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\label{sec:abcd} |
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|
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We find that in $t\bar{t}$ events \met and |
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< |
\met$/\sqrt{\rm SumJetPt}$ are nearly uncorrelated. |
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< |
This is demonstrated in Figure~\ref{fig:uncor}. |
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> |
\met$/\sqrt{\rm SumJetPt}$ are nearly uncorrelated, |
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> |
as demonstrated in Figure~\ref{fig:uncor}. |
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Thus, we can use an ABCD method in the \met$/\sqrt{\rm SumJetPt}$ vs |
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sumJetPt plane to estimate the background in a data driven way. |
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|
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< |
\begin{figure}[tb] |
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> |
\begin{figure}[bht] |
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\begin{center} |
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\includegraphics[width=0.75\linewidth]{uncorrelated.pdf} |
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\caption{\label{fig:uncor}\protect Distributions of SumJetPt |
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\end{center} |
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|
\end{figure} |
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|
|
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< |
\begin{figure}[bt] |
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> |
\begin{figure}[tb] |
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|
\begin{center} |
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\includegraphics[width=0.5\linewidth, angle=90]{abcdMC.pdf} |
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\caption{\label{fig:abcdMC}\protect Distributions of SumJetPt |
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%wrt changes in regions. I am not sure that we have done it and |
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%I am not sure it is necessary (Claudio).} |
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|
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< |
\begin{table}[htb] |
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> |
\begin{table}[ht] |
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\begin{center} |
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\caption{\label{tab:abcdMC} Expected SM Monte Carlo yields for |
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35 pb$^{-1}$ in the ABCD regions, as well as the predicted yield in |
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< |
the signal region given by A$\times$C/B. Here 'SM other' is the sum |
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> |
the signal region given by A $\times$ C / B. Here `SM other' is the sum |
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of non-dileptonic $t\bar{t}$ decays, $W^{\pm}$+jets, $W^+W^-$, |
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$W^{\pm}Z^0$, $Z^0Z^0$ and single top.} |
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< |
\begin{tabular}{l||c|c|c|c||c} |
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> |
\begin{tabular}{lccccc} |
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|
\hline |
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< |
sample & A & B & C & D & A$\times$C/B \\ |
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> |
sample & A & B & C & D & A $\times$ C / B \\ |
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> |
\hline |
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> |
|
| 71 |
> |
|
| 72 |
|
\hline |
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$t\bar{t}\rightarrow \ell^{+}\ell^{-}$ & 7.96 & 33.07 & 4.81 & 1.20 & 1.16 \\ |
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< |
$Z^0$ + jets & 0.00 & 1.16 & 0.08 & 0.08 & 0.00 \\ |
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$Z^0 \rightarrow \ell^{+}\ell^{-}$ & 0.03 & 1.47 & 0.10 & 0.10 & 0.00 \\ |
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SM other & 0.65 & 2.31 & 0.17 & 0.14 & 0.05 \\ |
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\hline |
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< |
total SM MC & 8.61 & 36.54 & 5.05 & 1.41 & 1.19 \\ |
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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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\end{tabular} |
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|
\end{center} |
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to account for the fact that any dilepton selection must include a |
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moderate \met cut in order to reduce Drell Yan backgrounds. This |
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is discussed in Section 5.3 of Reference~\cite{ref:ourvictory}; for a \met |
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cut of 50 GeV, the rescaling factor is obtained from the data as |
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> |
cut of 50 GeV, the rescaling factor is obtained from the MC as |
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|
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\newcommand{\ptll} {\ensuremath{P_T(\ell\ell)}} |
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\begin{center} |
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\item Similarly, the \met$>$50 GeV cut introduces an asymmetry between leptons and |
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neutrinos which is only partially compensated by the $K$ factor above. |
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\item The \met resolution is much worse than the dilepton $P_T$ resolution. |
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< |
When convoluted with a falling spectrum in the tails of \met, this result |
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> |
When convoluted with a falling spectrum in the tails of \met, this results |
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|
in a harder spectrum for \met than the original $P_T(\nu\nu)$. |
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\item The \met response in CMS is not exactly 1. This causes a distortion |
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|
in the \met distribution that is not present in the $P_T(\ell\ell)$ distribution. |
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sources. These events can affect the background prediction. Particularly |
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dangerous are high $P_T$ Drell Yan events that barely pass the \met$>$ 50 |
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GeV selection. They will tend to push the data-driven background prediction up. |
| 142 |
+ |
Therefore we estimate the number of DY events entering the background prediction |
| 143 |
+ |
using the $R_{out/in}$ method as described in Sec.~\ref{sec:othBG}. |
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\end{itemize} |
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|
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We have studied these effects in SM Monte Carlo, using a mixture of generator and |
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4&Y & N & N & GEN & Y & Y & Y & 1.55 \\ |
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5&Y & N & N & RECOSIM & Y & Y & Y & 1.51 \\ |
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6&Y & Y & N & RECOSIM & Y & Y & Y & 1.58 \\ |
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< |
7&Y & Y & Y & RECOSIM & Y & Y & Y & 1.18 \\ |
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> |
7&Y & Y & Y & RECOSIM & Y & Y & Y & 1.38 \\ |
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> |
%%%NOTE: updated value 1.18 -> 1.46 since 2/3 DY events have been removed by updated analysis selections, |
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> |
%%%dpt/pt cut and general lepton veto |
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|
\hline |
| 170 |
|
\end{tabular} |
| 171 |
|
\end{center} |
| 183 |
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% by $\approx 4\%$\footnote{We find that observed/predicted changes by roughly 0.1 |
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%for each 1.5\% change in \met response.}. |
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Finally, contamination from non $t\bar{t}$ |
| 186 |
< |
events can have a significant impact on the BG prediction. The changes between |
| 187 |
< |
lines 6 and 7 of Table~\ref{tab:victorybad} is driven by 3 |
| 188 |
< |
Drell Yan events that pass the \met selection in Monte Carlo (thus the effect |
| 189 |
< |
is statistically not well quantified). |
| 186 |
> |
events can have a significant impact on the BG prediction. |
| 187 |
> |
%The changes between |
| 188 |
> |
%lines 6 and 7 of Table~\ref{tab:victorybad} is driven by 3 |
| 189 |
> |
%Drell Yan events that pass the \met selection in Monte Carlo (thus the effect |
| 190 |
> |
%is statistically not well quantified). |
| 191 |
|
|
| 192 |
|
An additional source of concern is that the CMS Madgraph $t\bar{t}$ MC does |
| 193 |
|
not include effects of spin correlations between the two top quarks. |
| 256 |
|
\hline |
| 257 |
|
& Yield & ABCD & $P_T(\ell \ell)$ \\ |
| 258 |
|
\hline |
| 259 |
< |
SM only & 1.41 & 1.19 & 0.96 \\ |
| 260 |
< |
SM + LM0 & 7.88 & 4.24 & 2.28 \\ |
| 261 |
< |
SM + LM1 & 3.98 & 1.53 & 1.44 \\ |
| 259 |
> |
SM only & 1.43 & 1.19 & 1.03 \\ |
| 260 |
> |
SM + LM0 & 7.90 & 4.23 & 2.35 \\ |
| 261 |
> |
SM + LM1 & 4.00 & 1.53 & 1.51 \\ |
| 262 |
|
\hline |
| 263 |
|
\end{tabular} |
| 264 |
|
\end{center} |
