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\section{Results}
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\label{sec:results}
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The data, together with SM expectations is presented
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in Figure~\ref{fig:abcdData}. The data yields in the
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four regions are summarized in Table~\ref{tab:datayield}.
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\begin{figure}[tbh]
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\begin{center}
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\includegraphics[width=0.75\linewidth]{abcdData.png}
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\caption{\label{fig:abcdData}\protect Distributions of SumJetPt
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vs. MET$/\sqrt{\rm SumJetPt}$ for SM Monte Carlo and data. Here we also
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show our choice of ABCD regions.}
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\end{center}
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\end{figure}
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\begin{table}[hbt]
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\begin{center}
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\caption{\label{tab:datayield} Data yields in the four
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regions of Figure~\ref{fig:abcdData}. We also show the
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SM Monte Carlo expectations.}
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\begin{tabular}{|l|c|c|c|c||c|}
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\hline
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&A & B & C & D & AC/D \\ \hline
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Data &3 & 6 & 1 & 0 & $0.5^{+x}_{-y}$ \\
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SM MC &2.5 &11.2 & 1.5 & 0.4 & 0.4 \\
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\hline
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\end{tabular}
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\end{center}
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\end{table}
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There are
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zero events in the signal region (region D).
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As mentioned in Section~\ref{sec}, the number
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of SM events expected events from Monte Carlo is 0.4.
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The prediction of the ABCD method is 0.5
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(see Table~\ref{tab:datayield}. There are no events
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in the data in region D when $P_T(\ell \ell)$ is
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substituted for \met; thus the $P_T(\ell \ell)$
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method predicts a background of $0^{+x.x}_{-0.0}$
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events. As a cross-check, we use the $P_T(\ell \ell)$
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method to also predict the number of events in the
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control region $120<{\rm SumJetPt}<300$ GeV and
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\met/$\sqrt{\rm SumJetPt} > 8.5$. We predict
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$5.6^{+x}_{-y}$ events and we observe 4.
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{\color{red} (We need to make sure that this prediction
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includes the 1.4 fudge factor).}
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To summarize: we see no evidence for an anomalous
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rate of opposite sign isolated dilepton events
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at high \met and high SumJetPt. The extraction of
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quantitative limits on new physics models is discussed
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in Section~\ref{sec:limits}. |
