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claudioc |
1.1 |
\subsection{Dilepton studies in CR4}
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\label{sec:cr4}
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\subsubsection{Modeling of Additional Hard Jets in Top Dilepton Events}
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\label{sec:jetmultiplicity}
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Dilepton \ttbar\ events have 2 jets from the top decays, so additional
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jets from radiation or higher order contributions are required to
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claudioc |
1.10 |
enter the signal sample. In this Section we develop an algorithm
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vimartin |
1.13 |
to be applied to all \ttll\ MC samples to ensure that the distribution
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claudioc |
1.10 |
of extra jets is properly modelled.
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The modeling of additional jets in \ttbar\
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claudioc |
1.1 |
events is checked in a \ttll\ control sample,
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selected by requiring
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\begin{itemize}
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\item exactly 2 selected electrons or muons with \pt $>$ 20 GeV
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linacre |
1.8 |
\item \met\ $>$ 50 GeV
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claudioc |
1.1 |
\item $\geq1$ b-tagged jet
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burkett |
1.2 |
\item Z-veto ($|m_{\ell\ell} - 91| > 15$ GeV)
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claudioc |
1.1 |
\end{itemize}
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Figure~\ref{fig:dileptonnjets} shows a comparison of the jet
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multiplicity distribution in data and MC for this two-lepton control
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sample. After requiring at least 1 b-tagged jet, most of the
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events have 2 jets, as expected from the dominant process \ttll. There is also a
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significant fraction of events with additional jets.
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The 3-jet sample is mainly comprised of \ttbar\ events with 1 additional
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emission and similarly the $\ge4$-jet sample contains primarily
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$\ttbar+\ge2$ jet events.
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%Even though the primary \ttbar\
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%Madgraph sample used includes up to 3 additional partons at the Matrix
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%Element level, which are intended to describe additional hard jets,
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%Figure~\ref{fig:dileptonnjets} shows a slight mis-modeling of the
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%additional jets.
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\begin{figure}[hbt]
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\begin{center}
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linacre |
1.8 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_mueg.pdf}
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\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_diel.pdf}%
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\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_dimu.pdf}
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claudioc |
1.1 |
\caption{
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\label{fig:dileptonnjets}%\protect
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Comparison of the jet multiplicity distribution in data and MC for dilepton events in the \E-\M\
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(top), \E-\E\ (bottom left) and \M-\M\ (bottom right) channels.}
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\end{center}
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\end{figure}
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It should be noted that in the case of \ttll\ events
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with a single reconstructed lepton, the other lepton may be
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mis-reconstructed as a jet. For example, a hadronic tau may be
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mis-identified as a jet (since no $\tau$ identification is used).
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In this case only 1 additional jet from radiation may suffice for
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a \ttll\ event to enter the signal sample. As a result, both the
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samples with $\ttbar+1$ jet and $\ttbar+\ge2$ jets are relevant for
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burkett |
1.2 |
estimating the top dilepton background in the signal region.
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claudioc |
1.1 |
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%In this section we discuss a correction to $ N_{2 lep}^{MC} $ in Equation XXX
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%due to differences in the modelling of the jet multiplicity in data versus MC.
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%The same correction also enters $ N_{peak}^{MC}$ in Equation XXX to the extend that the
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%dilepton contributions to $ N_{peak}^{MC}$ gets corrected.
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%The dilepton control sample is defined by the following requirements:
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%\begin{itemize}
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%\item Exactly 2 selected electrons or muons with \pt $>$ 20 GeV
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%\item \met\ $>$ 50 GeV
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%\item $\geq1$ b-tagged jet
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%\end{itemize}
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%
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%This sample is dominated by \ttll. The distribution of \njets\ for data and MC passing this selection is displayed in Fig.~\ref{fig:dilepton_njets}.
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%We use this distribution to derive scale factors which reweight the \ttll\ MC \njets\ distribution to match the data. We define the following
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%quantities
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%
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%\begin{itemize}
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%\item $N_{2}=$ data yield minus non-dilepton \ttbar\ MC yield for \njets\ $\leq$ 2
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%\item $N_{3}=$ data yield minus non-dilepton \ttbar\ MC yield for \njets\ = 3
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%\item $N_{4}=$ data yield minus non-dilepton \ttbar\ MC yield for \njets\ $\geq$ 4
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%\item $M_{2}=$ dilepton \ttbar\ MC yield for \njets\ $\leq$ 2
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%\item $M_{3}=$ dilepton \ttbar\ MC yield for \njets\ = 3
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%\item $M_{4}=$ dilepton \ttbar\ MC yield for \njets\ $\geq$ 4
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%\end{itemize}
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%
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%We use these yields to define 3 scale factors, which quantify the data/MC ratio in the 3 \njets\ bins:
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%
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%\begin{itemize}
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%\item $SF_2 = N_2 / M_2$
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%\item $SF_3 = N_3 / M_3$
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%\item $SF_4 = N_4 / M_4$
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%\end{itemize}
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%
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%And finally, we define the scale factors $K_3$ and $K_4$:
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%
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%\begin{itemize}
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%\item $K_3 = SF_3 / SF_2$
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%\item $K_4 = SF_4 / SF_2$
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%\end{itemize}
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%
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%The scale factor $K_3$ is extracted from dilepton \ttbar\ events with \njets = 3, which have exactly 1 ISR jet.
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%The scale factor $K_4$ is extracted from dilepton \ttbar\ events with \njets $\geq$ 4, which have at least 2 ISR jets.
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%Both of these scale factors are needed since dilepton \ttbar\ events which fall in our signal region (including
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%the \njets $\geq$ 4 requirement) may require exactly 1 ISR jet, in the case that the second lepton is reconstructed
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%as a jet, or at least 2 ISR jets, in the case that the second lepton is not reconstructed as a jet. These scale
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%factors are applied to the dilepton \ttbar\ MC only. For a given MC event, we determine whether to use $K_3$ or $K_4$
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%by counting the number of reconstructed jets in the event ($N_{\rm{jets}}^R$) , and subtracting off any reconstructed
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%jet which is matched to the second lepton at generator level ($N_{\rm{jets}}^\ell$); $N_{\rm{jets}}^{\rm{cor}} = N_{\rm{jets}}^R - N_{\rm{jets}}^\ell$.
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%For events with $N_{\rm{jets}}^{\rm{cor}}=3$ the factor $K_3$ is applied, while for events with $N_{\rm{jets}}^{\rm{cor}}\geq4$ the factor $K_4$ is applied.
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%For all subsequent steps, the scale factors $K_3$ and $K_4$ have been
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%applied to the \ttll\ MC.
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Table~\ref{tab:njetskfactors} shows scale factors ($K_3$ and $K_4$)
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used to correct the
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fraction of events with additional jets in MC to the observed fraction
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in data. These scale factors are calculated from Fig.~\ref{fig:dileptonnjets}
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as follows:
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\begin{itemize}
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claudioc |
1.10 |
\item $N_{2}=$ data yield minus non-dilepton \ttbar\ MC yield for
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\njets\ =1 or 2.
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claudioc |
1.1 |
\item $N_{3}=$ data yield minus non-dilepton \ttbar\ MC yield for \njets\ = 3
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\item $N_{4}=$ data yield minus non-dilepton \ttbar\ MC yield for \njets\ $\geq$ 4
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claudioc |
1.10 |
\item $M_{2}=$ dilepton \ttbar\ MC yield for \njets\ = 1 or 2
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claudioc |
1.1 |
\item $M_{3}=$ dilepton \ttbar\ MC yield for \njets\ = 3
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\item $M_{4}=$ dilepton \ttbar\ MC yield for \njets\ $\geq$ 4
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\end{itemize}
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\noindent then
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\begin{itemize}
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\item $SF_2 = N_2 / M_2$
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\item $SF_3 = N_3 / M_3$
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\item $SF_4 = N_4 / M_4$
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\item $K_3 = SF_3 / SF_2$
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\item $K_4 = SF_4 / SF_2$
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\end{itemize}
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\noindent This insures that $K_3 M_3/(M_2 + K_3 M_3 + K_4 M_4) = N_3 /
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(N_2+N_3+N_4)$ and similarly for the $\geq 4$ jet bin.
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linacre |
1.14 |
Table~\ref{tab:njetskfactors} also shows the values of $K_3$ and $K_4$ for different values of the \met\ cut in the control sample definition.
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claudioc |
1.10 |
% These values of $K_3$ and $K_4$ are not used in the analysis, but
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vimartin |
1.13 |
This demonstrates that there is no statistically significant dependence of $K_3$ and $K_4$ on the \met\ cut.
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claudioc |
1.1 |
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linacre |
1.8 |
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claudioc |
1.10 |
The factors $K_3$ and $K_4$ (derived with the 100 GeV \met\ cut) are applied to the \ttll\ MC throughout the
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claudioc |
1.1 |
entire analysis, i.e.
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whenever \ttll\ MC is used to estimate or subtract
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claudioc |
1.10 |
a yield or distribution. To be explicit, whenever Powheg is used,
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the Powheg $K_3$ and $K_4$ are used; whenever default MadGraph is
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used, the MadGraph $K_3$ and $K_4$ are used, etc.
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claudioc |
1.1 |
%
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In order to do so, it is first necessary to count the number of
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additional jets from radiation and exclude leptons mis-identified as
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jets. A jet is considered a mis-identified lepton if it is matched to a
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generator-level second lepton with sufficient energy to satisfy the jet
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\pt\ requirement ($\pt>30~\GeV$). Then \ttll\ events that need two
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radiation jets to enter our selection are scaled by $K_4$,
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while those that only need one radiation jet are scaled by $K_3$.
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\begin{table}[!ht]
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\begin{center}
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vimartin |
1.12 |
{\footnotesize
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linacre |
1.14 |
\begin{tabular}{l|c|c|c|c|c|c}
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\cline{2-7}
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& \multicolumn{6}{c}{ \met\ cut for data/MC scale factors} \\
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claudioc |
1.1 |
\hline
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linacre |
1.14 |
Sample & 50 GeV & 100 GeV & 150 GeV & 200 GeV & 250 GeV & 300 GeV \\
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claudioc |
1.1 |
\hline
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\hline
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linacre |
1.14 |
N jets $= 3$
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& $K_3 = 0.98 \pm 0.02$ & $K_3 = 1.01 \pm 0.03$ & $K_3 = 1.00 \pm 0.08$ & $K_3 = 1.03 \pm 0.18$ & $K_3 = 1.29 \pm 0.51$ & $K_3 = 1.58 \pm 1.23$ \\
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N jets $\ge4$
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& $K_4 = 0.94 \pm 0.02$ & $K_4 = 0.93 \pm 0.04$ & $K_4 = 1.00 \pm 0.08$ & $K_4 = 1.07 \pm 0.18$ & $K_4 = 1.30 \pm 0.48$ & $K_4 = 1.65 \pm 1.19$ \\
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claudioc |
1.1 |
\hline
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vimartin |
1.12 |
\end{tabular}}
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claudioc |
1.1 |
\caption{Data/MC scale factors used to account for differences in the
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fraction of events with additional hard jets from radiation in
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linacre |
1.14 |
\ttll\ events.
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The N jets $= 3$ scale factor, $K_3$, is sensitive to $\ttbar+1$ extra jet from radiation, while
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the N jets $\ge4$ scale factor, $K_4$, is sensitive to $\ttbar+\ge2$ extra jets from radiation.
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The values derived with the 100 GeV \met\ cut are applied
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linacre |
1.8 |
to the \ttll\ MC throughout the analysis. \label{tab:njetskfactors}}
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claudioc |
1.1 |
\end{center}
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\end{table}
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\clearpage
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\subsubsection{Validation of the ``Physics'' Modelling of the \ttdl\
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MC in CR4}
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burkett |
1.2 |
\label{sec:CR4-valid}
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claudioc |
1.1 |
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As mentioned above, $t\bar{t} \to $ dileptons where one of the leptons
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is somehow lost constitutes the main background.
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The object of this test is to validate the $M_T$ distribution of this
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background by looking at the $M_T$ distribution of well identified
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dilepton events.
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We construct a transverse mass variable from the leading lepton and
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vimartin |
1.4 |
the \met. We distinguish between events with leading electrons and
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| 198 |
claudioc |
1.1 |
leading muons.
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The $t\bar{t}$ MC is corrected using the $K_3$ and $K_4$ factors
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from Section~\ref{sec:jetmultiplicity}. It is also normalized to the
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claudioc |
1.11 |
total data yield separately for the \met\ requirements of the various signal
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regions. These normalization factors are listed
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claudioc |
1.1 |
in Table~\ref{tab:cr4mtsf} and are close to unity.
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The underlying \met\ and $M_T$ distributions are shown in
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burkett |
1.2 |
Figures~\ref{fig:cr4met} and~\ref{fig:cr4mtrest}. The data-MC agreement
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| 208 |
claudioc |
1.1 |
is quite good. Quantitatively, this is also shown in Table~\ref{tab:cr4yields}.
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claudioc |
1.10 |
This is a {\bf very} important Table. It shows that for well
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| 210 |
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identified \ttdl\ , the MC can predict the $M_T$ tail. Since the
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| 211 |
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main background is also \ttdl\ except with one ``missed'' lepton,
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this is a key test.
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claudioc |
1.1 |
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\begin{table}[!h]
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| 215 |
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\begin{center}
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| 216 |
vimartin |
1.3 |
{\footnotesize
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| 217 |
vimartin |
1.6 |
\begin{tabular}{l||c||c|c|c|c|c|c}
|
| 218 |
claudioc |
1.1 |
\hline
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| 219 |
vimartin |
1.3 |
Sample & CR4PRESEL & CR4A & CR4B & CR4C &
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| 220 |
vimartin |
1.6 |
CR4D & CR4E & CR4F\\
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| 221 |
claudioc |
1.1 |
\hline
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| 222 |
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\hline
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| 223 |
vimartin |
1.6 |
$\mu$ Data/MC-SF & $1.01 \pm 0.03$ & $0.96 \pm 0.04$ & $0.99 \pm 0.07$ & $1.05 \pm 0.13$ & $0.91 \pm 0.20$ & $1.10 \pm 0.34$ & $1.50 \pm 0.67$ \\
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| 224 |
claudioc |
1.1 |
\hline
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| 225 |
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\hline
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| 226 |
vimartin |
1.6 |
e Data/MC-SF & $0.99 \pm 0.03$ & $0.99 \pm 0.05$ & $0.91 \pm 0.08$ & $0.84 \pm 0.13$ & $0.70 \pm 0.18$ & $0.73 \pm 0.29$ & $0.63 \pm 0.38$ \\
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| 227 |
claudioc |
1.1 |
\hline
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| 228 |
vimartin |
1.3 |
\end{tabular}}
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| 229 |
claudioc |
1.1 |
\caption{ Data/MC scale factors for total yields, applied to compare
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| 230 |
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the shapes of the distributions.
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| 231 |
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The uncertainties are statistical only.
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| 232 |
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\label{tab:cr4mtsf}}
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| 233 |
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\end{center}
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\end{table}
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\begin{table}[!h]
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| 238 |
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\begin{center}
|
| 239 |
vimartin |
1.3 |
{\footnotesize
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| 240 |
vimartin |
1.6 |
\begin{tabular}{l||c||c|c|c|c|c|c}
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| 241 |
claudioc |
1.1 |
\hline
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| 242 |
vimartin |
1.3 |
Sample & CR4PRESEL & CR4A & CR4B & CR4C &
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| 243 |
vimartin |
1.6 |
CR4D & CR4E & CR4F\\
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| 244 |
claudioc |
1.1 |
\hline
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| 245 |
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\hline
|
| 246 |
vimartin |
1.7 |
$\mu$ MC & $256 \pm 14$ & $152 \pm 11$ & $91 \pm 9$ & $26 \pm 5$ & $6 \pm 2$ & $4 \pm 2$ & $2 \pm 1$ \\
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| 247 |
vimartin |
1.6 |
$\mu$ Data & $251$ & $156$ & $98$ & $27$ & $8$ & $6$ & $4$ \\
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| 248 |
claudioc |
1.1 |
\hline
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| 249 |
vimartin |
1.7 |
$\mu$ Data/MC SF & $0.98 \pm 0.08$ & $1.02 \pm 0.11$ & $1.08 \pm 0.16$ & $1.04 \pm 0.28$ & $1.29 \pm 0.65$ & $1.35 \pm 0.80$ & $2.10 \pm 1.72$ \\
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claudioc |
1.1 |
\hline
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| 251 |
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\hline
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| 252 |
vimartin |
1.7 |
e MC & $227 \pm 13$ & $139 \pm 11$ & $73 \pm 8$ & $21 \pm 4$ & $5 \pm 2$ & $2 \pm 1$ & $1 \pm 1$ \\
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| 253 |
vimartin |
1.6 |
e Data & $219$ & $136$ & $72$ & $19$ & $2$ & $1$ & $1$ \\
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| 254 |
claudioc |
1.1 |
\hline
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vimartin |
1.7 |
e Data/MC SF & $0.96 \pm 0.09$ & $0.98 \pm 0.11$ & $0.99 \pm 0.16$ & $0.92 \pm 0.29$ & $0.41 \pm 0.33$ & $0.53 \pm 0.62$ & $0.76 \pm 0.96$ \\
|
| 256 |
|
|
\hline
|
| 257 |
|
|
\hline
|
| 258 |
|
|
$\mu$+e MC & $483 \pm 19$ & $291 \pm 16$ & $164 \pm 13$ & $47 \pm 7$ & $11 \pm 3$ & $6 \pm 2$ & $3 \pm 2$ \\
|
| 259 |
|
|
$\mu$+e Data & $470$ & $292$ & $170$ & $46$ & $10$ & $7$ & $5$ \\
|
| 260 |
|
|
\hline
|
| 261 |
|
|
$\mu$+e Data/MC SF & $0.97 \pm 0.06$ & $1.00 \pm 0.08$ & $1.04 \pm 0.11$ & $0.99 \pm 0.20$ & $0.90 \pm 0.37$ & $1.11 \pm 0.57$ & $1.55 \pm 1.04$ \\
|
| 262 |
claudioc |
1.1 |
\hline
|
| 263 |
vimartin |
1.3 |
\end{tabular}}
|
| 264 |
claudioc |
1.1 |
\caption{ Yields in \mt\ tail comparing the MC prediction (after
|
| 265 |
|
|
applying SFs) to data. The uncertainties are statistical only.
|
| 266 |
|
|
\label{tab:cr4yields}}
|
| 267 |
|
|
\end{center}
|
| 268 |
|
|
\end{table}
|
| 269 |
|
|
|
| 270 |
|
|
\begin{figure}[hbt]
|
| 271 |
|
|
\begin{center}
|
| 272 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/met_met50_leadmuo_nj4.pdf}%
|
| 273 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/met_met50_leadele_nj4.pdf}
|
| 274 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met100_leadmuo_nj4.pdf}%
|
| 275 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met100_leadele_nj4.pdf}
|
| 276 |
|
|
\caption{
|
| 277 |
|
|
Comparison of the \met\ (top) and \mt\ for $\met>100$ (bottom) distributions in data vs. MC for events
|
| 278 |
|
|
with a leading muon (left) and leading electron (right)
|
| 279 |
|
|
satisfying the requirements of CR4.
|
| 280 |
|
|
\label{fig:cr4met}
|
| 281 |
|
|
}
|
| 282 |
|
|
\end{center}
|
| 283 |
|
|
\end{figure}
|
| 284 |
|
|
|
| 285 |
|
|
\begin{figure}[hbt]
|
| 286 |
|
|
\begin{center}
|
| 287 |
vimartin |
1.3 |
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met50_leadmuo_nj4.pdf}%
|
| 288 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met50_leadele_nj4.pdf}
|
| 289 |
claudioc |
1.1 |
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met150_leadmuo_nj4.pdf}%
|
| 290 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met150_leadele_nj4.pdf}
|
| 291 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met200_leadmuo_nj4.pdf}%
|
| 292 |
|
|
\includegraphics[width=0.5\linewidth]{plots/CR4plots/mt_met200_leadele_nj4.pdf}
|
| 293 |
|
|
\caption{
|
| 294 |
|
|
Comparison of the \mt\ distribution in data vs. MC for events
|
| 295 |
|
|
with a leading muon (left) and leading electron (right)
|
| 296 |
|
|
satisfying the requirements of CR4. The \met\ requirements used are
|
| 297 |
vimartin |
1.3 |
50 GeV (top), 200 GeV (middle) and 250 GeV (bottom).
|
| 298 |
claudioc |
1.1 |
\label{fig:cr4mtrest}
|
| 299 |
|
|
}
|
| 300 |
|
|
\end{center}
|
| 301 |
|
|
\end{figure}
|
| 302 |
|
|
|
| 303 |
|
|
|
| 304 |
|
|
\clearpage
|
