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Revision 1.7 by benhoob, Wed Nov 10 17:27:20 2010 UTC vs.
Revision 1.8 by benhoob, Wed Nov 10 17:45:55 2010 UTC

# Line 66 | Line 66 | The number of data events in region $D'$
66   Section~\ref{sec:othBG} to be the same as region $D$ but with the
67   $\met/\sqrt{\rm SumJetPt}$ requirement
68   replaced by a $P_T(\ell\ell)/\sqrt{\rm SumJetPt}$ requirement
69 < is $N_{D'}=1$.  Thus the BG prediction is
69 > is $N_{D'}=2$.  Thus the BG prediction is
70   $N_D = K \cdot K_C \cdot N_{D'} = 1.5$
71   where $K=1.5 \pm xx$ as derived in Sec.~\ref{sec:victory} and
72   $K_C = 1$.
73   Note that if we were to subtract off from region $D'$
74 < the {\color{red} 0.4 $\pm$ 0.4} DY events estimated from
74 > the {\color{red} 0.8 $\pm$ 0.8} DY events estimated from
75   Section~\ref{sec:othBG}, the background
76 < prediction would change to $N_D=0.9 \pm xx$ events.
76 > prediction would change to $N_D=1.8 \pm xx$ events.
77  
78   %%%TO BE REPLACED
79   %{\color{red}As mentioned previously, for the 11/pb analysis
# Line 98 | Line 98 | prediction would change to $N_D=0.9 \pm
98  
99   As a cross-check, we use the $P_T(\ell \ell)$
100   method to also predict the number of events in the
101 < control region $120<{\rm SumJetPt}<300$ GeV and
101 > control region $125<{\rm SumJetPt}<300$ GeV and
102   \met/$\sqrt{\rm SumJetPt} > 8.5$.  We predict
103   $5.6^{+x}_{-y}$ events and we observe 4.
104   The results of the $P_T(\ell\ell)$ method are
# Line 106 | Line 106 | summarized in Figure~\ref{fig:victory}.
106  
107   \begin{figure}[hbt]
108   \begin{center}
109 < \includegraphics[width=0.48\linewidth]{victory_control.png}
110 < \includegraphics[width=0.48\linewidth]{victory_sig.png}
109 > \includegraphics[width=0.48\linewidth]{victory_control_35pb.png}
110 > \includegraphics[width=0.48\linewidth]{victory_signal_35pb.png}
111   \caption{\label{fig:victory}\protect Distributions of
112   tcMet/$\sqrt{\rm SumJetPt}$ for the control and signal region.
113   We show the oberved distributions in both Monte Carlo and data.

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