begin{center} |
734 |
– |
\caption{\label{tab:isotrk} Comparison of the data vs. MC efficiencies to satisfy the indicated requirements |
735 |
– |
on the absolute track isolation, and the ratio of these two efficiencies. Results are indicated separately for electrons and muons and for various |
736 |
– |
jet multiplicity requirements.} |
874 |
|
\begin{tabular}{l|c|c|c|c|c} |
875 |
|
|
876 |
|
%Electrons: |
968 |
|
\hline |
969 |
|
|
970 |
|
\end{tabular} |
971 |
+ |
\caption{\label{tab:isotrk} Comparison of the data vs. MC efficiencies to satisfy the indicated requirements |
972 |
+ |
on the absolute track isolation, and the ratio of these two efficiencies. Results are indicated separately for electrons and muons and for various |
973 |
+ |
jet multiplicity requirements.} |
974 |
|
\end{center} |
975 |
|
\end{table} |
976 |
|
|
977 |
+ |
\clearpage |
978 |
+ |
\subsection{Summary of uncertainties} |
979 |
+ |
\label{sec:bgunc-bottomline} |
980 |
+ |
|
981 |
+ |
The contribution from each source to the total uncertainty on the background yield is given in Tables~\ref{tab:relativeuncertaintycomponents} and~\ref{tab:uncertaintycomponents} for the relative and absolute uncertainties, respectively. In the low-\met\ regions the dominant uncertainty comes from the top tail-to-peak ratio, $R_{top}$ (Section~\ref{sec:ttp}), while in the high-\met\ regions the \ttll\ systematic uncertainty dominates (Section~\ref{sec:ttdilbkgunc}). |
982 |
+ |
|
983 |
+ |
\input{uncertainties_table.tex} |
984 |
+ |
|
985 |
+ |
|
986 |
+ |
|
987 |
+ |
|
988 |
|
|
989 |
|
%Figure.~\ref{fig:reliso} compares the relative track isolation |
990 |
|
%for events with a track with $\pt > 10~\GeV$ in addition to a selected |
1066 |
|
% \end{center} |
1067 |
|
%\end{figure} |
1068 |
|
|
1069 |
< |
% \subsection{Summary of uncertainties} |
919 |
< |
% \label{sec:bgunc-bottomline}. |
1069 |
> |
|
1070 |
|
|
1071 |
|
% THIS NEEDS TO BE WRITTEN |