| 1 |
%\section{Systematics Uncertainties on the Background Prediction}
|
| 2 |
%\label{sec:systematics}
|
| 3 |
|
| 4 |
In this Section we discuss the systematic uncertainty on the BG
|
| 5 |
prediction. This prediction is assembled from the event
|
| 6 |
counts in the peak region of the transverse mass distribution as
|
| 7 |
well as Monte Carlo
|
| 8 |
with a number of correction factors, as described previously.
|
| 9 |
The
|
| 10 |
final uncertainty on the prediction is built up from the uncertainties in these
|
| 11 |
individual
|
| 12 |
components.
|
| 13 |
The calculation is done for each signal
|
| 14 |
region,
|
| 15 |
for electrons and muons separately.
|
| 16 |
|
| 17 |
The choice to normalize to the peak region of $M_T$ has the
|
| 18 |
advantage that some uncertainties, e.g., luminosity, cancel.
|
| 19 |
It does however introduce complications because it couples
|
| 20 |
some of the uncertainties in non-trivial ways. For example,
|
| 21 |
the primary effect of an uncertainty on the rare MC cross-section
|
| 22 |
is to introduce an uncertainty in the rare MC background estimate
|
| 23 |
which comes entirely from MC. But this uncertainty also affects,
|
| 24 |
for example,
|
| 25 |
the $t\bar{t} \to$ dilepton BG estimate because it changes the
|
| 26 |
$t\bar{t}$ normalization to the peak region (because some of the
|
| 27 |
events in the peak region are from rare processes). These effects
|
| 28 |
are carefully accounted for. The contribution to the overall
|
| 29 |
uncertainty from each background source is tabulated in
|
| 30 |
Section~\ref{sec:bgunc-bottomline}.
|
| 31 |
Here we discuss the uncertainties one-by-one and comment
|
| 32 |
on their impact on the overall result, at least to first order.
|
| 33 |
Second order effects, such as the one described, are also included.
|
| 34 |
|
| 35 |
\subsection{Statistical uncertainties on the event counts in the $M_T$
|
| 36 |
peak regions}
|
| 37 |
These vary between 2\% and 20\%, depending on the signal region
|
| 38 |
(different
|
| 39 |
signal regions have different \met\ requirements, thus they also have
|
| 40 |
different $M_T$ regions used as control).
|
| 41 |
Since
|
| 42 |
the major backgrounds, eg, $t\bar{t}$ are normalized to the peak regions, this
|
| 43 |
fractional uncertainty is pretty much carried through all the way to
|
| 44 |
the end. There is also an uncertainty from the finite MC event counts
|
| 45 |
in the $M_T$ peak regions. This is also included, but it is smaller.
|
| 46 |
|
| 47 |
Normalizing to the $M_T$ peak has the distinct advantages that
|
| 48 |
uncertainties on luminosity, cross-sections, trigger efficiency,
|
| 49 |
lepton ID, cancel out.
|
| 50 |
For the low statistics regions with high \met\ requirements, the
|
| 51 |
price to pay in terms of event count is that statistical uncertainties start
|
| 52 |
to become significant. In the future we may consider a different
|
| 53 |
normalization startegy in the low statistics regions.
|
| 54 |
|
| 55 |
\subsection{Uncertainty from the choice of $M_T$ peak region}
|
| 56 |
|
| 57 |
This choice affects the scale factors of Table~\ref{tab:mtpeaksf}.
|
| 58 |
If the $M_T$ peak region is not well modelled, this would introduce an
|
| 59 |
uncertainty.
|
| 60 |
|
| 61 |
We have tested this possibility by recalculating the post-veto scale factors for a different
|
| 62 |
choice
|
| 63 |
of $M_T$ peak region ($40 < M_T < 100$ GeV instead of the default
|
| 64 |
$50 < M_T < 80$ GeV). This is shown in Table~\ref{tab:mtpeaksf2}.
|
| 65 |
The two results for the scale factors are very compatible.
|
| 66 |
We do not take any systematic uncertainty for this possible effect.
|
| 67 |
|
| 68 |
\begin{table}[!h]
|
| 69 |
\begin{center}
|
| 70 |
{\footnotesize
|
| 71 |
\begin{tabular}{l||c|c|c|c|c|c|c}
|
| 72 |
\hline
|
| 73 |
Sample & SRA & SRB & SRC & SRD & SRE & SRF & SRG\\
|
| 74 |
\hline
|
| 75 |
\hline
|
| 76 |
\multicolumn{8}{c}{$50 \leq \mt \leq 80$} \\
|
| 77 |
\hline
|
| 78 |
$\mu$ pre-veto \mt-SF & $1.02 \pm 0.02$ & $0.95 \pm 0.03$ & $0.90 \pm 0.05$ & $0.98 \pm 0.08$ & $0.97 \pm 0.13$ & $0.85 \pm 0.18$ & $0.92 \pm 0.31$ \\
|
| 79 |
$\mu$ post-veto \mt-SF & $1.00 \pm 0.02$ & $0.95 \pm 0.03$ & $0.91 \pm 0.05$ & $1.00 \pm 0.09$ & $0.99 \pm 0.13$ & $0.85 \pm 0.18$ & $0.96 \pm 0.31$ \\
|
| 80 |
\hline
|
| 81 |
$\mu$ veto \mt-SF & $0.98 \pm 0.01$ & $0.99 \pm 0.01$ & $1.01 \pm 0.02$ & $1.02 \pm 0.04$ & $1.02 \pm 0.06$ & $1.00 \pm 0.09$ & $1.04 \pm 0.11$ \\
|
| 82 |
\hline
|
| 83 |
\hline
|
| 84 |
e pre-veto \mt-SF & $0.95 \pm 0.02$ & $0.95 \pm 0.03$ & $0.94 \pm 0.06$ & $0.85 \pm 0.09$ & $0.84 \pm 0.13$ & $1.05 \pm 0.23$ & $1.04 \pm 0.33$ \\
|
| 85 |
e post-veto \mt-SF & $0.92 \pm 0.02$ & $0.91 \pm 0.03$ & $0.91 \pm 0.06$ & $0.74 \pm 0.08$ & $0.75 \pm 0.13$ & $0.91 \pm 0.22$ & $1.01 \pm 0.33$ \\
|
| 86 |
\hline
|
| 87 |
e veto \mt-SF & $0.97 \pm 0.01$ & $0.96 \pm 0.02$ & $0.97 \pm 0.03$ & $0.87 \pm 0.05$ & $0.89 \pm 0.08$ & $0.86 \pm 0.11$ & $0.97 \pm 0.14$ \\
|
| 88 |
\hline
|
| 89 |
\hline
|
| 90 |
\multicolumn{8}{c}{$40 \leq \mt \leq 100$} \\
|
| 91 |
\hline
|
| 92 |
$\mu$ pre-veto \mt-SF & $1.02 \pm 0.01$ & $0.97 \pm 0.02$ & $0.91 \pm 0.05$ & $0.95 \pm 0.06$ & $0.97 \pm 0.10$ & $0.80 \pm 0.14$ & $0.74 \pm 0.22$ \\
|
| 93 |
$\mu$ post-veto \mt-SF & $1.00 \pm 0.01$ & $0.96 \pm 0.02$ & $0.90 \pm 0.04$ & $0.98 \pm 0.07$ & $1.00 \pm 0.11$ & $0.80 \pm 0.15$ & $0.81 \pm 0.24$ \\
|
| 94 |
\hline
|
| 95 |
$\mu$ veto \mt-SF & $0.98 \pm 0.01$ & $0.99 \pm 0.01$ & $0.99 \pm 0.02$ & $1.03 \pm 0.03$ & $1.03 \pm 0.05$ & $1.01 \pm 0.08$ & $1.09 \pm 0.09$ \\
|
| 96 |
\hline
|
| 97 |
\hline
|
| 98 |
e pre-veto \mt-SF & $0.97 \pm 0.01$ & $0.93 \pm 0.02$ & $0.94 \pm 0.04$ & $0.81 \pm 0.06$ & $0.86 \pm 0.10$ & $0.95 \pm 0.17$ & $1.06 \pm 0.26$ \\
|
| 99 |
e post-veto \mt-SF & $0.94 \pm 0.01$ & $0.91 \pm 0.02$ & $0.91 \pm 0.04$ & $0.71 \pm 0.06$ & $0.82 \pm 0.10$ & $0.93 \pm 0.17$ & $1.09 \pm 0.27$ \\
|
| 100 |
\hline
|
| 101 |
e veto \mt-SF & $0.97 \pm 0.01$ & $0.98 \pm 0.01$ & $0.97 \pm 0.02$ & $0.88 \pm 0.04$ & $0.95 \pm 0.06$ & $0.98 \pm 0.08$ & $1.03 \pm 0.09$ \\
|
| 102 |
\hline
|
| 103 |
\end{tabular}}
|
| 104 |
\caption{ \mt\ peak Data/MC scale factors. The pre-veto SFs are applied to the
|
| 105 |
\ttdl\ sample, while the post-veto SFs are applied to the single
|
| 106 |
lepton samples. The veto SF is shown for comparison across channels.
|
| 107 |
The raw MC is used for backgrounds from rare processes.
|
| 108 |
The uncertainties are statistical only.
|
| 109 |
\label{tab:mtpeaksf2}}
|
| 110 |
\end{center}
|
| 111 |
\end{table}
|
| 112 |
|
| 113 |
|
| 114 |
\subsection{Uncertainty on the \wjets\ cross-section and the rare MC cross-sections}
|
| 115 |
These are taken as 50\%, uncorrelated.
|
| 116 |
The primary effect is to introduce a 50\%
|
| 117 |
uncertainty
|
| 118 |
on the $W +$ jets and rare BG
|
| 119 |
background predictions, respectively. However they also
|
| 120 |
have an effect on the other BGs via the $M_T$ peak normalization
|
| 121 |
in a way that tends to reduce the uncertainty. This is easy
|
| 122 |
to understand: if the $W$ cross-section is increased by 50\%, then
|
| 123 |
the $W$ background goes up. But the number of $M_T$ peak events
|
| 124 |
attributed to $t\bar{t}$ goes down, and since the $t\bar{t}$ BG is
|
| 125 |
scaled to the number of $t\bar{t}$ events in the peak, the $t\bar{t}$
|
| 126 |
BG goes down.
|
| 127 |
|
| 128 |
\subsection{Tail-to-peak ratios for lepton +
|
| 129 |
jets top and W events}
|
| 130 |
The tail-to-peak ratios $R_{top}$ and $R_{wjet}$ are described in Section~\ref{sec:ttp}.
|
| 131 |
The data/MC scale factors are studied in CR1 and CR2 (Sections~\ref{sec:cr1} and~\ref{sec:cr2}).
|
| 132 |
Only the scale factor for \wjets, $SFR_{wjet}$, is used, and its
|
| 133 |
uncertainty is given in Table~\ref{tab:cr1yields}.
|
| 134 |
This uncertainty affects both $R_{wjet}$ and $R_{top}$.
|
| 135 |
The additional systematic uncertainty on $R_{top}$ from the variation between optimistic and pessimistic scenarios is given in Section~\ref{sec:ttp}.
|
| 136 |
|
| 137 |
|
| 138 |
\subsection{Uncertainty on extra jet radiation for dilepton
|
| 139 |
background}
|
| 140 |
As discussed in Section~\ref{sec:jetmultiplicity}, the
|
| 141 |
jet distribution in
|
| 142 |
$t\bar{t} \to$
|
| 143 |
dilepton MC is rescaled by the factors $K_3$ and $K_4$ to make
|
| 144 |
it agree with the data. The 3\% uncertainties on $K_3$ and $K_4$
|
| 145 |
comes from data/MC statistics. This
|
| 146 |
results directly in a 3\% uncertainty on the dilepton background, which is by far
|
| 147 |
the most important one.
|
| 148 |
|
| 149 |
\subsection{Uncertainty from MC statistics}
|
| 150 |
This affects mostly the \ttll\ background estimate, which is taken
|
| 151 |
from
|
| 152 |
Monte Carlo with appropriate correction factors. This uncertainty
|
| 153 |
is negligible in the low \met\ signal regions, and grows to about
|
| 154 |
15\% in SRG.
|
| 155 |
|
| 156 |
|
| 157 |
\subsection{Uncertainty on the \ttll\ Background}
|
| 158 |
\label{sec:ttdilbkgunc}
|
| 159 |
The \ttbar\ background prediction is obtained from MC, with corrections
|
| 160 |
derived from control samples in data. The uncertainty associated with
|
| 161 |
the \ttbar\ background is derived from the level of closure of the
|
| 162 |
background prediction in CR4 (Table~\ref{tab:cr4yields}) and
|
| 163 |
CR5 (Table~\ref{tab:cr5yields}). The results from these control region
|
| 164 |
checks are shown in Figure~\ref{fig:ttdlunc}. The uncertainties assigned
|
| 165 |
to the \ttdl\ background prediction based on these tests are
|
| 166 |
5\% (SRA), 10\% (SRB), 15\% (SRC), 25\% (SRD), 40\% (SRE-G).
|
| 167 |
|
| 168 |
\begin{figure}[hbt]
|
| 169 |
\begin{center}
|
| 170 |
\includegraphics[width=0.6\linewidth]{plots/ttdilepton_uncertainty.pdf}
|
| 171 |
\caption{
|
| 172 |
\label{fig:ttdlunc}%\protect
|
| 173 |
Results of the comparison of yields in the \mt\ tail comparing the MC prediction (after
|
| 174 |
applying SFs) to data for CR4 and CR5 for all the signal
|
| 175 |
region requirements considered (A-G). The bands indicate the
|
| 176 |
systematic uncertainties assigned based on these tests,
|
| 177 |
ranging from $5\%$ for SRA to $40\%$ for SRE-G.}
|
| 178 |
\end{center}
|
| 179 |
\end{figure}
|
| 180 |
|
| 181 |
\clearpage
|
| 182 |
\subsubsection{Check of the impact of Signal Contamination}
|
| 183 |
|
| 184 |
We examine the contribution of possible signal events in the \ttll\
|
| 185 |
control regions (CR4 and CR5). It should be emphasized that these
|
| 186 |
regions are not used to apply data/MC SFs. They are used only to quantify
|
| 187 |
the level of data/MC agreement and assign a corresponding uncertainty.
|
| 188 |
As a result, if signal events were to populate these control regions
|
| 189 |
this would not lead to an increase in the predicted background.
|
| 190 |
|
| 191 |
To illustrate how much signal is expected to populate these control
|
| 192 |
regions, we examine signal points near the edge of the analysis
|
| 193 |
sensitivity (m(stop) = 450 m($\chi^0$) = 0 for T2tt, m(stop) = 450
|
| 194 |
m($\chi^0$) = 0, x=0.75 for T2bw).
|
| 195 |
Table~\ref{tab:signalcontamination} compares the expected signal
|
| 196 |
yields and the raw total MC background prediction in the control
|
| 197 |
regions with the \met\ and \mt\ requirements corresponding to SRB, SRC
|
| 198 |
and SRD (these are the signal regions that dominate the
|
| 199 |
sensitivity). The signal contamination is smaller than the uncertainty
|
| 200 |
on the dilepton background (10\%, 15\%, and 25\% for SRB, SRC, SRD, respectively) and smaller than the signal/background in
|
| 201 |
the signal regions.
|
| 202 |
Based on the fact that the CR4 and CR5 are not used to extract
|
| 203 |
data/MC scale factors and that we do not observe evidence for signal
|
| 204 |
contamination in these control regions (CR5, the control region with
|
| 205 |
larger statistical precision, actually shows a slight deficit of data w.r.t. MC), we
|
| 206 |
do not assign a correction for signal contamination in these control regions.
|
| 207 |
|
| 208 |
\begin{table}[!h]
|
| 209 |
\begin{center}
|
| 210 |
{\small
|
| 211 |
\begin{tabular}{l l||c|c|c}
|
| 212 |
\hline
|
| 213 |
\multicolumn{2}{c||}{Sample} & CR B & CR C & CR D \\
|
| 214 |
\hline
|
| 215 |
\hline
|
| 216 |
\multirow{4}{*}{CR4} & Raw MC & $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$ \\
|
| 217 |
%\hline
|
| 218 |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $2.6 \pm 0.3$ $(2\%)$ & $2.0 \pm 0.2$ $(4\%)$ & $1.4 \pm 0.2$ $(7\%)$ \\
|
| 219 |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $10.5 \pm 0.4$ $(6\%)$ &$6.1 \pm 0.3$ $(12\%)$ & $3.1 \pm 0.2$ $(16\%)$ \\
|
| 220 |
\hline
|
| 221 |
\hline
|
| 222 |
\multirow{4}{*}{CR5} & Raw MC & $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$ \\
|
| 223 |
%\hline
|
| 224 |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $10.6 \pm 0.6$ $(3\%)$ & $7.8 \pm 0.5$ $(8\%)$ & $5.4 \pm 0.4$ $(14\%)$ \\
|
| 225 |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $17.3 \pm 0.5$ $(6\%)$ &$11.3 \pm 0.4$ $(11\%)$ & $6.2 \pm 0.3$ $(16\%)$\\
|
| 226 |
\hline
|
| 227 |
\hline
|
| 228 |
\hline
|
| 229 |
\multirow{4}{*}{SIGNAL} & Raw MC & $486.3 \pm 7.8$& $164.3 \pm 4.5$& $61.5 \pm 2.8$ \\
|
| 230 |
& T2tt m(stop) = 450 m($\chi^0$) = 0 & $65.3 \pm 1.4$ $(13\%)$& $48.8 \pm 1.2$ $(30\%)$& $32.9 \pm 1.0$ $(53\%)$ \\
|
| 231 |
& T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $69.3 \pm 1.0$ $(14\%)$& $47.3 \pm 0.8$ $(29\%)$& $27.3 \pm 0.6$ $(44\%)$ \\
|
| 232 |
\hline
|
| 233 |
\end{tabular}}
|
| 234 |
\caption{ Yields in \mt\ tail comparing the raw SM MC prediction to the
|
| 235 |
yields for a few signal points on the edge of our sensitivity in the \ttll\
|
| 236 |
control regions CR4, CR5 and in the corresponding signal region.
|
| 237 |
The numbers in parenthesis are the expected signal yield divided by
|
| 238 |
the total background. The uncertainties are statistical only.
|
| 239 |
\label{tab:signalcontamination}}
|
| 240 |
\end{center}
|
| 241 |
\end{table}
|
| 242 |
|
| 243 |
%CR5 DUMP
|
| 244 |
%Total & $880.3 \pm 10.4$& $560.0 \pm 8.3$& $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$& $16.4 \pm 1.4$& $8.2 \pm 1.0$& $4.6 \pm 0.8$ \\
|
| 245 |
%\hline
|
| 246 |
%\hline
|
| 247 |
%Data & $941$& $559$& $287$& $95$& $26$& $8$& $5$& $3$ \\
|
| 248 |
%\hline
|
| 249 |
%T2tt m(stop) = 250 m($\chi^0$) = 0 & $84.3 \pm 9.2$& $61.9 \pm 7.9$& $35.7 \pm 6.0$& $5.9 \pm 2.4$& $1.0 \pm 1.0$& $1.0 \pm 1.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
|
| 250 |
%\hline
|
| 251 |
%T2tt m(stop) = 300 m($\chi^0$) = 50 & $61.4 \pm 4.7$& $53.6 \pm 4.4$& $42.0 \pm 3.9$& $14.3 \pm 2.3$& $7.2 \pm 1.6$& $1.8 \pm 0.8$& $0.7 \pm 0.5$& $0.0 \pm 0.0$ \\
|
| 252 |
%\hline
|
| 253 |
%T2tt m(stop) = 300 m($\chi^0$) = 100 & $33.3 \pm 3.5$& $28.6 \pm 3.2$& $19.2 \pm 2.6$& $6.1 \pm 1.5$& $1.8 \pm 0.8$& $0.4 \pm 0.4$& $0.4 \pm 0.4$& $0.4 \pm 0.4$ \\
|
| 254 |
%\hline
|
| 255 |
%T2tt m(stop) = 350 m($\chi^0$) = 0 & $33.4 \pm 2.2$& $29.8 \pm 2.1$& $27.3 \pm 2.0$& $15.3 \pm 1.5$& $5.6 \pm 0.9$& $1.9 \pm 0.5$& $0.3 \pm 0.2$& $0.0 \pm 0.0$ \\
|
| 256 |
%\hline
|
| 257 |
%T2tt m(stop) = 450 m($\chi^0$) = 0 & $12.0 \pm 0.6$& $11.3 \pm 0.6$& $10.6 \pm 0.6$& $7.8 \pm 0.5$& $5.4 \pm 0.4$& $3.1 \pm 0.3$& $1.8 \pm 0.2$& $0.6 \pm 0.1$ \\
|
| 258 |
%\hline
|
| 259 |
%T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0 & $48.5 \pm 1.9$& $40.2 \pm 1.7$& $33.0 \pm 1.5$& $14.4 \pm 1.0$& $5.7 \pm 0.6$& $2.7 \pm 0.4$& $1.3 \pm 0.3$& $0.5 \pm 0.2$ \\
|
| 260 |
%\hline
|
| 261 |
%T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0 & $22.3 \pm 0.6$& $20.2 \pm 0.6$& $17.3 \pm 0.5$& $11.3 \pm 0.4$& $6.2 \pm 0.3$& $3.1 \pm 0.2$& $1.3 \pm 0.1$& $0.7 \pm 0.1$ \\
|
| 262 |
%\hline
|
| 263 |
|
| 264 |
%CR4 DUMP
|
| 265 |
%\hline
|
| 266 |
%Total & $510.1 \pm 8.0$& $324.2 \pm 6.3$& $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$& $7.8 \pm 1.0$& $2.6 \pm 0.6$& $1.1 \pm 0.3$ \\
|
| 267 |
%\hline
|
| 268 |
%\hline
|
| 269 |
%Data & $462$& $289$& $169$& $45$& $10$& $7$& $5$& $3$ \\
|
| 270 |
%\hline
|
| 271 |
%T2tt m(stop) = 250 m($\chi^0$) = 0 & $37.7 \pm 6.1$& $30.9 \pm 5.5$& $18.0 \pm 4.2$& $6.0 \pm 2.5$& $2.0 \pm 1.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
|
| 272 |
%\hline
|
| 273 |
%T2tt m(stop) = 300 m($\chi^0$) = 50 & $16.6 \pm 2.4$& $14.4 \pm 2.3$& $11.3 \pm 2.0$& $5.6 \pm 1.4$& $3.2 \pm 1.1$& $1.8 \pm 0.8$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
|
| 274 |
%\hline
|
| 275 |
%T2tt m(stop) = 300 m($\chi^0$) = 100 & $9.6 \pm 1.8$& $6.4 \pm 1.5$& $4.6 \pm 1.3$& $0.7 \pm 0.5$& $0.4 \pm 0.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
|
| 276 |
%\hline
|
| 277 |
%T2tt m(stop) = 350 m($\chi^0$) = 0 & $8.2 \pm 1.1$& $7.6 \pm 1.0$& $5.7 \pm 0.9$& $3.4 \pm 0.7$& $1.9 \pm 0.5$& $0.6 \pm 0.3$& $0.3 \pm 0.2$& $0.1 \pm 0.1$ \\
|
| 278 |
%\hline
|
| 279 |
%T2tt m(stop) = 450 m($\chi^0$) = 0 & $3.1 \pm 0.3$& $2.9 \pm 0.3$& $2.6 \pm 0.3$& $2.0 \pm 0.2$& $1.4 \pm 0.2$& $1.0 \pm 0.2$& $0.4 \pm 0.1$& $0.2 \pm 0.1$ \\
|
| 280 |
%\hline
|
| 281 |
%T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0 & $52.6 \pm 1.9$& $42.6 \pm 1.7$& $32.1 \pm 1.5$& $14.7 \pm 1.0$& $5.5 \pm 0.6$& $1.9 \pm 0.4$& $0.6 \pm 0.2$& $0.3 \pm 0.1$ \\
|
| 282 |
%\hline
|
| 283 |
%T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0 & $16.9 \pm 0.5$& $14.9 \pm 0.5$& $10.5 \pm 0.4$& $6.1 \pm 0.3$& $3.1 \pm 0.2$& $1.5 \pm 0.1$& $0.6 \pm 0.1$& $0.3 \pm 0.1$ \\
|
| 284 |
%\hline
|
| 285 |
|
| 286 |
|
| 287 |
\subsubsection{Check of the uncertainty on the \ttll\ Background}
|
| 288 |
|
| 289 |
We check that the systematic uncertainty assigned to the \ttll\ background prediction
|
| 290 |
covers the uncertainty associated with
|
| 291 |
the theoretical modeling of the \ttbar\ production and decay
|
| 292 |
by comparing the background predictions obtained using
|
| 293 |
alternative MC samples. It should be noted that the full analysis is
|
| 294 |
performed with the alternative samples under consideration,
|
| 295 |
including the derivation of the various data-to-MC scale factors.
|
| 296 |
The variations considered are
|
| 297 |
|
| 298 |
\begin{itemize}
|
| 299 |
\item Top mass: The alternative values for the top mass differ
|
| 300 |
from the central value by $6~\GeV$: $m_{\mathrm{top}} = 178.5~\GeV$ and $m_{\mathrm{top}}
|
| 301 |
= 166.5~\GeV$.
|
| 302 |
\item Jet-parton matching scale: This corresponds to variations in the
|
| 303 |
scale at which the Matrix Element partons from Madgraph are matched
|
| 304 |
to Parton Shower partons from Pythia. The nominal value is
|
| 305 |
$x_q>20~\GeV$. The alternative values used are $x_q>10~\GeV$ and
|
| 306 |
$x_q>40~\GeV$.
|
| 307 |
\item Renormalization and factorization scale: The alternative samples
|
| 308 |
correspond to variations in the scale $\times 2$ and $\times 0.5$. The nominal
|
| 309 |
value for the scale used is $Q^2 = m_{\mathrm{top}}^2 +
|
| 310 |
\sum_{\mathrm{jets}} \pt^2$.
|
| 311 |
\item Alternative generators: Samples produced with different
|
| 312 |
generators, Powheg (our default) and Madgraph.
|
| 313 |
\item Modeling of taus: The alternative sample does not include
|
| 314 |
Tauola and is otherwise identical to the Powheg sample.
|
| 315 |
This effect was studied earlier using 7~TeV samples and found to be negligible.
|
| 316 |
\item The PDF uncertainty is estimated following the PDF4LHC
|
| 317 |
recommendations. The events are reweighted using alternative
|
| 318 |
PDF sets for CT10 and MSTW2008 and the uncertainties for each are derived using the
|
| 319 |
alternative eigenvector variations and the ``master equation''.
|
| 320 |
The NNPDF2.1 set with 100 replicas is also used. The central value is
|
| 321 |
determined from the mean and the uncertainty is derived from the
|
| 322 |
$1\sigma$ range. The overall uncertainty is derived from the envelope of the
|
| 323 |
alternative predictions and their uncertainties.
|
| 324 |
This effect was studied earlier using 7~TeV samples and found to be negligible.
|
| 325 |
\end{itemize}
|
| 326 |
|
| 327 |
\begin{figure}[hbt]
|
| 328 |
\begin{center}
|
| 329 |
\includegraphics[width=0.5\linewidth]{plots/n_dl_comp_SRA.pdf}%
|
| 330 |
\includegraphics[width=0.5\linewidth]{plots/n_dl_comp_SRB.pdf}
|
| 331 |
\includegraphics[width=0.5\linewidth]{plots/n_dl_comp_SRC.pdf}%
|
| 332 |
\includegraphics[width=0.5\linewidth]{plots/n_dl_comp_SRD.pdf}
|
| 333 |
\includegraphics[width=0.5\linewidth]{plots/n_dl_comp_SRE.pdf}
|
| 334 |
\caption{
|
| 335 |
\label{fig:ttllsyst}\protect
|
| 336 |
Comparison of the \ttll\ central prediction with those using
|
| 337 |
alternative MC samples. The blue band corresponds to the
|
| 338 |
total statistical error for all data and MC samples. The
|
| 339 |
alternative sample predictions are indicated by the
|
| 340 |
datapoints. The uncertainties on the alternative predictions
|
| 341 |
correspond to the uncorrelated statistical uncertainty from
|
| 342 |
the size of the alternative sample only. Note the
|
| 343 |
suppressed vertical scales.}
|
| 344 |
\end{center}
|
| 345 |
\end{figure}
|
| 346 |
|
| 347 |
|
| 348 |
\begin{table}[!h]
|
| 349 |
\begin{center}
|
| 350 |
{\footnotesize
|
| 351 |
\begin{tabular}{l||c|c|c|c|c|c|c}
|
| 352 |
\hline
|
| 353 |
$\Delta/N$ [\%] & Madgraph & Mass Up & Mass Down & Scale Up & Scale Down &
|
| 354 |
Match Up & Match Down \\
|
| 355 |
\hline
|
| 356 |
\hline
|
| 357 |
SRA & $2$ & $2$ & $5$ & $12$ & $7$ & $0$ & $2$ \\
|
| 358 |
\hline
|
| 359 |
SRB & $6$ & $0$ & $6$ & $5$ & $12$ & $5$ & $6$ \\
|
| 360 |
\hline
|
| 361 |
% SRC & $10$ & $3$ & $2$ & $12$ & $14$ & $16$ & $4$ \\
|
| 362 |
% \hline
|
| 363 |
% SRD & $10$ & $6$ & $6$ & $21$ & $15$ & $19$ & $0$ \\
|
| 364 |
% \hline
|
| 365 |
% SRE & $6$ & $17$ & $15$ & $2$ & $12$ & $17$ & $8$ \\
|
| 366 |
\hline
|
| 367 |
\end{tabular}}
|
| 368 |
\caption{ Relative difference in \ttdl\ predictions for alternative MC
|
| 369 |
samples in
|
| 370 |
the higher statistics regions SRA and SRB. These differences
|
| 371 |
are based on the central values of the predictions. For a fuller
|
| 372 |
picture
|
| 373 |
of the situation, including statistical uncertainites, see Fig.~\ref{fig:ttllsyst}.
|
| 374 |
\label{tab:fracdiff}}
|
| 375 |
\end{center}
|
| 376 |
\end{table}
|
| 377 |
|
| 378 |
|
| 379 |
In Fig.~\ref{fig:ttllsyst} we compare the alternate MC \ttll\ background predictions
|
| 380 |
for regions A through E. We can make the following observations based
|
| 381 |
on this Figure.
|
| 382 |
|
| 383 |
\begin{itemize}
|
| 384 |
\item In the tighter signal regions we are running out of
|
| 385 |
statistics.
|
| 386 |
\item Within the limited statistics, there is no evidence that the
|
| 387 |
situation changes as we go from signal region A to signal region E.
|
| 388 |
%Therefore, we assess a systematic based on the relatively high
|
| 389 |
%statistics
|
| 390 |
%test in signal region A, and apply the same systematic uncertainty
|
| 391 |
%to all other regions.
|
| 392 |
\item In signal regions B and above, the uncertainties assigned in Section~\ref{sec:ttdilbkgunc}
|
| 393 |
fully cover the alternative MC variations.
|
| 394 |
\item In order to fully (as opposed as 1$\sigma$) cover the
|
| 395 |
alternative MC variations in region A we would have to take a
|
| 396 |
systematic
|
| 397 |
uncertainty of $\approx 10\%$ instead of $5\%$. This would be driven by the
|
| 398 |
scale up/scale down variations, see Table~\ref{tab:fracdiff}.
|
| 399 |
\end{itemize}
|
| 400 |
|
| 401 |
\begin{table}[!ht]
|
| 402 |
\begin{center}
|
| 403 |
\begin{tabular}{l|c|c}
|
| 404 |
\hline
|
| 405 |
Sample
|
| 406 |
& K3 & K4\\
|
| 407 |
\hline
|
| 408 |
\hline
|
| 409 |
Powheg & $1.01 \pm 0.03$ & $0.93 \pm 0.04$ \\
|
| 410 |
Madgraph & $1.01 \pm 0.04$ & $0.92 \pm 0.04$ \\
|
| 411 |
Mass Up & $1.00 \pm 0.04$ & $0.92 \pm 0.04$ \\
|
| 412 |
Mass Down & $1.06 \pm 0.04$ & $0.99 \pm 0.05$ \\
|
| 413 |
Scale Up & $1.14 \pm 0.04$ & $1.23 \pm 0.06$ \\
|
| 414 |
Scale Down & $0.89 \pm 0.03$ & $0.74 \pm 0.03$ \\
|
| 415 |
Match Up & $1.02 \pm 0.04$ & $0.97 \pm 0.04$ \\
|
| 416 |
Match Down & $1.02 \pm 0.04$ & $0.91 \pm 0.04$ \\
|
| 417 |
\hline
|
| 418 |
\end{tabular}
|
| 419 |
\caption{$\met>100$ GeV: Data/MC scale factors used to account for differences in the
|
| 420 |
fraction of events with additional hard jets from radiation in
|
| 421 |
\ttll\ events. \label{tab:njetskfactors_met100}}
|
| 422 |
\end{center}
|
| 423 |
\end{table}
|
| 424 |
|
| 425 |
|
| 426 |
However, we have two pieces of information indicating that the
|
| 427 |
scale up/scale down variations are inconsistent with the data.
|
| 428 |
These are described below.
|
| 429 |
|
| 430 |
The first piece of information is that the jet multiplicity in the scale
|
| 431 |
up/scale down sample is the most inconsistent with the data. This is shown
|
| 432 |
in Table~\ref{tab:njetskfactors_met100}, where we tabulate the
|
| 433 |
$K_3$ and $K_4$ factors of Section~\ref{sec:jetmultiplicity} for
|
| 434 |
different \ttbar\ MC samples. The data/MC disagreement in the $N_{jets}$
|
| 435 |
distribution
|
| 436 |
for the scale up/scale down samples is also shown in Fig.~\ref{fig:dileptonnjets_scaleup}
|
| 437 |
and~\ref{fig:dileptonnjets_scaledw}. This should be compared with the
|
| 438 |
equivalent $N_{jets}$ plots for the default Powheg MC, see
|
| 439 |
Fig.~\ref{fig:dileptonnjets}, which agrees much better with data.
|
| 440 |
|
| 441 |
\begin{figure}[hbt]
|
| 442 |
\begin{center}
|
| 443 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_mueg_scaleup.pdf}
|
| 444 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_diel_scaleup.pdf}%
|
| 445 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_dimu_scaleup.pdf}
|
| 446 |
\caption{
|
| 447 |
\label{fig:dileptonnjets_scaleup}%\protect
|
| 448 |
SCALE UP: Comparison of the jet multiplicity distribution in data and MC for dilepton events in the \E-\M\
|
| 449 |
(top), \E-\E\ (bottom left) and \M-\M\ (bottom right) channels.}
|
| 450 |
\end{center}
|
| 451 |
\end{figure}
|
| 452 |
|
| 453 |
\begin{figure}[hbt]
|
| 454 |
\begin{center}
|
| 455 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_mueg_scaledw.pdf}
|
| 456 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_diel_scaledw.pdf}%
|
| 457 |
\includegraphics[width=0.5\linewidth]{plots/njets_all_met50_dimu_scaledw.pdf}
|
| 458 |
\caption{
|
| 459 |
\label{fig:dileptonnjets_scaledw}%\protect
|
| 460 |
SCALE DOWN: Comparison of the jet multiplicity distribution in data and MC for dilepton events in the \E-\M\
|
| 461 |
(top), \E-\E\ (bottom left) and \M-\M\ (bottom right) channels.}
|
| 462 |
\end{center}
|
| 463 |
\end{figure}
|
| 464 |
|
| 465 |
|
| 466 |
\clearpage
|
| 467 |
|
| 468 |
The second piece of information is that we have performed closure
|
| 469 |
tests in CR5 using the alternative MC samples. These are exactly
|
| 470 |
the same tests as the one performed in Section~\ref{sec:CR5} on the
|
| 471 |
Powheg sample. As we argued previously, this is a very powerful
|
| 472 |
test of the background calculation.
|
| 473 |
The results of this test are summarized in Table~\ref{tab:hugecr5yields}.
|
| 474 |
Concentrating on the relatively high statistics CR5A region, we see
|
| 475 |
for all \ttbar\ MC samples except scale up/scale down we obtain
|
| 476 |
closure within 1$\sigma$. The scale up/scale down tests closes
|
| 477 |
worse, only within 2$\sigma$. This again is evidence that the
|
| 478 |
scale up/scale down variations are in disagreement with the data.
|
| 479 |
|
| 480 |
\input{hugeCR5Table.tex}
|
| 481 |
|
| 482 |
Based on the two observations above, we argue that the MC
|
| 483 |
scale up/scale down variations are too extreme. We feel that
|
| 484 |
a reasonable choice would be to take one-half of the scale up/scale
|
| 485 |
down variations in our MC. This factor of 1/2 would then bring
|
| 486 |
the discrepancy in the closure test of
|
| 487 |
Table~\ref{tab:hugecr5yields} for the scale up/scale down variations
|
| 488 |
from about 2$\sigma$ to about 1$\sigma$.
|
| 489 |
|
| 490 |
Then, going back to Table~\ref{tab:fracdiff}, and reducing the scale
|
| 491 |
up/scale
|
| 492 |
down variations by a factor 2, we can see that a systematic
|
| 493 |
uncertainty
|
| 494 |
of 5\% covers the range of reasonable variations from different MC
|
| 495 |
models in SRA and SRB.
|
| 496 |
%The alternative MC models indicate that a 6\% systematic uncertainty
|
| 497 |
%covers the range of reasonable variations.
|
| 498 |
Note that this 5\% is also consistent with the level at which we are
|
| 499 |
able to test the closure of the method with alternative samples in CR5 for the high statistics
|
| 500 |
regions (Table~\ref{tab:hugecr5yields}).
|
| 501 |
The range of reasonable variations obtained with the alternative
|
| 502 |
samples are consistent with the uncertainties assigned for
|
| 503 |
the \ttll\ background based on the closure of the background
|
| 504 |
predictions and data in CR4 and CR5.
|
| 505 |
|
| 506 |
|
| 507 |
|
| 508 |
|
| 509 |
|
| 510 |
%\begin{table}[!h]
|
| 511 |
%\begin{center}
|
| 512 |
%{\footnotesize
|
| 513 |
%\begin{tabular}{l||c||c|c|c|c|c|c|c}
|
| 514 |
%\hline
|
| 515 |
%Sample & Powheg & Madgraph & Mass Up & Mass Down & Scale
|
| 516 |
%Up & Scale Down &
|
| 517 |
%Match Up & Match Down \\
|
| 518 |
%\hline
|
| 519 |
%\hline
|
| 520 |
%SRA & $579 \pm 10$ & $569 \pm 16$ & $591 \pm 18$ & $610 \pm 22$ & $651 \pm 22$ & $537 \pm 16$ & $578 \pm 18$ & $570 \pm 17$ \\
|
| 521 |
%\hline
|
| 522 |
%SRB & $328 \pm 7$ & $307 \pm 11$ & $329 \pm 13$ & $348 \pm 15$ & $344 \pm 15$ & $287 \pm 10$ & $313 \pm 13$ & $307 \pm 12$ \\
|
| 523 |
%\hline
|
| 524 |
%SRC & $111 \pm 4$ & $99 \pm 5$ & $107 \pm 7$ & $113 \pm 8$ & $124 \pm 8$ & $95 \pm 6$ & $93 \pm 6$ & $106 \pm 6$ \\
|
| 525 |
%\hline
|
| 526 |
%SRD & $39 \pm 2$ & $35 \pm 3$ & $41 \pm 4$ & $41 \pm 5$ & $47 \pm 5$ & $33 \pm 3$ & $31 \pm 3$ & $39 \pm 4$ \\
|
| 527 |
%\hline
|
| 528 |
%SRE & $14 \pm 1$ & $15 \pm 2$ & $17 \pm 3$ & $12 \pm 3$ & $15 \pm 3$ & $13 \pm 2$ & $12 \pm 2$ & $16 \pm 2$ \\
|
| 529 |
%\hline
|
| 530 |
%\end{tabular}}
|
| 531 |
%\caption{ \ttdl\ predictions for alternative MC samples. The uncertainties are statistical only.
|
| 532 |
%\label{tab:ttdlalt}}
|
| 533 |
%\end{center}
|
| 534 |
%\end{table}
|
| 535 |
|
| 536 |
|
| 537 |
|
| 538 |
|
| 539 |
%\begin{table}[!h]
|
| 540 |
%\begin{center}
|
| 541 |
%{\footnotesize
|
| 542 |
%\begin{tabular}{l||c|c|c|c|c|c|c}
|
| 543 |
%\hline
|
| 544 |
%$N \sigma$ & Madgraph & Mass Up & Mass Down & Scale Up & Scale Down &
|
| 545 |
%Match Up & Match Down \\
|
| 546 |
%\hline
|
| 547 |
%\hline
|
| 548 |
%SRA & $0.38$ & $0.42$ & $1.02$ & $2.34$ & $1.58$ & $0.01$ & $0.33$ \\
|
| 549 |
%\hline
|
| 550 |
%SRB & $1.17$ & $0.07$ & $0.98$ & $0.76$ & $2.29$ & $0.78$ & $1.11$ \\
|
| 551 |
%\hline
|
| 552 |
%SRC & $1.33$ & $0.37$ & $0.26$ & $1.24$ & $1.82$ & $1.97$ & $0.54$ \\
|
| 553 |
%\hline
|
| 554 |
%SRD & $0.82$ & $0.46$ & $0.38$ & $1.32$ & $1.27$ & $1.47$ & $0.00$ \\
|
| 555 |
%\hline
|
| 556 |
%SRE & $0.32$ & $0.75$ & $0.66$ & $0.07$ & $0.66$ & $0.83$ & $0.38$ \\
|
| 557 |
%\hline
|
| 558 |
%\end{tabular}}
|
| 559 |
%\caption{ N $\sigma$ difference in \ttdl\ predictions for alternative MC samples.
|
| 560 |
%\label{tab:nsig}}
|
| 561 |
%\end{center}
|
| 562 |
%\end{table}
|
| 563 |
|
| 564 |
|
| 565 |
%\begin{table}[!h]
|
| 566 |
%\begin{center}
|
| 567 |
%\begin{tabular}{l||c|c|c|c}
|
| 568 |
%\hline
|
| 569 |
%Av. $\Delta$ Evt. & Alt. Gen. & $\Delta$ Mass & $\Delta$ Scale
|
| 570 |
%& $\Delta$ Match \\
|
| 571 |
%\hline
|
| 572 |
%\hline
|
| 573 |
%SRA & $5.0$ ($1\%$) & $9.6$ ($2\%$) & $56.8$ ($10\%$) & $4.4$ ($1\%$) \\
|
| 574 |
%\hline
|
| 575 |
%SRB & $10.4$ ($3\%$) & $9.6$ ($3\%$) & $28.2$ ($9\%$) & $2.8$ ($1\%$) \\
|
| 576 |
%\hline
|
| 577 |
%SRC & $5.7$ ($5\%$) & $3.1$ ($3\%$) & $14.5$ ($13\%$) & $6.4$ ($6\%$) \\
|
| 578 |
%\hline
|
| 579 |
%SRD & $1.9$ ($5\%$) & $0.1$ ($0\%$) & $6.9$ ($18\%$) & $3.6$ ($9\%$) \\
|
| 580 |
%\hline
|
| 581 |
%SRE & $0.5$ ($3\%$) & $2.3$ ($16\%$) & $1.0$ ($7\%$) & $1.8$ ($12\%$) \\
|
| 582 |
%\hline
|
| 583 |
%\end{tabular}
|
| 584 |
%\caption{ Av. difference in \ttdl\ events for alternative sample pairs.
|
| 585 |
%\label{tab:devt}}
|
| 586 |
%\end{center}
|
| 587 |
%\end{table}
|
| 588 |
|
| 589 |
|
| 590 |
|
| 591 |
\clearpage
|
| 592 |
|
| 593 |
%
|
| 594 |
%
|
| 595 |
%The methodology for determining the systematics on the background
|
| 596 |
%predictions has not changed with respect to the nominal analysis.
|
| 597 |
%Because the template method has not changed, the same
|
| 598 |
%systematic uncertainty is assessed on this prediction (32\%).
|
| 599 |
%The 50\% uncertainty on the WZ and ZZ background is also unchanged.
|
| 600 |
%The systematic uncertainty in the OF background prediction based on
|
| 601 |
%e$\mu$ events has changed, due to the different composition of this
|
| 602 |
%sample after vetoing events containing b-tagged jets.
|
| 603 |
%
|
| 604 |
%As in the nominal analysis, we do not require the e$\mu$ events
|
| 605 |
%to satisfy the dilepton mass requirement and apply a scaling factor K,
|
| 606 |
%extracted from MC, to account for the fraction of e$\mu$ events
|
| 607 |
%which satisfy the dilepton mass requirement. This procedure is used
|
| 608 |
%in order to improve the statistical precision of the OF background estimate.
|
| 609 |
%
|
| 610 |
%For the selection used in the nominal analysis,
|
| 611 |
%the e$\mu$ sample is completely dominated by $t\bar{t}$
|
| 612 |
%events, and we observe that K is statistically consistent with constant with
|
| 613 |
%respect to the \MET\ requirement. However, in this analysis, the $t\bar{t}$
|
| 614 |
%background is strongly suppressed by the b-veto, and hence the non-$t\bar{t}$
|
| 615 |
%backgrounds (specifically, $Z\to\tau\tau$ and VV) become more relevant.
|
| 616 |
%At low \MET, the $Z\to\tau\tau$ background is pronounced, while $t\bar{t}$
|
| 617 |
%and VV dominate at high \MET\ (see App.~\ref{app:kinemu}).
|
| 618 |
%Therefore, the sample composition changes
|
| 619 |
%as the \MET\ requirement is varied, and as a result K depends
|
| 620 |
%on the \MET\ requirement.
|
| 621 |
%
|
| 622 |
%We thus measure K in MC separately for each
|
| 623 |
%\MET\ requirement, as displayed in Fig.~\ref{fig:kvmet} (left).
|
| 624 |
%%The systematic uncertainty on K is determined separately for each \MET\
|
| 625 |
%%requirement by comparing the relative difference in K in data vs. MC.
|
| 626 |
%The values of K used are the MC predictions
|
| 627 |
%%and the total systematic uncertainty on the OF prediction
|
| 628 |
%%as shown in
|
| 629 |
%(Table \ref{fig:kvmettable}).
|
| 630 |
%The contribution to the total OF prediction systematic uncertainty
|
| 631 |
%from K is assessed from the ratio of K in data and MC,
|
| 632 |
%shown in Fig.~\ref{fig:kvmet} (right).
|
| 633 |
%The ratio is consistent with unity to roughly 17\%,
|
| 634 |
%so we take this value as the systematic from K.
|
| 635 |
%17\% added in quadrature with 7\% from
|
| 636 |
%the electron to muon efficieny ratio
|
| 637 |
%(as assessed in the inclusive analysis)
|
| 638 |
%yields a total systematic of $\sim$18\%
|
| 639 |
%which we round up to 20\%.
|
| 640 |
%For \MET\ $>$ 150, there are no OF events in data inside the Z mass window
|
| 641 |
%so we take a systematic based on the statistical uncertainty
|
| 642 |
%of the MC prediction for K.
|
| 643 |
%This value is 25\% for \MET\ $>$ 150 GeV and 60\% for \MET\ $>$ 200 GeV.
|
| 644 |
%%Although we cannot check the value of K in data for \MET\ $>$ 150
|
| 645 |
%%because we find no OF events inside the Z mass window for this \MET\
|
| 646 |
%%cut, the overall OF yields with no dilepton mass requirement
|
| 647 |
%%agree to roughly 20\% (9 data vs 7.0 $\pm$ 1.1 MC).
|
| 648 |
%
|
| 649 |
%
|
| 650 |
%%Below Old
|
| 651 |
%
|
| 652 |
%%In reevaluating the systematics on the OF prediction, however,
|
| 653 |
%%we observed a different behavior of K as a function of \MET\
|
| 654 |
%%as was seen in the inclusive analysis.
|
| 655 |
%
|
| 656 |
%%Recall that K is the ratio of the number of \emu\ events
|
| 657 |
%%inside the Z window to the total number of \emu\ events.
|
| 658 |
%%In the inclusive analysis, it is taken from \ttbar\ MC
|
| 659 |
%%and used to scale the inclusive \emu\ yield in data.
|
| 660 |
%%The yield scaled by K is then corrected for
|
| 661 |
%%the $e$ vs $\mu$ efficiency difference to obtain the
|
| 662 |
%%final OF prediction.
|
| 663 |
%
|
| 664 |
%%Based on the plot in figure \ref{fig:kvmet},
|
| 665 |
%%we choose to use a different
|
| 666 |
%%K for each \MET\ cut and assess a systematic uncertainty
|
| 667 |
%%on the OF prediction based on the difference between
|
| 668 |
%%K in data and MC.
|
| 669 |
%%The variation of K as a function of \MET\ is caused
|
| 670 |
%%by a change in sample composition with increasing \MET.
|
| 671 |
%%At \MET\ $<$ 60 GeV, the contribution of Z plus jets is
|
| 672 |
%%not negligible (as it was in the inclusive analysis)
|
| 673 |
%%because of the b veto. (See appendix \ref{app:kinemu}.)
|
| 674 |
%%At higher \MET, \ttbar\ and diboson backgrounds dominate.
|
| 675 |
%
|
| 676 |
%
|
| 677 |
%
|
| 678 |
%
|
| 679 |
%\begin{figure}[hbt]
|
| 680 |
% \begin{center}
|
| 681 |
% \includegraphics[width=0.48\linewidth]{plots/kvmet_data_ttbm.pdf}
|
| 682 |
% \includegraphics[width=0.48\linewidth]{plots/kvmet_ratio.pdf}
|
| 683 |
% \caption{
|
| 684 |
% \label{fig:kvmet}\protect
|
| 685 |
% The left plot shows
|
| 686 |
% K as a function of \MET\ in MC (red) and data (black).
|
| 687 |
% The bin low edge corresponds to the \MET\ cut, and the
|
| 688 |
% bins are inclusive.
|
| 689 |
% The MC used is a sum of all SM MC used in the yield table of
|
| 690 |
% section \ref{sec:yields}.
|
| 691 |
% The right plot is the ratio of K in data to MC.
|
| 692 |
% The ratio is fit to a line whose slope is consistent with zero
|
| 693 |
% (the fit parameters are
|
| 694 |
% 0.9 $\pm$ 0.4 for the intercept and
|
| 695 |
% 0.001 $\pm$ 0.005 for the slope).
|
| 696 |
% }
|
| 697 |
% \end{center}
|
| 698 |
%\end{figure}
|
| 699 |
%
|
| 700 |
%
|
| 701 |
%
|
| 702 |
%\begin{table}[htb]
|
| 703 |
%\begin{center}
|
| 704 |
%\caption{\label{fig:kvmettable} The values of K used in the OF background prediction.
|
| 705 |
%The uncertainties shown are the total relative systematic used for the OF prediction,
|
| 706 |
%which is the systematic uncertainty from K added in quadrature with
|
| 707 |
%a 7\% uncertainty from the electron to muon efficieny ratio as assessed in the
|
| 708 |
%inclusive analysis.
|
| 709 |
%}
|
| 710 |
%\begin{tabular}{lcc}
|
| 711 |
%\hline
|
| 712 |
%\MET\ Cut & K & Relative Systematic \\
|
| 713 |
%\hline
|
| 714 |
%%the met zero row is used only for normalization of the money plot.
|
| 715 |
%%0 & 0.1 & \\
|
| 716 |
%30 & 0.12 & 20\% \\
|
| 717 |
%60 & 0.13 & 20\% \\
|
| 718 |
%80 & 0.12 & 20\% \\
|
| 719 |
%100 & 0.12 & 20\% \\
|
| 720 |
%150 & 0.09 & 25\% \\
|
| 721 |
%200 & 0.06 & 60\% \\
|
| 722 |
%\hline
|
| 723 |
%\end{tabular}
|
| 724 |
%\end{center}
|
| 725 |
%\end{table}
|
| 726 |
|
| 727 |
\subsection{Uncertainty from the isolated track veto}
|
| 728 |
This is the uncertainty associated with how well the isolated track
|
| 729 |
veto performance is modeled by the Monte Carlo. This uncertainty
|
| 730 |
only applies to the fraction of dilepton BG events that have
|
| 731 |
a second e/$\mu$ or a one prong $\tau \to h$, with
|
| 732 |
$P_T > 10$ GeV in $|\eta| < 2.4$. This fraction is about 1/3, see
|
| 733 |
Table~\ref{tab:trueisotrk}.
|
| 734 |
The uncertainty for these events
|
| 735 |
is 6\% and is obtained from tag-and-probe studies, see Section~\ref{sec:trkveto}.
|
| 736 |
|
| 737 |
\begin{table}[!h]
|
| 738 |
\begin{center}
|
| 739 |
{\footnotesize
|
| 740 |
\begin{tabular}{l||c|c|c|c|c|c|c}
|
| 741 |
\hline
|
| 742 |
Sample & SRA & SRB & SRC & SRD & SRE & SRF & SRG \\
|
| 743 |
\hline
|
| 744 |
\hline
|
| 745 |
$\mu$ Frac. \ttdl\ with true iso. trk. & $0.32 \pm 0.03$ & $0.30 \pm 0.03$ & $0.32 \pm 0.06$ & $0.34 \pm 0.10$ & $0.35 \pm 0.16$ & $0.40 \pm 0.24$ & $0.50 \pm 0.32$ \\
|
| 746 |
\hline
|
| 747 |
\hline
|
| 748 |
e Frac. \ttdl\ with true iso. trk. & $0.32 \pm 0.03$ & $0.31 \pm 0.04$ & $0.33 \pm 0.06$ & $0.38 \pm 0.11$ & $0.38 \pm 0.19$ & $0.60 \pm 0.31$ & $0.61 \pm 0.45$ \\
|
| 749 |
\hline
|
| 750 |
\end{tabular}}
|
| 751 |
\caption{ Fraction of \ttdl\ events with a true isolated track.
|
| 752 |
\label{tab:trueisotrk}}
|
| 753 |
\end{center}
|
| 754 |
\end{table}
|
| 755 |
|
| 756 |
\subsubsection{Isolated Track Veto: Tag and Probe Studies}
|
| 757 |
\label{sec:trkveto}
|
| 758 |
|
| 759 |
|
| 760 |
In this section we compare the performance of the isolated track veto in data and MC using tag-and-probe studies
|
| 761 |
with samples of Z$\to$ee and Z$\to\mu\mu$. The purpose of these studies is to demonstrate that the efficiency
|
| 762 |
to satisfy the isolated track veto requirements is well-reproduced in the MC, since if this were not the case
|
| 763 |
we would need to apply a data-to-MC scale factor in order to correctly
|
| 764 |
predict the \ttll\ background.
|
| 765 |
|
| 766 |
This study
|
| 767 |
addresses possible data vs. MC discrepancies for the {\bf efficiency} to identify (and reject) events with a
|
| 768 |
second {\bf genuine} lepton (e, $\mu$, or $\tau\to$1-prong). It does not address possible data vs. MC discrepancies
|
| 769 |
in the fake rate for rejecting events without a second genuine lepton; this is handled separately in the top normalization
|
| 770 |
procedure by scaling the \ttlj\ contribution to match the data in the \mt\ peak after applying the isolated track veto.
|
| 771 |
|
| 772 |
Furthermore, we test the data and MC
|
| 773 |
isolated track veto efficiencies for electrons and muons since we are using a Z tag-and-probe technique, but we do not
|
| 774 |
directly test the performance for hadronic tracks from $\tau$ decays. The performance for hadronic $\tau$ decay products
|
| 775 |
may differ from that of electrons and muons for two reasons. First, the $\tau$ may decay to a hadronic track plus one
|
| 776 |
or two $\pi^0$'s, which may decay to $\gamma\gamma$ followed by a photon conversion. As shown in Figure~\ref{fig:absiso},
|
| 777 |
the isolation distribution for charged tracks from $\tau$ decays that are not produced in association with $\pi^0$s are
|
| 778 |
consistent with that from $\E$s and $\M$s. Since events from single prong $\tau$ decays produced in association with
|
| 779 |
$\pi^0$s comprise a small fraction of the total sample, and since the kinematics of $\tau$, $\pi^0$ and $\gamma\to e^+e^-$
|
| 780 |
decays are well-understood, we currently demonstrate that the isolation is well-reproduced for electrons and muons only.
|
| 781 |
Second, hadronic tracks may undergo nuclear interactions and hence their tracks may not be reconstructed.
|
| 782 |
As discussed above, independent studies show that the MC reproduces the hadronic tracking efficiency within 4\%,
|
| 783 |
leading to a total background uncertainty of less than 0.5\% (after taking into account the fraction of the total background
|
| 784 |
due to hadronic $\tau$ decays with \pt\ $>$ 10 GeV tracks), and we hence regard this effect as negligible.
|
| 785 |
|
| 786 |
The tag-and-probe studies are performed in the full data sample, and compared with the DYJets madgraph sample.
|
| 787 |
All events must contain a tag-probe pair (details below) with opposite-sign and satisfying the Z mass requirement 76--106 GeV.
|
| 788 |
We compare the distributions of absolute track isolation for probe electrons/muons in data vs. MC. The contributions to
|
| 789 |
this isolation sum are from ambient energy in the event from underlying event, pile-up and jet activitiy, and hence do
|
| 790 |
not depend on the \pt\ of the probe lepton. We therefore restrict the probe \pt\ to be $>$ 30 GeV in order to suppress
|
| 791 |
fake backgrounds with steeply-falling \pt\ spectra. To suppress non-Z backgrounds (in particular \ttbar) we require
|
| 792 |
\met\ $<$ 30 GeV and 0 b-tagged events.
|
| 793 |
The specific criteria for tags and probes for electrons and muons are:
|
| 794 |
|
| 795 |
%We study the isolated track veto efficiency in bins of \njets.
|
| 796 |
%We are interested in events with at least 4 jets to emulate the hadronic activity in our signal sample. However since
|
| 797 |
%there are limited statistics for Z + $\geq$4 jet events, we study the isolated track performance in events with
|
| 798 |
|
| 799 |
|
| 800 |
\begin{itemize}
|
| 801 |
\item{Electrons}
|
| 802 |
|
| 803 |
\begin{itemize}
|
| 804 |
\item{Tag criteria}
|
| 805 |
|
| 806 |
\begin{itemize}
|
| 807 |
\item Electron passes full analysis ID/iso selection
|
| 808 |
\item \pt\ $>$ 30 GeV, $|\eta|<2.1$
|
| 809 |
\item Matched to the single electron trigger \verb=HLT_Ele27_WP80_v*=
|
| 810 |
\end{itemize}
|
| 811 |
|
| 812 |
\item{Probe criteria}
|
| 813 |
\begin{itemize}
|
| 814 |
\item Electron passes full analysis ID selection
|
| 815 |
\item \pt\ $>$ 30 GeV
|
| 816 |
\end{itemize}
|
| 817 |
\end{itemize}
|
| 818 |
\item{Muons}
|
| 819 |
\begin{itemize}
|
| 820 |
\item{Tag criteria}
|
| 821 |
\begin{itemize}
|
| 822 |
\item Muon passes full analysis ID/iso selection
|
| 823 |
\item \pt\ $>$ 30 GeV, $|\eta|<2.1$
|
| 824 |
\item Matched to 1 of the 2 single muon triggers
|
| 825 |
\begin{itemize}
|
| 826 |
\item \verb=HLT_IsoMu30_v*=
|
| 827 |
\item \verb=HLT_IsoMu30_eta2p1_v*=
|
| 828 |
\end{itemize}
|
| 829 |
\end{itemize}
|
| 830 |
\item{Probe criteria}
|
| 831 |
\begin{itemize}
|
| 832 |
\item Muon passes full analysis ID selection
|
| 833 |
\item \pt\ $>$ 30 GeV
|
| 834 |
\end{itemize}
|
| 835 |
\end{itemize}
|
| 836 |
\end{itemize}
|
| 837 |
|
| 838 |
The absolute track isolation distributions for passing probes are displayed in Fig.~\ref{fig:tnp}. In general we observe
|
| 839 |
good agreement between data and MC. To be more quantitative, we compare the data vs. MC efficiencies to satisfy
|
| 840 |
absolute track isolation requirements varying from $>$ 1 GeV to $>$ 5 GeV, as summarized in Table~\ref{tab:isotrk}.
|
| 841 |
In the $\geq 0$ and $\geq 1$ jet bins where the efficiencies can be tested with statistical precision, the data and MC
|
| 842 |
efficiencies agree within 6\%, and we apply this as a systematic uncertainty on the isolated track veto efficiency.
|
| 843 |
For the higher jet multiplicity bins the statistical precision decreases, but we do not observe any evidence for
|
| 844 |
a data vs. MC discrepancy in the isolated track veto efficiency.
|
| 845 |
|
| 846 |
|
| 847 |
%This is because our analysis requirement is relative track isolation $<$ 0.1, and m
|
| 848 |
%This requirement is chosen because most of the tracks rejected by the isolated
|
| 849 |
%track veto have a \pt\ near the 10 GeV threshold, and our analysis requirement is relative track isolation $<$ 1 GeV.
|
| 850 |
|
| 851 |
\begin{figure}[hbt]
|
| 852 |
\begin{center}
|
| 853 |
\includegraphics[width=0.3\linewidth]{plots/el_tkiso_0j.pdf}%
|
| 854 |
\includegraphics[width=0.3\linewidth]{plots/mu_tkiso_0j.pdf}
|
| 855 |
\includegraphics[width=0.3\linewidth]{plots/el_tkiso_1j.pdf}%
|
| 856 |
\includegraphics[width=0.3\linewidth]{plots/mu_tkiso_1j.pdf}
|
| 857 |
\includegraphics[width=0.3\linewidth]{plots/el_tkiso_2j.pdf}%
|
| 858 |
\includegraphics[width=0.3\linewidth]{plots/mu_tkiso_2j.pdf}
|
| 859 |
\includegraphics[width=0.3\linewidth]{plots/el_tkiso_3j.pdf}%
|
| 860 |
\includegraphics[width=0.3\linewidth]{plots/mu_tkiso_3j.pdf}
|
| 861 |
\includegraphics[width=0.3\linewidth]{plots/el_tkiso_4j.pdf}%
|
| 862 |
\includegraphics[width=0.3\linewidth]{plots/mu_tkiso_4j.pdf}
|
| 863 |
\caption{
|
| 864 |
\label{fig:tnp} Comparison of the absolute track isolation in data vs. MC for electrons (left) and muons (right)
|
| 865 |
for events with the \njets\ requirement varied from \njets\ $\geq$ 0 to \njets\ $\geq$ 4.
|
| 866 |
}
|
| 867 |
\end{center}
|
| 868 |
\end{figure}
|
| 869 |
|
| 870 |
\clearpage
|
| 871 |
|
| 872 |
\begin{table}[!ht]
|
| 873 |
\begin{center}
|
| 874 |
\begin{tabular}{l|c|c|c|c|c}
|
| 875 |
|
| 876 |
%Electrons:
|
| 877 |
%Selection : ((((((((((abs(tagAndProbeMass-91)<15)&&(qProbe*qTag<0))&&((eventSelection&1)==1))&&(abs(tag->eta())<2.1))&&(tag->pt()>30.0))&&(HLT_Ele27_WP80_tag > 0))&&(met<30))&&(nbl==0))&&((leptonSelection&8)==8))&&(probe->pt()>30))&&(drprobe<0.05)
|
| 878 |
%Total MC yields : 2497277
|
| 879 |
%Total DATA yields : 2649453
|
| 880 |
%Muons:
|
| 881 |
%Selection : ((((((((((abs(tagAndProbeMass-91)<15)&&(qProbe*qTag<0))&&((eventSelection&2)==2))&&(abs(tag->eta())<2.1))&&(tag->pt()>30.0))&&(HLT_IsoMu24_tag > 0))&&(met<30))&&(nbl==0))&&((leptonSelection&65536)==65536))&&(probe->pt()>30))&&(drprobe<0.05)
|
| 882 |
%Total MC yields : 3749863
|
| 883 |
%Total DATA yields : 4210022
|
| 884 |
%Info in <TCanvas::MakeDefCanvas>: created default TCanvas with name c1
|
| 885 |
%Info in <TCanvas::Print>: pdf file plots/nvtx.pdf has been created
|
| 886 |
|
| 887 |
\hline
|
| 888 |
\hline
|
| 889 |
e + $\geq$0 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 890 |
\hline
|
| 891 |
data & 0.098 $\pm$ 0.0002 & 0.036 $\pm$ 0.0001 & 0.016 $\pm$ 0.0001 & 0.009 $\pm$ 0.0001 & 0.006 $\pm$ 0.0000 \\
|
| 892 |
mc & 0.097 $\pm$ 0.0002 & 0.034 $\pm$ 0.0001 & 0.016 $\pm$ 0.0001 & 0.009 $\pm$ 0.0001 & 0.005 $\pm$ 0.0000 \\
|
| 893 |
data/mc & 1.00 $\pm$ 0.00 & 1.04 $\pm$ 0.00 & 1.04 $\pm$ 0.01 & 1.03 $\pm$ 0.01 & 1.02 $\pm$ 0.01 \\
|
| 894 |
|
| 895 |
\hline
|
| 896 |
\hline
|
| 897 |
$\mu$ + $\geq$0 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 898 |
\hline
|
| 899 |
data & 0.094 $\pm$ 0.0001 & 0.034 $\pm$ 0.0001 & 0.016 $\pm$ 0.0001 & 0.009 $\pm$ 0.0000 & 0.006 $\pm$ 0.0000 \\
|
| 900 |
mc & 0.093 $\pm$ 0.0001 & 0.033 $\pm$ 0.0001 & 0.015 $\pm$ 0.0001 & 0.009 $\pm$ 0.0000 & 0.006 $\pm$ 0.0000 \\
|
| 901 |
data/mc & 1.01 $\pm$ 0.00 & 1.03 $\pm$ 0.00 & 1.03 $\pm$ 0.01 & 1.03 $\pm$ 0.01 & 1.02 $\pm$ 0.01 \\
|
| 902 |
|
| 903 |
\hline
|
| 904 |
\hline
|
| 905 |
e + $\geq$1 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 906 |
\hline
|
| 907 |
data & 0.110 $\pm$ 0.0005 & 0.044 $\pm$ 0.0003 & 0.022 $\pm$ 0.0002 & 0.014 $\pm$ 0.0002 & 0.009 $\pm$ 0.0002 \\
|
| 908 |
mc & 0.110 $\pm$ 0.0005 & 0.042 $\pm$ 0.0003 & 0.021 $\pm$ 0.0002 & 0.013 $\pm$ 0.0002 & 0.009 $\pm$ 0.0001 \\
|
| 909 |
data/mc & 1.00 $\pm$ 0.01 & 1.04 $\pm$ 0.01 & 1.06 $\pm$ 0.02 & 1.08 $\pm$ 0.02 & 1.06 $\pm$ 0.03 \\
|
| 910 |
|
| 911 |
\hline
|
| 912 |
\hline
|
| 913 |
$\mu$ + $\geq$1 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 914 |
\hline
|
| 915 |
data & 0.106 $\pm$ 0.0004 & 0.043 $\pm$ 0.0003 & 0.023 $\pm$ 0.0002 & 0.014 $\pm$ 0.0002 & 0.010 $\pm$ 0.0001 \\
|
| 916 |
mc & 0.106 $\pm$ 0.0004 & 0.042 $\pm$ 0.0003 & 0.021 $\pm$ 0.0002 & 0.013 $\pm$ 0.0002 & 0.009 $\pm$ 0.0001 \\
|
| 917 |
data/mc & 1.00 $\pm$ 0.01 & 1.04 $\pm$ 0.01 & 1.06 $\pm$ 0.01 & 1.08 $\pm$ 0.02 & 1.07 $\pm$ 0.02 \\
|
| 918 |
|
| 919 |
\hline
|
| 920 |
\hline
|
| 921 |
e + $\geq$2 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 922 |
\hline
|
| 923 |
data & 0.117 $\pm$ 0.0012 & 0.050 $\pm$ 0.0008 & 0.026 $\pm$ 0.0006 & 0.017 $\pm$ 0.0005 & 0.012 $\pm$ 0.0004 \\
|
| 924 |
mc & 0.120 $\pm$ 0.0012 & 0.048 $\pm$ 0.0008 & 0.025 $\pm$ 0.0006 & 0.016 $\pm$ 0.0005 & 0.011 $\pm$ 0.0004 \\
|
| 925 |
data/mc & 0.97 $\pm$ 0.01 & 1.05 $\pm$ 0.02 & 1.05 $\pm$ 0.03 & 1.07 $\pm$ 0.04 & 1.07 $\pm$ 0.05 \\
|
| 926 |
|
| 927 |
\hline
|
| 928 |
\hline
|
| 929 |
$\mu$ + $\geq$2 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 930 |
\hline
|
| 931 |
data & 0.111 $\pm$ 0.0010 & 0.048 $\pm$ 0.0007 & 0.026 $\pm$ 0.0005 & 0.018 $\pm$ 0.0004 & 0.013 $\pm$ 0.0004 \\
|
| 932 |
mc & 0.115 $\pm$ 0.0010 & 0.048 $\pm$ 0.0006 & 0.025 $\pm$ 0.0005 & 0.016 $\pm$ 0.0004 & 0.012 $\pm$ 0.0003 \\
|
| 933 |
data/mc & 0.97 $\pm$ 0.01 & 1.01 $\pm$ 0.02 & 1.04 $\pm$ 0.03 & 1.09 $\pm$ 0.04 & 1.09 $\pm$ 0.04 \\
|
| 934 |
|
| 935 |
\hline
|
| 936 |
\hline
|
| 937 |
e + $\geq$3 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 938 |
\hline
|
| 939 |
data & 0.123 $\pm$ 0.0031 & 0.058 $\pm$ 0.0022 & 0.034 $\pm$ 0.0017 & 0.023 $\pm$ 0.0014 & 0.017 $\pm$ 0.0012 \\
|
| 940 |
mc & 0.131 $\pm$ 0.0030 & 0.055 $\pm$ 0.0020 & 0.030 $\pm$ 0.0015 & 0.020 $\pm$ 0.0013 & 0.015 $\pm$ 0.0011 \\
|
| 941 |
data/mc & 0.94 $\pm$ 0.03 & 1.06 $\pm$ 0.06 & 1.14 $\pm$ 0.08 & 1.16 $\pm$ 0.10 & 1.17 $\pm$ 0.12 \\
|
| 942 |
|
| 943 |
\hline
|
| 944 |
\hline
|
| 945 |
$\mu$ + $\geq$3 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 946 |
\hline
|
| 947 |
data & 0.121 $\pm$ 0.0025 & 0.055 $\pm$ 0.0018 & 0.033 $\pm$ 0.0014 & 0.022 $\pm$ 0.0011 & 0.017 $\pm$ 0.0010 \\
|
| 948 |
mc & 0.120 $\pm$ 0.0024 & 0.052 $\pm$ 0.0016 & 0.029 $\pm$ 0.0012 & 0.019 $\pm$ 0.0010 & 0.014 $\pm$ 0.0009 \\
|
| 949 |
data/mc & 1.01 $\pm$ 0.03 & 1.06 $\pm$ 0.05 & 1.14 $\pm$ 0.07 & 1.14 $\pm$ 0.08 & 1.16 $\pm$ 0.10 \\
|
| 950 |
|
| 951 |
\hline
|
| 952 |
\hline
|
| 953 |
e + $\geq$4 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 954 |
\hline
|
| 955 |
data & 0.129 $\pm$ 0.0080 & 0.070 $\pm$ 0.0061 & 0.044 $\pm$ 0.0049 & 0.031 $\pm$ 0.0042 & 0.021 $\pm$ 0.0034 \\
|
| 956 |
mc & 0.132 $\pm$ 0.0075 & 0.059 $\pm$ 0.0053 & 0.035 $\pm$ 0.0041 & 0.025 $\pm$ 0.0035 & 0.017 $\pm$ 0.0029 \\
|
| 957 |
data/mc & 0.98 $\pm$ 0.08 & 1.18 $\pm$ 0.15 & 1.26 $\pm$ 0.20 & 1.24 $\pm$ 0.24 & 1.18 $\pm$ 0.28 \\
|
| 958 |
|
| 959 |
\hline
|
| 960 |
\hline
|
| 961 |
$\mu$ + $\geq$4 jets & $>$ 1 GeV & $>$ 2 GeV & $>$ 3 GeV & $>$ 4 GeV & $>$ 5 GeV \\
|
| 962 |
\hline
|
| 963 |
data & 0.136 $\pm$ 0.0067 & 0.064 $\pm$ 0.0048 & 0.041 $\pm$ 0.0039 & 0.029 $\pm$ 0.0033 & 0.024 $\pm$ 0.0030 \\
|
| 964 |
mc & 0.130 $\pm$ 0.0063 & 0.065 $\pm$ 0.0046 & 0.035 $\pm$ 0.0034 & 0.020 $\pm$ 0.0026 & 0.013 $\pm$ 0.0022 \\
|
| 965 |
data/mc & 1.04 $\pm$ 0.07 & 0.99 $\pm$ 0.10 & 1.19 $\pm$ 0.16 & 1.47 $\pm$ 0.25 & 1.81 $\pm$ 0.37 \\
|
| 966 |
|
| 967 |
\hline
|
| 968 |
\hline
|
| 969 |
|
| 970 |
\end{tabular}
|
| 971 |
\caption{\label{tab:isotrk} Comparison of the data vs. MC efficiencies to satisfy the indicated requirements
|
| 972 |
on the absolute track isolation, and the ratio of these two efficiencies. Results are indicated separately for electrons and muons and for various
|
| 973 |
jet multiplicity requirements.}
|
| 974 |
\end{center}
|
| 975 |
\end{table}
|
| 976 |
|
| 977 |
\clearpage
|
| 978 |
\subsection{Summary of uncertainties}
|
| 979 |
\label{sec:bgunc-bottomline}
|
| 980 |
|
| 981 |
The contribution from each source to the total uncertainty on the background yield is given in Tables~\ref{tab:relativeuncertaintycomponents} and~\ref{tab:uncertaintycomponents} for the relative and absolute uncertainties, respectively. In the low-\met\ regions the dominant uncertainty comes from the top tail-to-peak ratio, $R_{top}$ (Section~\ref{sec:ttp}), while in the high-\met\ regions the \ttll\ systematic uncertainty dominates (Section~\ref{sec:ttdilbkgunc}).
|
| 982 |
|
| 983 |
\input{uncertainties_table.tex}
|
| 984 |
|
| 985 |
|
| 986 |
|
| 987 |
|
| 988 |
|
| 989 |
%Figure.~\ref{fig:reliso} compares the relative track isolation
|
| 990 |
%for events with a track with $\pt > 10~\GeV$ in addition to a selected
|
| 991 |
%muon for $\Z+4$ jet events and various \ttll\ components. The
|
| 992 |
%isolation distributions show significant differences, particularly
|
| 993 |
%between the leptons from a \W\ or \Z\ decay and the tracks arising
|
| 994 |
%from $\tau$ decays. As can also be seen in the figure, the \pt\
|
| 995 |
%distribution for the various categories of tracks is different, where
|
| 996 |
%the decay products from $\tau$s are significantly softer. Since the
|
| 997 |
%\pt\ enters the denominator of the isolation definition and hence
|
| 998 |
%alters the isolation variable...
|
| 999 |
|
| 1000 |
%\begin{figure}[hbt]
|
| 1001 |
% \begin{center}
|
| 1002 |
% \includegraphics[width=0.5\linewidth]{plots/pfiso_njets4_log.png}%
|
| 1003 |
% \includegraphics[width=0.5\linewidth]{plots/pfpt_njets4.png}
|
| 1004 |
% \caption{
|
| 1005 |
% \label{fig:reliso}%\protect
|
| 1006 |
% Comparison of relative track isolation variable for PF cand probe in Z+jets and ttbar
|
| 1007 |
% Z+Jets and ttbar dilepton have similar isolation distributions
|
| 1008 |
% ttbar with leptonic and single prong taus tend to be less
|
| 1009 |
% isolated. The difference in the isolation can be attributed
|
| 1010 |
% to the different \pt\ distribution of the samples, since
|
| 1011 |
% $\tau$ decay products tend to be softer than leptons arising
|
| 1012 |
% from \W\ or \Z\ decays.}
|
| 1013 |
% \end{center}
|
| 1014 |
%\end{figure}
|
| 1015 |
|
| 1016 |
% \includegraphics[width=0.5\linewidth]{plots/pfabsiso_njets4_log.png}
|
| 1017 |
|
| 1018 |
|
| 1019 |
%BEGIN SECTION TO WRITE OUT
|
| 1020 |
%In detail, the procedure to correct the dilepton background is:
|
| 1021 |
|
| 1022 |
%\begin{itemize}
|
| 1023 |
%\item Using tag-and-probe studies, we plot the distribution of {\bf absolute} track isolation for identified probe electrons
|
| 1024 |
%and muons {\bf TODO: need to compare the e vs. $\mu$ track iso distributions, they might differ due to e$\to$e$\gamma$}.
|
| 1025 |
%\item We verify that the distribution of absolute track isolation does not depend on the \pt\ of the probe lepton.
|
| 1026 |
%This is due to the fact that this isolation is from ambient PU and jet activity in the event, which is uncorrelated with
|
| 1027 |
%the lepton \pt {\bf TODO: verify this in data and MC.}.
|
| 1028 |
%\item Our requirement is {\bf relative} track isolation $<$ 0.1. For a given \ttll\ MC event, we determine the \pt of the 2nd
|
| 1029 |
%lepton and translate this to find the corresponding requirement on the {\bf absolute} track isolation, which is simply $0.1\times$\pt.
|
| 1030 |
%\item We measure the efficiency to satisfy this requirement in data and MC, and define a scale-factor $SF_{\epsilon(trk)}$ which
|
| 1031 |
%is the ratio of the data-to-MC efficiencies. This scale-factor is applied to the \ttll\ MC event.
|
| 1032 |
%\item {\bf THING 2 we are unsure about: we can measure this SF for electrons and for muons, but we can't measure it for hadronic
|
| 1033 |
%tracks from $\tau$ decays. Verena has showed that the absolute track isolation distribution in hadronic $\tau$ tracks is harder due
|
| 1034 |
%to $\pi^0\to\gamma\gamma$ with $\gamma\to e^+e^-$.}
|
| 1035 |
%\end{itemize}
|
| 1036 |
%END SECTION TO WRITE OUT
|
| 1037 |
|
| 1038 |
|
| 1039 |
%{\bf fix me: What you have written in the next paragraph does not
|
| 1040 |
%explain how $\epsilon_{fake}$ is measured.
|
| 1041 |
%Why not measure $\epsilon_{fake}$ in the b-veto region?}
|
| 1042 |
|
| 1043 |
%A measurement of the $\epsilon_{fake}$ in data is non-trivial. However, it is
|
| 1044 |
%possible to correct for differences in the $\epsilon_{fake}$ between data and MC by
|
| 1045 |
%applying an additional scale factor for the single lepton background
|
| 1046 |
%alone, using the sample in the \mt\ peak region. This scale factor is determined after applying the isolated track
|
| 1047 |
%veto and after subtracting the \ttll\ component, corrected for the
|
| 1048 |
%isolation efficiency derived previously.
|
| 1049 |
%As shown in Figure~\ref{fig:vetoeffcomp}, the efficiency for selecting an
|
| 1050 |
%isolated track in single lepton events is independent of \mt\, so the use of
|
| 1051 |
%an overall scale factor is justified to estimate the contribution in
|
| 1052 |
%the \mt\ tail.
|
| 1053 |
%
|
| 1054 |
%\begin{figure}[hbt]
|
| 1055 |
% \begin{center}
|
| 1056 |
% \includegraphics[width=0.5\linewidth]{plots/vetoeff_comp.png}
|
| 1057 |
% \caption{
|
| 1058 |
% \label{fig:vetoeffcomp}%\protect
|
| 1059 |
% Efficiency for selecting an isolated track comparing
|
| 1060 |
% single lepton \ttlj\ and dilepton \ttll\ events in MC and
|
| 1061 |
% data as a function of \mt. The
|
| 1062 |
% efficiencies in \ttlj\ and \ttll\ exhibit no dependence on
|
| 1063 |
% \mt\, while the data ranges between the two. This behavior
|
| 1064 |
% is expected since the low \mt\ region is predominantly \ttlj, while the
|
| 1065 |
% high \mt\ region contains mostly \ttll\ events.}
|
| 1066 |
% \end{center}
|
| 1067 |
%\end{figure}
|
| 1068 |
|
| 1069 |
|
| 1070 |
|
| 1071 |
% THIS NEEDS TO BE WRITTEN
|
