| 129 |
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jets top and W events} |
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|
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 uncertainty is given in Table~\ref{tab:cr1yields}). This uncertainty affects both $R_{wjet}$ and $R_{top}$. |
| 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 |
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|
| 155 |
|
|
| 156 |
|
|
| 157 |
|
\subsection{Uncertainty on the \ttll\ Background} |
| 158 |
< |
|
| 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 \ttbar\ background is derived from the level of closure of the |
| 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\ Acceptance} |
| 287 |
> |
\subsubsection{Check of the uncertainty on the \ttll\ Background} |
| 288 |
|
|
| 289 |
< |
The uncertainty associated with |
| 290 |
< |
the theoretical modeling of the \ttbar\ production and decay is |
| 291 |
< |
checked by comparing the background predictions obtained using |
| 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. |
| 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 |
|
|
| 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 |
< |
The alternative MC models indicate that a 6\% systematic uncertainty to |
| 497 |
< |
cover the range of reasonable variations. |
| 498 |
< |
Note that this 6\% is also consistent with the level at which we are |
| 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 |
| 976 |
|
|
| 977 |
|
\clearpage |
| 978 |
|
\subsection{Summary of uncertainties} |
| 979 |
< |
\label{sec:bgunc-bottomline}. |
| 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 |
| 991 |
|
%muon for $\Z+4$ jet events and various \ttll\ components. The |
