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Revision 1.18 by benhoob, Mon Nov 15 10:18:23 2010 UTC vs.
Revision 1.22 by claudioc, Tue Nov 16 12:23:36 2010 UTC

# Line 1 | Line 1
1 < \clearpage
1 > %\clearpage
2  
3   \section{Results}
4   \label{sec:results}
# Line 49 | Line 49 | $W^{\pm}$ + jets
49   \hline
50      total SM MC                          &           8.63   &          36.85   &           5.07   &           1.43   &           1.19  \\
51   \hline
52 <           data                          &             11   &             36   &              5   &              1   &  $1.53 \pm 0.86(stat) \pm 0.15(syst)$  \\
52 >           data                          &             11   &             36   &              5   &              1   &  $1.53 \pm 0.86$  \\
53   \hline
54   \end{tabular}
55   \end{center}
# Line 61 | Line 61 | $W^{\pm}$ + jets
61   %estimate of the $t\bar{t}$ contribution.  The result
62   %of this exercise is {\color{red} xx} events.
63  
64 < \clearpage
64 > %\clearpage
65  
66   \subsection{Background estimate from the $P_T(\ell\ell)$ method}
67   \label{sec:victoryres}
68  
69   We first use the $P_T(\ell \ell)$ method to predict the number of events
70   in control region A, defined in Sec.~\ref{sec:abcd} as
71 < $125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5.
71 > $125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5~GeV$^{1/2}$.
72   We count the number of events in region
73   $A'$, defined in Sec.~\ref{sec:othBG} by replacing the above $\met/\sqrt{\rm SumJetPt}$
74   cut with the same cut on the quantity $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$,
# Line 117 | Line 117 | ${P_T(\ell\ell)}/\sqrt{\rm SumJetPt}$ in
117   \begin{table}[hbt]
118   \begin{center}
119   \caption{\label{tab:victory_control}Results of the dilepton $p_{T}$ template method in the control region
120 < $125 < \mathrm{sumJetPt} < 300$~GeV. The predicted and observed yields for
120 > $125 < \mathrm{sumJetPt} < 300$~GeV$^{1/2}$. The predicted and observed yields for
121   the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
122   and MC. The error on the prediction for data is statistical only, assuming
123   Gaussian errors.}
# Line 135 | Line 135 | total SM   MC &      7.18           &
135   \begin{table}[hbt]
136   \begin{center}
137   \caption{\label{tab:victory_signal}Results of the dilepton $p_{T}$ template method in the signal region
138 < $\mathrm{sumJetPt} > 300$~GeV. The predicted and observed yields for
138 > $\mathrm{sumJetPt} > 300$~GeV$^{1/2}$. The predicted and observed yields for
139   the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
140   and MC. The error on the prediction for data is statistical only, assuming
141   Gaussian errors.}
# Line 151 | Line 151 | total SM   MC &      1.03
151   \end{table}
152  
153  
154 + % \clearpage
155   \subsection{Summary of results}
156 < To summarize: we see no evidence for an anomalous
156 >
157 > In summary, in the signal region defined as $\mathrm{SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt} > 8.5$~GeV$^{1/2}$:\\
158 > We observe 1 event. \\
159 > We expect 1.4 events from Standard Model MC prediction. \\
160 > The ABCD data driven method predicts $1.5 \pm 0.9(stat) \pm 0.2(syst)$ events. \\
161 > The  $P_T(\ell\ell)$ method predicts $2.5 \pm 2.2$ events.
162 >  
163 > All three background estimates are consistent within their uncertainties.
164 > We thus take as our best estimate of the Standard Model yield in
165 > the signal region the MC prediction and assign as an uncertainty the
166 > maximal deviation with either of the data-driven methods,  $N_{BG}=1.4 \pm 1.1$.
167 >
168 > We conclude that we see no evidence for an anomalous
169   rate of opposite sign isolated dilepton events
170   at high \met and high SumJetPt.  The extraction of
171   quantitative limits on new physics models is discussed

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