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Revision 1.28 by benhoob, Wed Oct 31 17:45:34 2012 UTC

# Line 14 | Line 14 | The calculation is done for each signal
14   region,
15   for electrons and muons separately.
16  
17 < The choice to normalizing to the peak region of $M_T$ has the
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,
# Line 25 | Line 25 | 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 BG source is tabulated in
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 < First, however, we discuss the uncertainties one-by-one and we comment
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  
# Line 37 | Line 37 | 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.
40 > different $M_T$ regions used as control).
41   Since
42 < the major BG, eg, $t\bar{t}$ are normalized to the peak regions, this
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.
# Line 47 | Line 47 | in the $M_T$ peak regions.  This is also
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 statistical uncertainties starts
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  
# Line 58 | Line 58 | This choice affects the scale factors of
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
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}.  
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  
# Line 111 | Line 111 | e veto \mt-SF      & $0.97 \pm 0.01$ & $
111   \end{table}
112  
113  
114 < \subsection{Uncertainty on the Wjets cross-section and the rare MC cross-sections}
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
# Line 125 | Line 125 | attributed to $t\bar{t}$ goes down, and
125   scaled to the number of $t\bar{t}$ events in the peak, the $t\bar{t}$
126   BG goes down.  
127  
128 < \subsection{Scale factors for the tail-to-peak ratios for lepton +
128 > \subsection{Tail-to-peak ratios for lepton +
129    jets top and W events}
130 < These tail-to-peak ratios are described in Section~\ref{sec:ttp}.
131 < They are studied in CR1 and CR2.  The studies are described
132 < in Sections~\ref{sec:cr1} and~\ref{sec:cr2}), respectively, where
133 < we also give the uncertainty on the scale factors.  See
134 < Tables~\ref{tab:cr1yields}
135 < and~\ref{tab:cr2yields}, scale factors $SFR_{wjet}$ and $SFR_{top})$.
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}
# Line 142 | Line 143 | $t\bar{t} \to$
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 < result directly in a 3\% uncertainty on the dilepton BG, which is by far
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  
149 \subsection{Uncertainty on the \ttll\ Acceptance}
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 theoretical modeling of the \ttbar\ production and decay is
162 < estimated by comparing the background predictions obtained using
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 for T2bw with x=0.75 and m(stop) = 350
195 > m($\chi^0$) = 0 for T2bw with x=0.5).
196 > Table~\ref{tab:signalcontamination} compares the expected signal
197 > yields and the raw total MC background prediction in the control
198 > regions with the \met\ and \mt\ requirements corresponding to SRB, SRC
199 > and SRD (these are the signal regions that dominate the
200 > sensitivity). The signal contamination is smaller than the uncertainty
201 > on the dilepton background and smaller than the signal/background in
202 > the signal regions, with the exception of the T2bw scenario with x=0.5.
203 > However, based on the fact that the CR4 and CR5 are not used to extract
204 > data/MC scale factors and that we do not observe evidence for signal
205 > contamination in these control regions (CR5, the control region with
206 > larger statistical precision, actually shows a slight deficit of data w.r.t. MC), we
207 > do not assign a correction for signal contamination in these control regions.
208 >
209 > \begin{table}[!h]
210 > \begin{center}
211 > {\small
212 > \begin{tabular}{l l||c|c|c}
213 > \hline
214 > \multicolumn{2}{c||}{Sample}              & CR B & CR C & CR D \\
215 > \hline
216 > \hline
217 > \multirow{4}{*}{CR4} & Raw MC            & $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$ \\
218 > %\hline
219 > & T2tt m(stop) = 450 m($\chi^0$) = 0  & $2.6 \pm 0.3$ $(2\%)$ & $2.0 \pm 0.2$ $(4\%)$ & $1.4 \pm 0.2$ $(7\%)$ \\
220 > & T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $10.5 \pm 0.4$ $(6\%)$ &$6.1 \pm 0.3$ $(12\%)$ & $3.1 \pm 0.2$ $(16\%)$ \\
221 > & T2bw x=0.5  m(stop) = 350 m($\chi^0$) = 0     & $32.1 \pm 1.5$ $(19\%)$ & $14.7 \pm 1.0$ $(29\%)$ & $5.5 \pm 0.6$ $(28\%)$ \\
222 > \hline
223 > \hline
224 > \multirow{4}{*}{CR5} & Raw MC            & $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$ \\
225 > %\hline
226 > & T2tt m(stop) = 450 m($\chi^0$) = 0  & $10.6 \pm 0.6$ $(3\%)$ & $7.8 \pm 0.5$ $(8\%)$ & $5.4 \pm 0.4$ $(14\%)$ \\
227 > & T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0 & $17.3 \pm 0.5$ $(6\%)$ &$11.3 \pm 0.4$ $(11\%)$ & $6.2 \pm 0.3$ $(16\%)$\\
228 > & T2bw x=0.5  m(stop) = 350 m($\chi^0$) = 0     & $33.0 \pm 1.5$ $(11\%)$& $14.4 \pm 1.0$ $(14\%)$& $5.7 \pm 0.6$ $(15\%)$ \\
229 > \hline
230 > \hline
231 > \hline
232 > \multirow{4}{*}{SIGNAL} & Raw MC                 & $486.3 \pm 7.8$& $164.3 \pm 4.5$& $61.5 \pm 2.8$ \\
233 > & T2tt m(stop) = 450 m($\chi^0$) = 0    & $65.3 \pm 1.4$ $(13\%)$& $48.8 \pm 1.2$ $(30\%)$& $32.9 \pm 1.0$ $(53\%)$ \\
234 > & T2bw x=0.75 m(stop) = 450 m($\chi^0$) = 0     & $69.3 \pm 1.0$ $(14\%)$& $47.3 \pm 0.8$ $(29\%)$& $27.3 \pm 0.6$ $(44\%)$ \\
235 > & T2bw x=0.5  m(stop) = 350 m($\chi^0$) = 0     & $105.5 \pm 2.8$ $(22\%)$& $44.6 \pm 1.8$ $(27\%)$& $15.9 \pm 1.1$ $(26\%)$ \\
236 > \hline
237 > \end{tabular}}
238 > \caption{ Yields in \mt\ tail comparing the raw SM MC prediction to the
239 >  yields for a few signal points on the edge of our sensitivity in the \ttll\
240 >  control regions CR4, CR5 and in the corresponding signal region.
241 >  The numbers in parenthesis are the expected signal yield divided by
242 >  the total background. The uncertainties are statistical only.
243 > \label{tab:signalcontamination}}
244 > \end{center}
245 > \end{table}
246 >
247 > %CR5 DUMP
248 > %Total           & $880.3 \pm 10.4$& $560.0 \pm 8.3$& $306.5 \pm 6.2$& $101.8 \pm 3.6$& $38.0 \pm 2.2$& $16.4 \pm 1.4$& $8.2 \pm 1.0$& $4.6 \pm 0.8$ \\
249 > %\hline
250 > %\hline
251 > %Data            & $941$& $559$& $287$& $95$& $26$& $8$& $5$& $3$ \\
252 > %\hline
253 > %T2tt m(stop) = 250 m($\chi^0$) = 0     & $84.3 \pm 9.2$& $61.9 \pm 7.9$& $35.7 \pm 6.0$& $5.9 \pm 2.4$& $1.0 \pm 1.0$& $1.0 \pm 1.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
254 > %\hline
255 > %T2tt m(stop) = 300 m($\chi^0$) = 50    & $61.4 \pm 4.7$& $53.6 \pm 4.4$& $42.0 \pm 3.9$& $14.3 \pm 2.3$& $7.2 \pm 1.6$& $1.8 \pm 0.8$& $0.7 \pm 0.5$& $0.0 \pm 0.0$ \\
256 > %\hline
257 > %T2tt m(stop) = 300 m($\chi^0$) = 100   & $33.3 \pm 3.5$& $28.6 \pm 3.2$& $19.2 \pm 2.6$& $6.1 \pm 1.5$& $1.8 \pm 0.8$& $0.4 \pm 0.4$& $0.4 \pm 0.4$& $0.4 \pm 0.4$ \\
258 > %\hline
259 > %T2tt m(stop) = 350 m($\chi^0$) = 0     & $33.4 \pm 2.2$& $29.8 \pm 2.1$& $27.3 \pm 2.0$& $15.3 \pm 1.5$& $5.6 \pm 0.9$& $1.9 \pm 0.5$& $0.3 \pm 0.2$& $0.0 \pm 0.0$ \\
260 > %\hline
261 > %T2tt m(stop) = 450 m($\chi^0$) = 0     & $12.0 \pm 0.6$& $11.3 \pm 0.6$& $10.6 \pm 0.6$& $7.8 \pm 0.5$& $5.4 \pm 0.4$& $3.1 \pm 0.3$& $1.8 \pm 0.2$& $0.6 \pm 0.1$ \\
262 > %\hline
263 > %T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0       & $48.5 \pm 1.9$& $40.2 \pm 1.7$& $33.0 \pm 1.5$& $14.4 \pm 1.0$& $5.7 \pm 0.6$& $2.7 \pm 0.4$& $1.3 \pm 0.3$& $0.5 \pm 0.2$ \\
264 > %\hline
265 > %T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0      & $22.3 \pm 0.6$& $20.2 \pm 0.6$& $17.3 \pm 0.5$& $11.3 \pm 0.4$& $6.2 \pm 0.3$& $3.1 \pm 0.2$& $1.3 \pm 0.1$& $0.7 \pm 0.1$ \\
266 > %\hline
267 >
268 > %CR4 DUMP
269 > %\hline
270 > %Total           & $510.1 \pm 8.0$& $324.2 \pm 6.3$& $168.2 \pm 4.5$& $51.5 \pm 2.5$& $19.6 \pm 1.5$& $7.8 \pm 1.0$& $2.6 \pm 0.6$& $1.1 \pm 0.3$ \\
271 > %\hline
272 > %\hline
273 > %Data            & $462$& $289$& $169$& $45$& $10$& $7$& $5$& $3$ \\
274 > %\hline
275 > %T2tt m(stop) = 250 m($\chi^0$) = 0     & $37.7 \pm 6.1$& $30.9 \pm 5.5$& $18.0 \pm 4.2$& $6.0 \pm 2.5$& $2.0 \pm 1.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
276 > %\hline
277 > %T2tt m(stop) = 300 m($\chi^0$) = 50    & $16.6 \pm 2.4$& $14.4 \pm 2.3$& $11.3 \pm 2.0$& $5.6 \pm 1.4$& $3.2 \pm 1.1$& $1.8 \pm 0.8$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
278 > %\hline
279 > %T2tt m(stop) = 300 m($\chi^0$) = 100   & $9.6 \pm 1.8$& $6.4 \pm 1.5$& $4.6 \pm 1.3$& $0.7 \pm 0.5$& $0.4 \pm 0.4$& $0.0 \pm 0.0$& $0.0 \pm 0.0$& $0.0 \pm 0.0$ \\
280 > %\hline
281 > %T2tt m(stop) = 350 m($\chi^0$) = 0     & $8.2 \pm 1.1$& $7.6 \pm 1.0$& $5.7 \pm 0.9$& $3.4 \pm 0.7$& $1.9 \pm 0.5$& $0.6 \pm 0.3$& $0.3 \pm 0.2$& $0.1 \pm 0.1$ \\
282 > %\hline
283 > %T2tt m(stop) = 450 m($\chi^0$) = 0     & $3.1 \pm 0.3$& $2.9 \pm 0.3$& $2.6 \pm 0.3$& $2.0 \pm 0.2$& $1.4 \pm 0.2$& $1.0 \pm 0.2$& $0.4 \pm 0.1$& $0.2 \pm 0.1$ \\
284 > %\hline
285 > %T2bw m(stop) = 350 x=0.5 m($\chi^0$) = 0       & $52.6 \pm 1.9$& $42.6 \pm 1.7$& $32.1 \pm 1.5$& $14.7 \pm 1.0$& $5.5 \pm 0.6$& $1.9 \pm 0.4$& $0.6 \pm 0.2$& $0.3 \pm 0.1$ \\
286 > %\hline
287 > %T2bw m(stop) = 450 x=0.75 m($\chi^0$) = 0      & $16.9 \pm 0.5$& $14.9 \pm 0.5$& $10.5 \pm 0.4$& $6.1 \pm 0.3$& $3.1 \pm 0.2$& $1.5 \pm 0.1$& $0.6 \pm 0.1$& $0.3 \pm 0.1$ \\
288 > %\hline
289 >
290 >
291 > \subsubsection{Check of the uncertainty on the \ttll\ Background}
292 >
293 > We check that the systematic uncertainty assigned to the \ttll\ background prediction
294 > covers the uncertainty associated with
295 > the theoretical modeling of the \ttbar\ production and decay
296 > by comparing the background predictions obtained using
297   alternative MC samples. It should be noted that the full analysis is
298   performed with the alternative samples under consideration,
299   including the derivation of the various data-to-MC scale factors.
# Line 159 | Line 301 | The variations considered are
301  
302   \begin{itemize}
303   \item Top mass: The alternative values for the top mass differ
304 <  from the central value by $5~\GeV$: $m_{\mathrm{top}} = 178.5~\GeV$ and $m_{\mathrm{top}}
304 >  from the central value by $6~\GeV$: $m_{\mathrm{top}} = 178.5~\GeV$ and $m_{\mathrm{top}}
305    = 166.5~\GeV$.
306   \item Jet-parton matching scale: This corresponds to variations in the
307    scale at which the Matrix Element partons from Madgraph are matched
# Line 176 | Line 318 | The variations considered are
318    Tauola and is otherwise identical to the Powheg sample.
319    This effect was studied earlier using 7~TeV samples and found to be negligible.
320   \item The PDF uncertainty is estimated following the PDF4LHC
321 <  recommendations[CITE]. The events are reweighted using alternative
321 >  recommendations. The events are reweighted using alternative
322    PDF sets for CT10 and MSTW2008 and the uncertainties for each are derived using the
323 <  alternative eigenvector variations and the ``master equation''. In
324 <  addition, the NNPDF2.1 set with 100 replicas. The central value is
323 >  alternative eigenvector variations and the ``master equation''.
324 >  The NNPDF2.1 set with 100 replicas is also used. The central value is
325    determined from the mean and the uncertainty is derived from the
326    $1\sigma$ range. The overall uncertainty is derived from the envelope of the
327    alternative predictions and their uncertainties.
# Line 247 | Line 389 | on this Figure.
389    statistics.    
390   \item Within the limited statistics, there is no evidence that the
391    situation changes as we go from signal region A to signal region E.
392 < Therefore, we assess a systematic based on the relatively high
393 < statistics
394 < test in signal region A, and apply the same systematic uncertainty
395 < to all other regions.
392 > %Therefore, we assess a systematic based on the relatively high
393 > %statistics
394 > %test in signal region A, and apply the same systematic uncertainty
395 > %to all other regions.
396 > \item In signal regions B and above, the uncertainties assigned in Section~\ref{sec:ttdilbkgunc}
397 > fully cover the alternative MC variations.
398   \item In order to fully (as opposed as 1$\sigma$) cover the
399   alternative MC variations in region A we would have to take a
400   systematic
401 < uncertainty of $\approx 10\%$.  This would be driven by the
401 > uncertainty of $\approx 10\%$ instead of $5\%$.  This would be driven by the
402   scale up/scale down variations, see Table~\ref{tab:fracdiff}.
403   \end{itemize}
404  
# Line 288 | Line 432 | scale up/scale down variations are incon
432   These are described below.
433  
434   The first piece of information is that the jet multiplicity in the scale
435 < up/scale down sample is the most inconsistent with the data.  This can be shown
435 > up/scale down sample is the most inconsistent with the data.  This is shown
436   in Table~\ref{tab:njetskfactors_met100}, where we tabulate the
437 < $K_3$ and $K_4$ factors of Section~\ref{tab:njetskfactors_met100} for
437 > $K_3$ and $K_4$ factors of Section~\ref{sec:jetmultiplicity} for
438   different \ttbar\ MC samples.  The data/MC disagreement in the $N_{jets}$
439   distribution
440   for the scale up/scale down samples is also shown in Fig.~\ref{fig:dileptonnjets_scaleup}
# Line 351 | Line 495 | Then, going back to Table~\ref{tab:fracd
495   up/scale
496   down variations by a factor 2, we can see that a systematic
497   uncertainty
498 < of 6\% would fully cover all of the variations from different MC
499 < samples in SRA and SRB.
500 < {\bf Thus, we take a 6\% systematic uncertainty,  constant as a
501 < function of signal region, as the systematic due to alternative MC
502 < models.}.
503 < Note that this 6\% is also consistent with the level at which we are
504 < able
505 < to test the closure of the method in CR5 for the high statistics
506 < regions
507 < (Table~\ref{tab:hugecr5yields}).
508 <
498 > of 5\% covers the range of reasonable variations from different MC
499 > models in SRA and SRB.
500 > %The alternative MC models indicate that a 6\% systematic uncertainty
501 > %covers the range of reasonable variations.
502 > Note that this 5\% is also consistent with the level at which we are
503 > able to test the closure of the method with alternative samples in CR5 for the high statistics
504 > regions (Table~\ref{tab:hugecr5yields}).
505 > The range of reasonable variations obtained with the alternative
506 > samples are consistent with the uncertainties assigned for
507 > the \ttll\ background based on the closure of the background
508 > predictions and data in CR4 and CR5.
509  
510  
511  
# Line 592 | Line 736 | a second e/$\mu$ or a one prong $\tau \t
736   $P_T > 10$ GeV in $|\eta| < 2.4$.  This fraction is about 1/3, see
737   Table~\ref{tab:trueisotrk}.
738   The uncertainty for these events
739 < is 6\% and is obtained from Tag and Probe studies of Section~\ref{sec:trkveto}
739 > is 6\% and is obtained from tag-and-probe studies, see Section~\ref{sec:trkveto}.
740  
741   \begin{table}[!h]
742   \begin{center}
# Line 641 | Line 785 | decays are well-understood, we currently
785   Second, hadronic tracks may undergo nuclear interactions and hence their tracks may not be reconstructed.
786   As discussed above, independent studies show that the MC reproduces the hadronic tracking efficiency within 4\%,
787   leading to a total background uncertainty of less than 0.5\% (after taking into account the fraction of the total background
788 < due to hadronic $\tau$ decays with \pt\ $>$ 10 GeV tracks), and we hence regard this effect as neglgigible.
788 > due to hadronic $\tau$ decays with \pt\ $>$ 10 GeV tracks), and we hence regard this effect as negligible.
789  
790   The tag-and-probe studies are performed in the full data sample, and compared with the DYJets madgraph sample.
791   All events must contain a tag-probe pair (details below) with opposite-sign and satisfying the Z mass requirement 76--106 GeV.
# Line 698 | Line 842 | The specific criteria for tags and probe
842   The absolute track isolation distributions for passing probes are displayed in Fig.~\ref{fig:tnp}. In general we observe
843   good agreement between data and MC. To be more quantitative, we compare the data vs. MC efficiencies to satisfy
844   absolute track isolation requirements varying from $>$ 1 GeV to $>$ 5 GeV, as summarized in Table~\ref{tab:isotrk}.
845 < In the $\geq$0 and $\geq$1 jet bins where the efficiencies can be tested with statistical precision, the data and MC
845 > In the $\geq 0$ and $\geq 1$ jet bins where the efficiencies can be tested with statistical precision, the data and MC
846   efficiencies agree within 6\%, and we apply this as a systematic uncertainty on the isolated track veto efficiency.
847   For the higher jet multiplicity bins the statistical precision decreases, but we do not observe any evidence for
848   a data vs. MC discrepancy in the isolated track veto efficiency.
# Line 731 | Line 875 | for events with the \njets\ requirement
875  
876   \begin{table}[!ht]
877   \begin{center}
734 \caption{\label{tab:isotrk} Comparison of the data vs. MC efficiencies to satisfy the indicated requirements
735 on the absolute track isolation, and the ratio of these two efficiencies. Results are indicated separately for electrons and muons and for various
736 jet multiplicity requirements.}
878   \begin{tabular}{l|c|c|c|c|c}
879  
880   %Electrons:
# Line 831 | Line 972 | $\mu$ + $\geq$4 jets   &           $>$ 1
972   \hline
973  
974   \end{tabular}
975 + \caption{\label{tab:isotrk} Comparison of the data vs. MC efficiencies to satisfy the indicated requirements
976 + on the absolute track isolation, and the ratio of these two efficiencies. Results are indicated separately for electrons and muons and for various
977 + jet multiplicity requirements.}
978   \end{center}
979   \end{table}
980  
981 + \clearpage
982 + \subsection{Summary of uncertainties}
983 + \label{sec:bgunc-bottomline}
984 +
985 + 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}).
986 +
987 + \input{uncertainties_table.tex}
988 +
989 +
990 +
991 +
992  
993   %Figure.~\ref{fig:reliso} compares the relative track isolation
994   %for events with a track with $\pt > 10~\GeV$ in addition to a selected
# Line 915 | Line 1070 | $\mu$ + $\geq$4 jets   &           $>$ 1
1070   %      \end{center}
1071   %\end{figure}
1072  
918 \subsection{Summary of uncertainties}
919 \label{sec:bgunc-bottomline}.
1073  
1074 < THIS NEEDS TO BE WRITTEN
1074 >
1075 > % THIS NEEDS TO BE WRITTEN

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