| 1 |
\clearpage
|
| 2 |
|
| 3 |
\section{Results}
|
| 4 |
\label{sec:results}
|
| 5 |
|
| 6 |
\begin{figure}[tbh]
|
| 7 |
\begin{center}
|
| 8 |
\includegraphics[width=0.75\linewidth]{abcd_35pb.png}
|
| 9 |
\caption{\label{fig:abcdData}\protect Distributions of SumJetPt
|
| 10 |
vs. MET$/\sqrt{\rm SumJetPt}$ for SM Monte Carlo and data. Here we also
|
| 11 |
show our choice of ABCD regions.}
|
| 12 |
\end{center}
|
| 13 |
\end{figure}
|
| 14 |
|
| 15 |
The data, together with SM expectations is presented
|
| 16 |
in Figure~\ref{fig:abcdData}. We see 1 event in the
|
| 17 |
signal region (region $D$). The Standard Model MC
|
| 18 |
expectation is 1.4 events.
|
| 19 |
|
| 20 |
\subsection{Background estimate from the ABCD method}
|
| 21 |
\label{sec:abcdres}
|
| 22 |
|
| 23 |
The data yields in the
|
| 24 |
four regions are summarized in Table~\ref{tab:datayield}.
|
| 25 |
The prediction of the ABCD method is is given by $A\times C/B$ and
|
| 26 |
is 1.5 $\pm$ 0.9 events (statistical uncertainty only, assuming
|
| 27 |
Gaussian errors), as shown in Table~\ref{tab:datayield}.
|
| 28 |
|
| 29 |
\begin{table}[hbt]
|
| 30 |
\begin{center}
|
| 31 |
\caption{\label{tab:datayield} Data yields in the four
|
| 32 |
regions of Figure~\ref{fig:abcdData}, as well as the predicted yield in region D given
|
| 33 |
by A$\times$C / B. The quoted uncertainty
|
| 34 |
on the prediction in data is statistical only, assuming Gaussian errors.
|
| 35 |
We also show the SM Monte Carlo expectations, scaled to 34.85~pb$^{-1}$.}
|
| 36 |
\begin{tabular}{l||c|c|c|c||c}
|
| 37 |
\hline
|
| 38 |
sample & A & B & C & D & A$\times$C / B \\
|
| 39 |
\hline
|
| 40 |
$t\bar{t}\rightarrow \ell^{+}\ell^{-}$ & 7.96 & 33.07 & 4.81 & 1.20 & 1.16 \\
|
| 41 |
$t\bar{t}\rightarrow \mathrm{other}$ & 0.15 & 0.85 & 0.09 & 0.04 & 0.02 \\
|
| 42 |
$Z^0$ + jets & 0.00 & 1.16 & 0.08 & 0.08 & 0.00 \\
|
| 43 |
$W^{\pm}$ + jets & 0.00 & 0.10 & 0.00 & 0.00 & 0.00 \\
|
| 44 |
$W^+W^-$ & 0.19 & 0.29 & 0.02 & 0.07 & 0.02 \\
|
| 45 |
$W^{\pm}Z^0$ & 0.03 & 0.04 & 0.01 & 0.01 & 0.00 \\
|
| 46 |
$Z^0Z^0$ & 0.00 & 0.03 & 0.00 & 0.00 & 0.00 \\
|
| 47 |
single top & 0.28 & 1.00 & 0.04 & 0.01 & 0.01 \\
|
| 48 |
\hline
|
| 49 |
total SM MC & 8.61 & 36.54 & 5.05 & 1.41 & 1.19 \\
|
| 50 |
\hline
|
| 51 |
data & 11 & 36 & 5 & 1 &1.53 $\pm$ 0.86 \\
|
| 52 |
\hline
|
| 53 |
\end{tabular}
|
| 54 |
\end{center}
|
| 55 |
\end{table}
|
| 56 |
|
| 57 |
%As a cross-check, we can subtract from the yields in
|
| 58 |
%Table~\ref{tab:datayield} the expected DY contributions
|
| 59 |
%from Table~\ref{tab:ABCD-DY} in order to get a ``purer''
|
| 60 |
%estimate of the $t\bar{t}$ contribution. The result
|
| 61 |
%of this exercise is {\color{red} xx} events.
|
| 62 |
|
| 63 |
\clearpage
|
| 64 |
|
| 65 |
\subsection{Background estimate from the $P_T(\ell\ell)$ method}
|
| 66 |
\label{sec:victoryres}
|
| 67 |
|
| 68 |
We first use the $P_T(\ell \ell)$ method to predict the number of events
|
| 69 |
in control region A, defined in Sec.~\ref{sec:abcd} as
|
| 70 |
$125<{\rm SumJetPt}>300$~GeV and $\met/\sqrt{\rm SumJetPt}>$8.5.
|
| 71 |
We count the number of events in region
|
| 72 |
$A'$, defined in Sec.~\ref{sec:othBG} by replacing the above $\met/\sqrt{\rm SumJetPt}$
|
| 73 |
cut with the same cut on the quantity $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$,
|
| 74 |
and find $N_{A'}=6$. To predict the yield in region A we take
|
| 75 |
$N_A = K \cdot K_C \cdot N_{A'} = 10.4 \pm 4.2$
|
| 76 |
(statistical uncertainty only, assuming Gaussian errors),
|
| 77 |
where we have taken $K = 1.73$ and $K_C = 1$. This yield is in good
|
| 78 |
agreement with the observed yield of 11 events, as shown in
|
| 79 |
Table~\ref{tab:victory_control} and displayed in Fig.~\ref{fig:victory} (left).
|
| 80 |
{\color{red} \bf Perform DY estimate for this control region}.
|
| 81 |
|
| 82 |
Encouraged by the good agreement between predicted and observed yields
|
| 83 |
in the control region, we proceed to perform the $P_T(\ell \ell)$ method
|
| 84 |
in the signal region ${\rm SumJetPt}>300$~GeV.
|
| 85 |
The number of data events in region $D'$, which is defined in
|
| 86 |
Section~\ref{sec:othBG} to be the same as region $D$ but with the
|
| 87 |
$\met/\sqrt{\rm SumJetPt}$ requirement
|
| 88 |
replaced by a $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$ requirement,
|
| 89 |
is $N_{D'}=2$.
|
| 90 |
We next subtract off the expected DY contribution of
|
| 91 |
{\color{red} \bf $N_{DY}$ = 0.8 $\pm$ 0.8 (update DY estimate)} events, as calculated
|
| 92 |
in Sec.~\ref{sec:othBG}. The BG prediction is
|
| 93 |
$N_D = K \cdot K_C \cdot (N_{D'}-N_{DY}) = 1.8^{+2.5}_{-1.8}$ (statistical
|
| 94 |
uncertainty only, assuming Gaussian errors), where $K=1.54 \pm xx$
|
| 95 |
as derived in Sec.~\ref{sec:victory} and $K_C = 1$.
|
| 96 |
This prediction is consistent with the observed yield of
|
| 97 |
1 event, as summarized in Table~\ref{tab:victory_signal} and Fig.~\ref{fig:victory}
|
| 98 |
(right).
|
| 99 |
|
| 100 |
|
| 101 |
\begin{figure}[hbt]
|
| 102 |
\begin{center}
|
| 103 |
\includegraphics[width=0.48\linewidth]{victory_control_35pb.png}
|
| 104 |
\includegraphics[width=0.48\linewidth]{victory_signal_35pb.png}
|
| 105 |
\caption{\label{fig:victory}\protect Distributions of
|
| 106 |
tcMet/$\sqrt{\rm SumJetPt}$ for the control and signal region.
|
| 107 |
We show the oberved distributions in both Monte Carlo and data.
|
| 108 |
We also show the distributions predicted from
|
| 109 |
${P_T(\ell\ell)}/\sqrt{\rm SumJetPt}$ in both MC and data.}
|
| 110 |
\end{center}
|
| 111 |
\end{figure}
|
| 112 |
|
| 113 |
|
| 114 |
\begin{table}[hbt]
|
| 115 |
\begin{center}
|
| 116 |
\caption{\label{tab:victory_control}Results of the dilepton $p_{T}$ template method in the control region
|
| 117 |
$125 < \mathrm{sumJetPt} < 300$~GeV. The predicted and observed yields for
|
| 118 |
the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
|
| 119 |
and MC. The error on the prediction for data is statistical only, assuming
|
| 120 |
Gaussian errors.}
|
| 121 |
\begin{tabular}{lccc}
|
| 122 |
\hline
|
| 123 |
& Predicted & Observed & Obs/Pred \\
|
| 124 |
\hline
|
| 125 |
total SM MC & 7.10 & 8.61 & 1.21 \\
|
| 126 |
data & 10.38 $\pm$ 4.24 & 11 & 1.06 \\
|
| 127 |
\hline
|
| 128 |
\end{tabular}
|
| 129 |
\end{center}
|
| 130 |
\end{table}
|
| 131 |
|
| 132 |
\begin{table}[hbt]
|
| 133 |
\begin{center}
|
| 134 |
\caption{\label{tab:victory_signal}Results of the dilepton $p_{T}$ template method in the signal region
|
| 135 |
$\mathrm{sumJetPt} > 300$~GeV. The predicted and observed yields for
|
| 136 |
the region $\mathrm{tcmet}/\sqrt{\mathrm{sumJetPt}}>$~8.5 are shown for data
|
| 137 |
and MC. The error on the prediction for data is statistical only, assuming
|
| 138 |
Gaussian errors.}
|
| 139 |
\begin{tabular}{lccc}
|
| 140 |
\hline
|
| 141 |
& Predicted & Observed & Obs/Pred \\
|
| 142 |
\hline
|
| 143 |
total SM MC & 0.96 & 1.41 & 1.46 \\
|
| 144 |
data & $1.8^{+2.5}_{-1.8}$ & 1 & 0.56 \\
|
| 145 |
\hline
|
| 146 |
\end{tabular}
|
| 147 |
\end{center}
|
| 148 |
\end{table}
|
| 149 |
|
| 150 |
|
| 151 |
\subsection{Summary of results}
|
| 152 |
To summarize: we see no evidence for an anomalous
|
| 153 |
rate of opposite sign isolated dilepton events
|
| 154 |
at high \met and high SumJetPt. The extraction of
|
| 155 |
quantitative limits on new physics models is discussed
|
| 156 |
in Section~\ref{sec:limit}. |
