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Revision 1.23 by benhoob, Fri Nov 19 17:08:29 2010 UTC

# Line 1 | Line 1
1 < \clearpage
1 > %\clearpage
2  
3   \section{Results}
4   \label{sec:results}
# Line 23 | Line 23 | The Standard Model MC expectation is 1.4
23  
24   The data yields in the
25   four regions are summarized in Table~\ref{tab:datayield}.
26 < The prediction of the ABCD method is is given by $A\times C/B$ and
27 < is $1.5 \pm 0.9(stat) \pm 0.2(syst)$ events, as shown in Table~\ref{tab:datayield}.  
26 > The prediction of the ABCD method is is given by $k_{ABCD} \times (A\times C/B)$ and
27 > is $1.8 \pm 1.0(stat) \pm 0.4(syst)$ events, where $k_{ABCD} = 1.2 \pm 0.2$ as discussed
28 > in Sec.~\ref{sec:abcd}.
29  
30   \begin{table}[hbt]
31   \begin{center}
# Line 49 | Line 50 | $W^{\pm}$ + jets
50   \hline
51      total SM MC                          &           8.63   &          36.85   &           5.07   &           1.43   &           1.19  \\
52   \hline
53 <           data                          &             11   &             36   &              5   &              1   &  $1.53 \pm 0.86(stat) \pm 0.15(syst)$  \\
53 >           data                          &             11   &             36   &              5   &              1   &  $1.53 \pm 0.86$  \\
54   \hline
55   \end{tabular}
56   \end{center}
# Line 61 | Line 62 | $W^{\pm}$ + jets
62   %estimate of the $t\bar{t}$ contribution.  The result
63   %of this exercise is {\color{red} xx} events.
64  
65 < \clearpage
65 > %\clearpage
66  
67   \subsection{Background estimate from the $P_T(\ell\ell)$ method}
68   \label{sec:victoryres}
69  
70   We first use the $P_T(\ell \ell)$ method to predict the number of events
71   in control region A, defined in Sec.~\ref{sec:abcd} as
72 < $125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5.
72 > $125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5~GeV$^{1/2}$.
73   We count the number of events in region
74   $A'$, defined in Sec.~\ref{sec:othBG} by replacing the above $\met/\sqrt{\rm SumJetPt}$
75   cut with the same cut on the quantity $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$,
# Line 117 | Line 118 | ${P_T(\ell\ell)}/\sqrt{\rm SumJetPt}$ in
118   \begin{table}[hbt]
119   \begin{center}
120   \caption{\label{tab:victory_control}Results of the dilepton $p_{T}$ template method in the control region
121 < $125 < \mathrm{sumJetPt} < 300$~GeV. The predicted and observed yields for
121 > $125 < \mathrm{sumJetPt} < 300$~GeV$^{1/2}$. The predicted and observed yields for
122   the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
123   and MC. The error on the prediction for data is statistical only, assuming
124   Gaussian errors.}
# Line 135 | Line 136 | total SM   MC &      7.18           &
136   \begin{table}[hbt]
137   \begin{center}
138   \caption{\label{tab:victory_signal}Results of the dilepton $p_{T}$ template method in the signal region
139 < $\mathrm{sumJetPt} > 300$~GeV. The predicted and observed yields for
139 > $\mathrm{sumJetPt} > 300$~GeV$^{1/2}$. The predicted and observed yields for
140   the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
141   and MC. The error on the prediction for data is statistical only, assuming
142   Gaussian errors.}
# Line 151 | Line 152 | total SM   MC &      1.03
152   \end{table}
153  
154  
155 + % \clearpage
156   \subsection{Summary of results}
157 < To summarize: we see no evidence for an anomalous
157 >
158 > In summary, in the signal region defined as $\mathrm{SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt} > 8.5$~GeV$^{1/2}$:\\
159 > We observe 1 event. \\
160 > We expect 1.4 events from Standard Model MC prediction. \\
161 > The ABCD data driven method predicts $1.8 \pm 1.0(stat) \pm 0.4(syst)$ events. \\
162 > The  $P_T(\ell\ell)$ method predicts $2.5 \pm 2.2$ events.
163 >  
164 > All three background estimates are consistent within their uncertainties.
165 > We thus take as our best estimate of the Standard Model yield in
166 > the signal region the MC prediction and assign as an uncertainty the
167 > maximal deviation with either of the data-driven methods,  $N_{BG}=1.4 \pm 1.1$.
168 >
169 > We conclude that we see no evidence for an anomalous
170   rate of opposite sign isolated dilepton events
171   at high \met and high SumJetPt.  The extraction of
172   quantitative limits on new physics models is discussed

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