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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}. We see 1 event in the |
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signal region (region $D$). The Standard Model MC |
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expectation is 1.4 events. |
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signal region (region $D$). For more information about |
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this one candidate events, see Appendix~\ref{sec:cand}. |
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The Standard Model MC expectation is 1.4 events. |
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\subsection{Background estimate from the ABCD method} |
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\label{sec:abcdres} |
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The data yields in the |
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four regions are summarized in Table~\ref{tab:datayield}. |
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The prediction of the ABCD method is is given by $A\times C/B$ and |
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is 1.5 $\pm$ 0.9 events (statistical uncertainty only, assuming |
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Gaussian errors), as shown in Table~\ref{tab:datayield}. |
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The prediction of the ABCD method is is given by $k_{ABCD} \times (A\times C/B)$ and |
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is $1.8 \pm 1.0(stat) \pm 0.4(syst)$ events, where $k_{ABCD} = 1.2 \pm 0.2$ as discussed |
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in Sec.~\ref{sec:abcd}. |
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\begin{table}[hbt] |
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\begin{center} |
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\hline |
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total SM MC & 8.63 & 36.85 & 5.07 & 1.43 & 1.19 \\ |
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\hline |
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data & 11 & 36 & 5 & 1 & $1.53\pm0.86$ \\ |
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data & 11 & 36 & 5 & 1 & $1.53 \pm 0.86$ \\ |
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\hline |
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\end{tabular} |
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\end{center} |
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%estimate of the $t\bar{t}$ contribution. The result |
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%of this exercise is {\color{red} xx} events. |
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\subsection{Background estimate from the $P_T(\ell\ell)$ method} |
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\label{sec:victoryres} |
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We first use the $P_T(\ell \ell)$ method to predict the number of events |
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in control region A, defined in Sec.~\ref{sec:abcd} as |
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$125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5. |
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$125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5~GeV$^{1/2}$. |
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We count the number of events in region |
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$A'$, defined in Sec.~\ref{sec:othBG} by replacing the above $\met/\sqrt{\rm SumJetPt}$ |
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cut with the same cut on the quantity $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$, |
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\begin{table}[hbt] |
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\begin{center} |
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\caption{\label{tab:victory_control}Results of the dilepton $p_{T}$ template method in the control region |
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$125 < \mathrm{sumJetPt} < 300$~GeV. The predicted and observed yields for |
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$125 < \mathrm{sumJetPt} < 300$~GeV$^{1/2}$. The predicted and observed yields for |
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the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data |
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and MC. The error on the prediction for data is statistical only, assuming |
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Gaussian errors.} |
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& Predicted & Observed & Obs/Pred \\ |
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\hline |
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total SM MC & 7.18 & 8.63 & 1.20 \\ |
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data & $6.06 \pm 5.95$ & 11 & 1.06 \\ |
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data & $6.06 \pm 5.95$ & 11 & 1.82 \\ |
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\hline |
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\end{tabular} |
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\end{center} |
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\begin{table}[hbt] |
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\begin{center} |
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\caption{\label{tab:victory_signal}Results of the dilepton $p_{T}$ template method in the signal region |
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$\mathrm{sumJetPt} > 300$~GeV. The predicted and observed yields for |
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$\mathrm{sumJetPt} > 300$~GeV$^{1/2}$. The predicted and observed yields for |
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the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data |
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and MC. The error on the prediction for data is statistical only, assuming |
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Gaussian errors.} |
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\end{table} |
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\subsection{Summary of results} |
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To summarize: we see no evidence for an anomalous |
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In summary, in the signal region defined as $\mathrm{SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt} > 8.5$~GeV$^{1/2}$:\\ |
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We observe 1 event. \\ |
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We expect 1.4 events from Standard Model MC prediction. \\ |
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The ABCD data driven method predicts $1.8 \pm 1.0(stat) \pm 0.4(syst)$ events. \\ |
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The $P_T(\ell\ell)$ method predicts $2.5 \pm 2.2$ events. |
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All three background estimates are consistent within their uncertainties. |
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We thus take as our best estimate of the Standard Model yield in |
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the signal region the MC prediction and assign as an uncertainty the |
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maximal deviation with either of the data-driven methods, $N_{BG}=1.4 \pm 1.1$. |
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We conclude that 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 |
