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1   \section{Results}
2   \label{sec:results}
3  
4 < The data, together with SM expectations is presented
5 < in Figure~\ref{fig:abcdData}.  The data yields in the
6 < four regions are summarized in Table~\ref{tab:datayield}.
7 <
8 <
4 > %\noindent {\color{red} In the 11 pb everything is very
5 > %simple because there are a few zeros.  This text is written
6 > %for the full dataset under the assumption that some of these
7 > %numbers will not be zero anymore.}
8  
9   \begin{figure}[tbh]
10   \begin{center}
# Line 17 | Line 16 | show our choice of ABCD regions.}
16   \end{figure}
17  
18  
19 + The data, together with SM expectations is presented
20 + in Figure~\ref{fig:abcdData}.  We see $\color{red} 0$
21 + events in the signal region (region $D$).  The Standard Model
22 + MC expectation is {\color{red} 0.4} events.
23 +
24 + \subsection{Background estimate from the ABCD method}
25 + \label{sec:abcdres}
26 +
27 + The data yields in the
28 + four regions are summarized in Table~\ref{tab:datayield}.
29 + The prediction of the ABCD method is is given by $AC/B$ and
30 + is 0.5 events.
31 + (see Table~\ref{tab:datayield}.  
32 +
33   \begin{table}[hbt]
34   \begin{center}
35   \caption{\label{tab:datayield} Data yields in the four
# Line 24 | Line 37 | regions of Figure~\ref{fig:abcdData}.  W
37   SM Monte Carlo expectations.}
38   \begin{tabular}{|l|c|c|c|c||c|}
39   \hline
40 <      &A   & B    & C   & D   & AC/D \\ \hline
40 >      &A   & B    & C   & D   & AC/B \\ \hline
41   Data  &3   & 6    & 1   & 0   & $0.5^{+x}_{-y}$ \\
42   SM MC &2.5 &11.2  & 1.5 & 0.4 & 0.4 \\
43   \hline
# Line 32 | Line 45 | SM MC &2.5 &11.2  & 1.5 & 0.4 & 0.4 \\
45   \end{center}
46   \end{table}
47  
48 + %As a cross-check, we can subtract from the yields in
49 + %Table~\ref{tab:datayield} the expected DY contributions
50 + %from Table~\ref{tab:ABCD-DY} in order to get a ``purer''
51 + %estimate of the $t\bar{t}$ contribution.  The result
52 + %of this exercise is {\color{red} xx} events.
53 +
54 + \subsection{Background estimate from the $P_T(\ell\ell)$ method}
55 + \label{sec:victoryres}
56 +
57 +
58 + {\color{red}As mentioned previously, for the 11/pb analysis
59 + we use the $K$ factor from data and take $K_{\rm fudge}=1$.
60 + This will change for the full dataset.  We will also pay
61 + more attention to the statistical errors.}
62 +
63 + The number of data events in region $D'$, which is defined in
64 + Section~\ref{sec:othBG} to be the same as region $D$ but with the
65 + $\met/\sqrt{\rm SumJetPt}$ requirement
66 + replaced by a $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$ requirement
67 + is $N_{D'}=1$.  Thus the BG prediction is
68 + $N_D = K \cdot K_{\rm fudge} \cdot N_{D'} = 1.5$
69 + where we used $K=1.5 \pm xx$ and $K_{\rm fudge}=1.0 \pm 0.0$.
70 + Note that if we were to subtract off from region $D'$
71 + the {\color{red} 0.4 $\pm$ 0.4} DY events estimated from
72 + Section~\ref{sec:othBG}, the background
73 + prediction would change to $N_D=0.9 \pm xx$ events.
74 + {\color{red} When we do this with a real
75 + $K_{\rm fudge}$, the fudge factor will be different
76 + after the DY subtraction.}
77  
78 < There are
37 < zero events in the signal region (region D).
38 < As mentioned in Section~\ref{sec}, the number
39 < of SM events expected events from Monte Carlo is 0.4.
40 < The prediction of the ABCD method is 0.5
41 < (see Table~\ref{tab:datayield}.  There are no events
42 < in the data in region D when $P_T(\ell \ell)$ is
43 < substituted for \met; thus the $P_T(\ell \ell)$
44 < method predicts a background of $0^{+x.x}_{-0.0}$
45 < events.  As a cross-check, we use the $P_T(\ell \ell)$
78 > As a cross-check, we use the $P_T(\ell \ell)$
79   method to also predict the number of events in the
80   control region $120<{\rm SumJetPt}<300$ GeV and
81   \met/$\sqrt{\rm SumJetPt} > 8.5$.  We predict
82   $5.6^{+x}_{-y}$ events and we observe 4.
83 < {\color{red} (We need to make sure that this prediction
84 < includes the 1.4 fudge factor).}
83 > The results of the $P_T(\ell\ell)$ method are
84 > summarized in Figure~\ref{fig:victory}.
85 >
86 > \begin{figure}[hbt]
87 > \begin{center}
88 > \includegraphics[width=0.48\linewidth]{victory_control.png}
89 > \includegraphics[width=0.48\linewidth]{victory_sig.png}
90 > \caption{\label{fig:victory}\protect Distributions of
91 > tcMet/$\sqrt{\rm SumJetPt}$ for the control and signal region.
92 > We show the oberved distributions in both Monte Carlo and data.
93 > We also show the distributions predicted from
94 > tcMet/$\sqrt{P_T(\ell\ell)}$ in both MC and data.}
95 > \end{center}
96 > \end{figure}
97 >
98  
99 + \subsection{Summary of results}
100   To summarize: we see no evidence for an anomalous
101   rate of opposite sign isolated dilepton events
102   at high \met and high SumJetPt.  The extraction of

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