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Revision: 1.8
Committed: Tue Sep 18 23:07:05 2012 UTC (12 years, 7 months ago) by benhoob
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add 2012C edge results

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# User Rev Content
1 benhoob 1.4 %\clearpage
2 benhoob 1.1 \section{Background Estimation Techniques}
3     \label{sec:bkg}
4    
5     In this section we describe the techniques used to estimate the SM backgrounds in our signal regions defined by requirements of large \MET.
6 benhoob 1.4 The SM backgrounds fall into three categories:
7 benhoob 1.1
8     \begin{itemize}
9 benhoob 1.2 \item \zjets: this is the dominant background after the preselection. The \MET\ in \zjets\ events is estimated with the
10 benhoob 1.1 ``\MET\ templates'' technique described in Sec.~\ref{sec:bkg_zjets};
11     \item Flavor-symmetric (FS) backgrounds: this category includes processes which produces 2 leptons of uncorrelated flavor. It is dominated
12     by \ttbar\ but also contains Z$\to\tau\tau$, WW, and single top processes. This is the dominant contribution in the signal regions, and it
13 benhoob 1.2 is estimated using a data control sample of e$\mu$ events as described in Sec.~\ref{sec:bkg_fs};
14 benhoob 1.1 \item WZ and ZZ backgrounds: this background is estimated from MC, after validating the MC modeling of these processes using data control
15 benhoob 1.2 samples with jets and exactly 3 leptons (WZ control sample) and exactly 4 leptons (ZZ control sample) as described in Sec.~\ref{sec:bkg_vz};
16 benhoob 1.4 %\item Rare SM backgrounds: this background contains rare processes such as $t\bar{t}$V and triple vector boson processes VVV (V=W,Z).
17     %This background is estimated from MC as described in Sec.~\ref{sec:bkg_raresm}. {\bf FIXME: add rare MC}
18 benhoob 1.1 \end{itemize}
19    
20     \subsection{Estimating the \zjets\ Background with \MET\ Templates}
21     \label{sec:bkg_zjets}
22    
23 benhoob 1.3 The premise of this data driven technique is that \MET\ in \zjets\ events
24 benhoob 1.1 is produced by the hadronic recoil system and {\it not} by the leptons making up the Z.
25     Therefore, the basic idea of the \MET\ template method is to measure the \MET\ distribution in
26     a control sample which has no true MET and the same general attributes regarding
27     fake MET as in \zjets\ events. We thus use a sample of \gjets\ events, since both \zjets\
28     and \gjets\ events consist of a well-measured object recoiling against hadronic jets.
29    
30     For selecting photon-like objects, the very loose photon selection described in Sec.~\ref{sec:phosel} is used.
31     It is not essential for the photon sample to have high purity. For our purposes, selecting jets with predominantly
32     electromagnetic energy deposition in a good fiducial volume suffices to ensure that
33     they are well measured and do not contribute to fake \MET. The \gjets\ events are selected with a suite of
34     single photon triggers with \pt thresholds varying from 22--90 GeV. The events are weighted by the trigger prescale
35     such that \gjets\ events evenly sample the conditions over the full period of data taking.
36     There remains a small difference in the PU conditions in the \gjets\ vs. \zjets\ samples due to the different
37     dependencies of the $\gamma$ vs. Z isolation efficiencies on PU. To account for this, we reweight the \gjets\ samples
38     to match the distribution of reconstructed primary vertices in the \zjets\ sample.
39    
40     To account for kinematic differences between the hadronic systems in the control vs. signal
41     samples, we measure the \MET\ distributions in the \gjets\ sample in bins of the number of jets
42 benhoob 1.3 and the scalar sum of jet transverse energies (\Ht). These \MET\ templates are extracted separately from the 5 single photon
43     triggers with thresholds 22, 36, 50, 75, and 90 GeV, so that the templates are effectively binned in photon \pt.
44     All \MET distributions are normalized to unit area to form ``MET templates''.
45     The prediction of the MET in each \Z event is the template which corresponds to the \njets,
46     \Ht, and Z \pt in the \zjets\ event. The prediction for the \Z sample is simply the sum of all such templates.
47     All templates are displayed in App.~\ref{app:templates}.
48 benhoob 1.1
49 benhoob 1.6 After preselection, there is a small contribution from backgrounds other than \zjets. To correct for this, the \MET\ templates
50     prediction is scaled such that the total background prediction matches the observed data yield in the \MET\ 0--60 GeV region.
51     Because the non-\zjets impurity in the low \MET\ region after preselection is very small, this results in
52     scaling factors of 0.985 (0.995) for the inclusive (targeted) search.
53 benhoob 1.1
54     \subsection{Estimating the Flavor-Symmetric Background with e$\mu$ Events}
55     \label{sec:bkg_fs}
56    
57     In this subsection we describe the background estimate for the FS background. Since this background produces equal rates of same-flavor (SF)
58     ee and $\mu\mu$ lepton pairs as opposite-flavor (OF) e$\mu$ lepton pairs, the OF yield can be used to estimate the SF yield, after
59     correcting for the different electron vs. muon offline selection efficiencies and the different efficiencies for the ee, $\mu\mu$, and e$\mu$ triggers.
60    
61     An important quantity needed to translate from the OF yield to a prediction for the background in the SF final state is the ratio
62     $R_{\mu e} = \epsilon_\mu / \epsilon_e$, where $\epsilon_\mu$ ($\epsilon_e$) indicates the offline muon (electron) selection efficiency.
63     This quantity can be extracted from data using the observed Z$\to\mu\mu$ and Z$\to$ee yields in the preselection region, after correcting
64     for the different trigger efficiencies.
65    
66     Hence we define:
67    
68     \begin{itemize}
69     \item $N_{ee}^{\rm{trig}} = \epsilon_{ee}^{\rm{trig}}N_{ee}^{\rm{offline}}$,
70     \item $N_{\mu\mu}^{\rm{trig}} = \epsilon_{\mu\mu}^{\rm{trig}}N_{\mu\mu}^{\rm{offline}}$,
71     \item $N_{e\mu}^{\rm{trig}} = \epsilon_{e\mu}^{\rm{trig}}N_{e\mu}^{\rm{offline}}$.
72     \end{itemize}
73    
74 benhoob 1.3 Here $N_{\ell\ell}^{\rm{trig}}$ denotes the number of selected Z events in the $\ell\ell$ channel passing the offline and trigger selection
75     (in other words, the number of recorded and selected events), $\epsilon_{\ell\ell}^{\rm{trig}}$ is the trigger efficiency, and
76     $N_{\ell\ell}^{\rm{offline}}$ is the number of events that would have passed the offline selection if the trigger had an efficiency of 100\%.
77 benhoob 1.1 Thus we calculate the quantity:
78    
79     \begin{equation}
80     R_{\mu e} = \sqrt{\frac{N_{\mu\mu}^{\rm{offline}}}{N_{ee}^{\rm{offline}}}} = \sqrt{\frac{N_{\mu\mu}^{\rm{trig}}/\epsilon_{\mu\mu}^{\rm{trig}}}{N_{ee}^{\rm{trig}}/\epsilon_{ee}^{\rm{trig}}}}
81 benhoob 1.6 = \sqrt{\frac{144122/0.88}{110325/0.95}} = 1.19\pm0.07.
82 benhoob 1.1 \end{equation}
83    
84     Here we have used the Z$\to\mu\mu$ and Z$\to$ee yields from Table~\ref{table:zyields_2j} and the trigger efficiencies quoted in Sec.~\ref{sec:datasets}.
85 benhoob 1.4 The indicated uncertainty is due to the 3\% uncertainties in the trigger efficiencies. %{\bf FIXME: check for variation w.r.t. lepton \pt}.
86 benhoob 1.1 The predicted yields in the ee and $\mu\mu$ final states are calculated from the observed e$\mu$ yield as
87    
88     \begin{itemize}
89     \item $N_{ee}^{\rm{predicted}} = \frac {N_{e\mu}^{\rm{trig}}} {\epsilon_{e\mu}^{\rm{trig}}} \frac {\epsilon_{ee}^{\rm{trig}}} {2 R_{\mu e}}
90 benhoob 1.6 = \frac{N_{e\mu}^{\rm{trig}}}{0.92}\frac{0.95}{2\times1.26} = (0.43\pm0.05) \times N_{e\mu}^{\rm{trig}}$ ,
91 benhoob 1.1 \item $N_{\mu\mu}^{\rm{predicted}} = \frac {N_{e\mu}^{\rm{trig}}} {\epsilon_{e\mu}^{\rm{trig}}} \frac {\epsilon_{\mu\mu}^{\rm{trig}} R_{\mu e}} {2}
92 benhoob 1.6 = \frac {N_{e\mu}^{\rm{trig}}} {0.95} \frac {0.88 \times 1.26}{2} = (0.55\pm0.07) \times N_{e\mu}^{\rm{trig}}$,
93 benhoob 1.1 \end{itemize}
94    
95     and the predicted yield in the combined ee and $\mu\mu$ channel is simply the sum of these two predictions:
96    
97     \begin{itemize}
98     \item $N_{ee+\mu\mu}^{\rm{predicted}} = (0.99\pm0.06)\times N_{e\mu}^{\rm{trig}}$.
99     \end{itemize}
100    
101 benhoob 1.3 Note that the relative uncertainty in the combined ee and $\mu\mu$ prediction is smaller than those for the individual ee and $\mu\mu$ predictions
102 benhoob 1.4 because the uncertainty in $R_{\mu e}$ cancels when summing the ee and $\mu\mu$ predictions. %{\bf N.B. these uncertainties are preliminary}.
103 benhoob 1.1
104     To improve the statistical precision of the FS background estimate, we remove the requirement that the e$\mu$ lepton pair falls in the Z mass window.
105     Instead we scale the e$\mu$ yield by $K$, the efficiency for e$\mu$ events to satisfy the Z mass requirement, extracted from simulation. In Fig.~\ref{fig:K_incl}
106 benhoob 1.6 we display the value of $K$ in data and simulation, for a variety of \MET\ requirements, for the inclusive analysis.
107     Based on this we chose $K=0.14\pm0.02$ for the lower \MET\ regions, $K=0.14\pm0.04$ for the \MET\ $>$ 200 GeV region,and $K=0.14\pm0.09$ for \MET\ $>$ 300 GeV,
108     where the larger uncertainties reflect the reduced statistical precision at large \MET.
109 benhoob 1.1 The corresponding plot for the targeted analysis, including the b-veto, is displayed in Fig.~\ref{fig:K_targeted}.
110     Based on this we chose $K=0.13\pm0.02$
111 benhoob 1.6 for all \MET\ regions up to \MET\ $>$ 150 GeV. For the \MET\ $>$ 200 GeV region we choose $K=0.13\pm0.05$, due to the reduced statistical precision.
112 benhoob 1.1
113     \begin{figure}[!ht]
114     \begin{center}
115     \begin{tabular}{cc}
116 benhoob 1.6 \includegraphics[width=0.4\textwidth]{plots/extractK_inclusive_92fb.pdf} &
117     \includegraphics[width=0.4\textwidth]{plots/extractK_exclusive_92fb.pdf} \\
118 benhoob 1.1 \end{tabular}
119 benhoob 1.6 \caption{\label{fig:K_incl}
120 benhoob 1.1 The efficiency for e$\mu$ events to satisfy the dilepton mass requirement, $K$, in data and simulation for inclusive \MET\ intervals (left) and
121 benhoob 1.6 exclusive \MET\ intervals (right) for the inclusive analysis.
122 benhoob 1.1 }
123 benhoob 1.6
124     \begin{comment}
125    
126     ----------------------------------------
127     EXCLUSIVE RESULTS
128     ----------------------------------------
129    
130     root [3] extractK(true,false,false)
131     Using selection : ((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20)
132     Using weight : vtxweight * weight
133     OF entries (total) 21691
134     OF entries (Z mass) 2934
135     K 0.135263
136     Warning in <TROOT::Append>: Replacing existing TH1: htot (Potential memory leak).
137     Warning in <TROOT::Append>: Replacing existing TH1: hZ (Potential memory leak).
138    
139     --------------------------------------------------------------
140     pfmet>0 && pfmet<30
141    
142     data :
143     total : 3650
144     Z : 461
145     K : 0.13 +/- 0.006
146    
147     MC :
148     total : 399.019
149     Z : 51.0493
150     K : 0.13 +/- 0.007
151     --------------------------------------------------------------
152    
153    
154     --------------------------------------------------------------
155     pfmet>30 && pfmet<60
156    
157     data :
158     total : 6951
159     Z : 904
160     K : 0.13 +/- 0.004
161    
162     MC :
163     total : 755.309
164     Z : 111.206
165     K : 0.15 +/- 0.003
166     --------------------------------------------------------------
167    
168    
169     --------------------------------------------------------------
170     pfmet>60 && pfmet<100
171    
172     data :
173     total : 7206
174     Z : 1037
175     K : 0.14 +/- 0.004
176    
177     MC :
178     total : 838.418
179     Z : 123.554
180     K : 0.15 +/- 0.003
181     --------------------------------------------------------------
182    
183    
184     --------------------------------------------------------------
185     pfmet>100 && pfmet<200
186    
187     data :
188     total : 3690
189     Z : 512
190     K : 0.14 +/- 0.006
191    
192     MC :
193     total : 451.624
194     Z : 67.7098
195     K : 0.15 +/- 0.004
196     --------------------------------------------------------------
197    
198    
199     --------------------------------------------------------------
200     pfmet>200 && pfmet<300
201    
202     data :
203     total : 172
204     Z : 17
205     K : 0.10 +/- 0.024
206    
207     MC :
208     total : 24.2441
209     Z : 2.67077
210     K : 0.11 +/- 0.013
211     --------------------------------------------------------------
212    
213    
214     --------------------------------------------------------------
215     pfmet>300
216    
217     data :
218     total : 22
219     Z : 3
220     K : 0.14 +/- 0.079
221    
222     MC :
223     total : 4.53108
224     Z : 0.230071
225     K : 0.05 +/- 0.022
226     --------------------------------------------------------------
227    
228    
229    
230     ----------------------------------------
231     INCLUSIVE RESULTS
232     ----------------------------------------
233    
234     root [4] extractK(false,false,false)
235     Using selection : ((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20)
236     Using weight : vtxweight * weight
237     OF entries (total) 21691
238     OF entries (Z mass) 2934
239     K 0.135263
240     Warning in <TROOT::Append>: Replacing existing TH1: htot (Potential memory leak).
241     Warning in <TROOT::Append>: Replacing existing TH1: hZ (Potential memory leak).
242    
243     --------------------------------------------------------------
244     pfmet>0
245    
246     data :
247     total : 21691
248     Z : 2934
249     K : 0.14 +/- 0.002
250    
251     MC :
252     total : 2472.89
253     Z : 356.434
254     K : 0.14 +/- 0.002
255     --------------------------------------------------------------
256    
257    
258     --------------------------------------------------------------
259     pfmet>30
260    
261     data :
262     total : 18041
263     Z : 2473
264     K : 0.14 +/- 0.003
265    
266     MC :
267     total : 2074.05
268     Z : 305.382
269     K : 0.15 +/- 0.002
270     --------------------------------------------------------------
271    
272    
273     --------------------------------------------------------------
274     pfmet>60
275    
276     data :
277     total : 11090
278     Z : 1569
279     K : 0.14 +/- 0.004
280    
281     MC :
282     total : 1318.79
283     Z : 194.166
284     K : 0.15 +/- 0.002
285     --------------------------------------------------------------
286    
287    
288     --------------------------------------------------------------
289     pfmet>100
290    
291     data :
292     total : 3884
293     Z : 532
294     K : 0.14 +/- 0.006
295    
296     MC :
297     total : 480.402
298     Z : 70.6107
299     K : 0.15 +/- 0.004
300     --------------------------------------------------------------
301    
302    
303     --------------------------------------------------------------
304     pfmet>200
305    
306     data :
307     total : 194
308     Z : 20
309     K : 0.10 +/- 0.023
310    
311     MC :
312     total : 28.7751
313     Z : 2.90084
314     K : 0.10 +/- 0.012
315     --------------------------------------------------------------
316    
317    
318     --------------------------------------------------------------
319     pfmet>300
320    
321     data :
322     total : 22
323     Z : 3
324     K : 0.14 +/- 0.079
325    
326     MC :
327     total : 4.53108
328     Z : 0.230071
329     K : 0.05 +/- 0.022
330     --------------------------------------------------------------
331    
332     \end{comment}
333    
334 benhoob 1.1 \end{center}
335     \end{figure}
336    
337     \begin{figure}[!hb]
338     \begin{center}
339     \begin{tabular}{cc}
340 benhoob 1.6 \includegraphics[width=0.4\textwidth]{plots/extractK_inclusive_bvetoMedium_92fb.pdf} &
341     \includegraphics[width=0.4\textwidth]{plots/extractK_exclusive_bvetoMedium_92fb.pdf} \\
342 benhoob 1.1 \end{tabular}
343     \caption{
344     The efficiency for e$\mu$ events to satisfy the dilepton mass requirement, $K$, in data and simulation for inclusive \MET\ intervals (left) and
345     exclusive \MET\ intervals (right) for the targeted analysis, including the b-veto.
346     Based on this we chose $K=0.13\pm0.02$ for the \MET\ regions up to \MET\ $>$ 100 GeV.
347     For higher \MET\ regions we chose $K=0.13\pm0.07$.
348 benhoob 1.4 %{\bf FIXME plots made with 10\% of \zjets\ MC statistics, to be remade with full statistics}
349 benhoob 1.1 \label{fig:K_targeted}
350     }
351 benhoob 1.6 \begin{comment}
352    
353     root [2] extractK(true,false,true)
354     Using selection : (((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20))&&(nbcsvm==0)
355     Using weight : vtxweight * weight
356     OF entries (total) 5756
357     OF entries (Z mass) 654
358     K 0.113621
359     Warning in <TStreamerInfo::Compile>: Counter fNClusterRange should not be skipped from class TTree
360     Info in <TCanvas::MakeDefCanvas>: created default TCanvas with name c1
361    
362     --------------------------------------------------------------
363     pfmet>0 && pfmet<30
364    
365     data :
366     total : 1303
367     Z : 126
368     K : 0.10 +/- 0.009
369    
370     MC :
371     total : 131.974
372     Z : 15.1946
373     K : 0.12 +/- 0.020
374     --------------------------------------------------------------
375    
376    
377     --------------------------------------------------------------
378     pfmet>30 && pfmet<60
379    
380     data :
381     total : 1818
382     Z : 190
383     K : 0.10 +/- 0.008
384    
385     MC :
386     total : 172.956
387     Z : 21.9369
388     K : 0.13 +/- 0.007
389     --------------------------------------------------------------
390    
391    
392     --------------------------------------------------------------
393     pfmet>60 && pfmet<80
394    
395     data :
396     total : 994
397     Z : 122
398     K : 0.12 +/- 0.011
399    
400     MC :
401     total : 109.789
402     Z : 13.9792
403     K : 0.13 +/- 0.008
404     --------------------------------------------------------------
405    
406    
407     --------------------------------------------------------------
408     pfmet>80 && pfmet<100
409    
410     data :
411     total : 699
412     Z : 99
413     K : 0.14 +/- 0.014
414    
415     MC :
416     total : 73.3643
417     Z : 11.5154
418     K : 0.16 +/- 0.010
419     --------------------------------------------------------------
420    
421    
422     --------------------------------------------------------------
423     pfmet>100 && pfmet<150
424    
425     data :
426     total : 722
427     Z : 93
428     K : 0.13 +/- 0.013
429    
430     MC :
431     total : 86.7947
432     Z : 11.742
433     K : 0.14 +/- 0.009
434     --------------------------------------------------------------
435    
436    
437     --------------------------------------------------------------
438     pfmet>150 && pfmet<200
439    
440     data :
441     total : 163
442     Z : 18
443     K : 0.11 +/- 0.026
444    
445     MC :
446     total : 19.4473
447     Z : 2.97965
448     K : 0.15 +/- 0.017
449     --------------------------------------------------------------
450    
451    
452     --------------------------------------------------------------
453     pfmet>200
454    
455     data :
456     total : 57
457     Z : 6
458     K : 0.11 +/- 0.043
459    
460     MC :
461     total : 8.99801
462     Z : 0.794136
463     K : 0.09 +/- 0.021
464     --------------------------------------------------------------
465    
466     root [3] Info in <TCanvas::Print>: pdf file /Users/benhoob/tas/ZMet2012/plots/extractK_exclusive_bvetoMedium_92fb.pdf has been created
467    
468     root [3]
469     root [3] extractK(false,false,true)
470     Using selection : (((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20))&&(nbcsvm==0)
471     Using weight : vtxweight * weight
472     OF entries (total) 5756
473     OF entries (Z mass) 654
474     K 0.113621
475     Warning in <TROOT::Append>: Replacing existing TH1: htot (Potential memory leak).
476     Warning in <TROOT::Append>: Replacing existing TH1: hZ (Potential memory leak).
477    
478     --------------------------------------------------------------
479     pfmet>0
480    
481     data :
482     total : 5756
483     Z : 654
484     K : 0.11 +/- 0.004
485    
486     MC :
487     total : 603.333
488     Z : 78.1422
489     K : 0.13 +/- 0.005
490     --------------------------------------------------------------
491    
492    
493     --------------------------------------------------------------
494     pfmet>30
495    
496     data :
497     total : 4453
498     Z : 528
499     K : 0.12 +/- 0.005
500    
501     MC :
502     total : 471.396
503     Z : 62.9476
504     K : 0.13 +/- 0.004
505     --------------------------------------------------------------
506    
507    
508     --------------------------------------------------------------
509     pfmet>60
510    
511     data :
512     total : 2635
513     Z : 338
514     K : 0.13 +/- 0.007
515    
516     MC :
517     total : 298.41
518     Z : 41.0107
519     K : 0.14 +/- 0.005
520     --------------------------------------------------------------
521    
522    
523     --------------------------------------------------------------
524     pfmet>80
525    
526     data :
527     total : 1641
528     Z : 216
529     K : 0.13 +/- 0.009
530    
531     MC :
532     total : 188.602
533     Z : 27.0313
534     K : 0.14 +/- 0.006
535     --------------------------------------------------------------
536    
537    
538     --------------------------------------------------------------
539     pfmet>100
540    
541     data :
542     total : 942
543     Z : 117
544     K : 0.12 +/- 0.011
545    
546     MC :
547     total : 115.24
548     Z : 15.5158
549     K : 0.13 +/- 0.008
550     --------------------------------------------------------------
551    
552    
553     --------------------------------------------------------------
554     pfmet>150
555    
556     data :
557     total : 220
558     Z : 24
559     K : 0.11 +/- 0.022
560    
561     MC :
562     total : 28.4454
563     Z : 3.77378
564     K : 0.13 +/- 0.014
565     --------------------------------------------------------------
566    
567    
568     --------------------------------------------------------------
569     pfmet>200
570    
571     data :
572     total : 57
573     Z : 6
574     K : 0.11 +/- 0.043
575    
576     MC :
577     total : 8.99801
578     Z : 0.794136
579     K : 0.09 +/- 0.021
580     --------------------------------------------------------------
581    
582     \end{comment}
583    
584     \end{center}
585     \end{figure}
586    
587    
588     \begin{comment}
589    
590     \begin{figure}[!hb]
591     \begin{center}
592     \begin{tabular}{cc}
593     \includegraphics[width=0.4\textwidth]{plots/extractK_inclusive_bvetoLoose_92fb.pdf} &
594     \includegraphics[width=0.4\textwidth]{plots/extractK_exclusive_bvetoLoose_92fb.pdf} \\
595     \end{tabular}
596     \caption{
597     The efficiency for e$\mu$ events to satisfy the dilepton mass requirement, $K$, in data and simulation for inclusive \MET\ intervals (left) and
598     exclusive \MET\ intervals (right) for the targeted analysis, including the b-veto.
599     %{\bf FIXME plots made with 10\% of \zjets\ MC statistics, to be remade with full statistics}
600     \label{fig:K_targeted}}
601    
602    
603     root [2] extractK(true,false,true)
604     Using selection : (((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20))&&(nbcsvl==0)
605     Using weight : vtxweight * weight
606     OF entries (total) 2715
607     OF entries (Z mass) 279
608     K 0.102762
609     Warning in <TStreamerInfo::Compile>: Counter fNClusterRange should not be skipped from class TTree
610     Info in <TCanvas::MakeDefCanvas>: created default TCanvas with name c1
611    
612     --------------------------------------------------------------
613     pfmet>0 && pfmet<30
614    
615     data :
616     total : 713
617     Z : 59
618     K : 0.08 +/- 0.011
619    
620     MC :
621     total : 74.2549
622     Z : 7.09789
623     K : 0.10 +/- 0.025
624     --------------------------------------------------------------
625    
626    
627     --------------------------------------------------------------
628     pfmet>30 && pfmet<60
629    
630     data :
631     total : 850
632     Z : 79
633     K : 0.09 +/- 0.010
634    
635     MC :
636     total : 84.6973
637     Z : 9.55105
638     K : 0.11 +/- 0.009
639     --------------------------------------------------------------
640    
641    
642     --------------------------------------------------------------
643     pfmet>60 && pfmet<80
644    
645     data :
646     total : 469
647     Z : 61
648     K : 0.13 +/- 0.017
649    
650     MC :
651     total : 50.1496
652     Z : 5.92081
653     K : 0.12 +/- 0.012
654     --------------------------------------------------------------
655    
656    
657     --------------------------------------------------------------
658     pfmet>80 && pfmet<100
659    
660     data :
661     total : 269
662     Z : 33
663     K : 0.12 +/- 0.021
664    
665     MC :
666     total : 30.0547
667     Z : 4.67993
668     K : 0.16 +/- 0.014
669     --------------------------------------------------------------
670    
671    
672     --------------------------------------------------------------
673     pfmet>100 && pfmet<150
674    
675     data :
676     total : 311
677     Z : 34
678     K : 0.11 +/- 0.019
679    
680     MC :
681     total : 39.4475
682     Z : 5.02593
683     K : 0.13 +/- 0.014
684     --------------------------------------------------------------
685    
686    
687     --------------------------------------------------------------
688     pfmet>150 && pfmet<200
689    
690     data :
691     total : 79
692     Z : 10
693     K : 0.13 +/- 0.040
694    
695     MC :
696     total : 9.96228
697     Z : 1.4975
698     K : 0.15 +/- 0.023
699     --------------------------------------------------------------
700    
701    
702     --------------------------------------------------------------
703     pfmet>200
704    
705     data :
706     total : 24
707     Z : 3
708     K : 0.12 +/- 0.072
709    
710     MC :
711     total : 5.3503
712     Z : 0.425719
713     K : 0.08 +/- 0.027
714     --------------------------------------------------------------
715    
716     root [3] Info in <TCanvas::Print>: pdf file /Users/benhoob/tas/ZMet2012/plots/extractK_exclusive_bvetoLoose_92fb.pdf has been created
717    
718     root [3]
719     root [3] extractK(false,false,true)
720     Using selection : (((((leptype==2)&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(isdata==0 || (run<197556 || run>198913)))&&(njets>=2))&&(lep1.pt()>20 && lep2.pt()>20))&&(nbcsvl==0)
721     Using weight : vtxweight * weight
722     OF entries (total) 2715
723     OF entries (Z mass) 279
724     K 0.102762
725     Warning in <TROOT::Append>: Replacing existing TH1: htot (Potential memory leak).
726     Warning in <TROOT::Append>: Replacing existing TH1: hZ (Potential memory leak).
727    
728     --------------------------------------------------------------
729     pfmet>0
730    
731     data :
732     total : 2715
733     Z : 279
734     K : 0.10 +/- 0.006
735    
736     MC :
737     total : 293.912
738     Z : 34.199
739     K : 0.12 +/- 0.008
740     --------------------------------------------------------------
741    
742    
743     --------------------------------------------------------------
744     pfmet>30
745    
746     data :
747     total : 2002
748     Z : 220
749     K : 0.11 +/- 0.007
750    
751     MC :
752     total : 219.661
753     Z : 27.101
754     K : 0.12 +/- 0.006
755     --------------------------------------------------------------
756    
757    
758     --------------------------------------------------------------
759     pfmet>60
760    
761     data :
762     total : 1152
763     Z : 141
764     K : 0.12 +/- 0.010
765    
766     MC :
767     total : 134.962
768     Z : 17.5498
769     K : 0.13 +/- 0.007
770     --------------------------------------------------------------
771    
772    
773     --------------------------------------------------------------
774     pfmet>80
775    
776     data :
777     total : 683
778     Z : 80
779     K : 0.12 +/- 0.013
780    
781     MC :
782     total : 84.8149
783     Z : 11.629
784     K : 0.14 +/- 0.009
785     --------------------------------------------------------------
786    
787    
788     --------------------------------------------------------------
789     pfmet>100
790    
791     data :
792     total : 414
793     Z : 47
794     K : 0.11 +/- 0.017
795    
796     MC :
797     total : 54.7604
798     Z : 6.94915
799     K : 0.13 +/- 0.011
800     --------------------------------------------------------------
801    
802    
803     --------------------------------------------------------------
804     pfmet>150
805    
806     data :
807     total : 103
808     Z : 13
809     K : 0.13 +/- 0.035
810    
811     MC :
812     total : 15.3125
813     Z : 1.92322
814     K : 0.13 +/- 0.019
815     --------------------------------------------------------------
816    
817    
818     --------------------------------------------------------------
819     pfmet>200
820    
821     data :
822     total : 24
823     Z : 3
824     K : 0.12 +/- 0.072
825    
826     MC :
827     total : 5.3503
828     Z : 0.425719
829     K : 0.08 +/- 0.027
830     --------------------------------------------------------------
831    
832    
833 benhoob 1.1 \end{center}
834     \end{figure}
835    
836 benhoob 1.6
837     \end{comment}
838    
839    
840 benhoob 1.1 \clearpage
841    
842     \subsection{Estimating the WZ and ZZ Background with MC}
843     \label{sec:bkg_vz}
844    
845     Backgrounds from W($\ell\nu$)Z($\ell\ell$) where the W lepton is not identified or is outside acceptance, and Z($\nu\nu$)Z($\ell\ell$),
846     are estimated from simulation. The MC modeling of these processes is validated by comparing the MC predictions with data in control samples
847     with exactly 3 leptons (WZ control sample) and exactly 4 leptons (ZZ control sample).
848 benhoob 1.6 The critical samples are the WZJetsTo3LNu and ZZJetsTo4L, listed in Table~\ref{tab:mcsamples}
849     (the WZJetsTo2L2Q, ZZJetsTo2L2Q, and ZZJetsTo2L2Nu samples are also used in this analysis but their contribution to the 3-lepton and 4-lepton
850     control samples is negligible).
851 benhoob 1.1
852     \subsubsection{WZ Validation Studies}
853     \label{sec:bkg_wz}
854    
855     A pure WZ sample can be selected in data with the requirements:
856    
857     \begin{itemize}
858     \item Exactly 3 $p_T>20$~GeV leptons passing analysis identication and isolation requirements,
859     \item 2 of the 3 leptons must fall in the Z window 81-101 GeV,
860     \item \MET $>$ 50 GeV (to suppress DY).
861     \end{itemize}
862    
863     The data and MC yields passing the above selection are in Table~\ref{tab:wz}.
864 benhoob 1.6 The inclusive yields (without any jet requirements) agree within 13\%, which is consistent within
865     the uncertainty in the CMS measured WZ cross section (17\%). A data vs. MC comparison of kinematic
866 benhoob 1.1 distributions (jet multiplicity, \MET, Z \pt) is given in Fig.~\ref{fig:wz}. High \MET\
867     values in WZ and ZZ events arise from highly boosted W or Z bosons that decay leptonically,
868     and we therefore check that the MC does a reasonable job of reproducing the \pt distributions of the
869     leptonically decaying \Z. While the inclusive WZ yields are in reasonable agreement, we observe
870     an excess in data in events with at least 2 jets, corresponding to the jet multiplicity requirement
871 benhoob 1.6 in our preselection. We observe 106 events in data while the MC predicts $62\pm1.5$~(stat), representing an excess of 71\%,
872 benhoob 1.7 as indicated in Table~\ref{tab:wz2j}.
873     This excess will be studied further. For the time being, based on these studies we currently assess an uncertainty of 70\% on the WZ yield.
874    
875     \begin{comment}
876     We note some possible contributions to this discrepancy:
877 benhoob 1.1
878     \begin{itemize}
879    
880 benhoob 1.6 \item {\bf The following checks refer to the 5.2 fb$^{-1}$ results and will be updated.}
881    
882 benhoob 1.1 \item The \zjets\ contribution is under-estimated here, for 2 reasons: first, because the \zjets\
883     yield passing a \MET $>$ 50 GeV requirement is under-estimated in MC and second, because the fake
884     rate is typically under-estimated in the MC. To get a rough idea for how much the excess depends
885     on the \zjets\ yield, if the \zjets\ yield is doubled then the excess is reduced from 78\% to 55\%.
886 benhoob 1.4 Also note that we are currently using 10\% of the \zjets\ MC sample and there is 1 event with a weight
887     of about 5, so the plots and tables will be remade with full \zjets\ sample.
888 benhoob 1.1
889     \item The \ttbar\ contribution is under-estimated here because the fake
890     rate is typically under-estimated in the MC. To get a rough idea for how much the excess depends
891     on the \ttbar\ yield, if the \ttbar\ yield is doubled then the excess is reduced from 78\% to 57\%.
892    
893     \item Currently no attempt is made to reject jets from pile-up interactions, which may be responsible
894 benhoob 1.3 for some of the excess at large \njets. To check this, we increase the jet \pt threhsold to 40 GeV, which
895     helps to suppress PU jets, and observe 39 events in data vs. an MC prediction of $25\pm5.2$~(stat),
896 benhoob 1.1 decreasing the excess from 78\% to 58\%. In the future this may be improved by explicitly
897     requiring the jets to be consistent with originating from the signal primary vertex.
898    
899     \end{itemize}
900 benhoob 1.7 \end{comment}
901    
902 benhoob 1.1
903    
904     \begin{table}[htb]
905     \begin{center}
906     \caption{\label{tab:wz} Data and Monte Carlo yields passing the WZ preselection. }
907     \begin{tabular}{lccccc}
908     \hline
909 benhoob 1.3 \hline
910 benhoob 1.1 Sample & ee & $\mu\mu$ & e$\mu$ & total \\
911     \hline
912 benhoob 1.5
913     %Loading babies at : ../output/V00-01-04
914     %Using selection : ((((((isdata==0 || (run<197556 || run>198913))&&(((leptype==0 && (ee==1 || isdata==0))||(leptype==1 && (mm==1 || isdata==0)))||(leptype==2 && (em==1||me==1||isdata==0))))&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(lep1.pt()>20.0 && lep2.pt()>20.0))&&(nlep==3 && lep3.pt()>20.0))&&(pfmet>50))&&(dilmass>81 && dilmass<101)
915     %Using weight : weight * 9.2 * trgeff * vtxweight
916    
917     WZ &116.7 $\pm$ 0.8 &151.5 $\pm$ 0.8 & 8.1 $\pm$ 0.2 &276.3 $\pm$ 1.2 \\
918     ttV & 4.1 $\pm$ 0.2 & 4.9 $\pm$ 0.2 & 1.2 $\pm$ 0.1 & 10.2 $\pm$ 0.3 \\
919     \ttbar & 1.2 $\pm$ 0.6 & 3.2 $\pm$ 0.9 & 3.6 $\pm$ 1.0 & 7.9 $\pm$ 1.5 \\
920     ZZ & 2.5 $\pm$ 0.0 & 3.4 $\pm$ 0.0 & 0.2 $\pm$ 0.0 & 6.1 $\pm$ 0.0 \\
921     \zjets & 1.2 $\pm$ 0.9 & 3.0 $\pm$ 1.8 & 0.0 $\pm$ 0.0 & 4.2 $\pm$ 2.1 \\
922     vvv & 1.6 $\pm$ 0.1 & 2.1 $\pm$ 0.1 & 0.3 $\pm$ 0.0 & 4.0 $\pm$ 0.1 \\
923     single top & 0.0 $\pm$ 0.0 & 0.2 $\pm$ 0.2 & 0.0 $\pm$ 0.0 & 0.2 $\pm$ 0.2 \\
924     WW & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.1 $\pm$ 0.0 & 0.1 $\pm$ 0.1 \\
925     \hline
926     tot SM MC &127.3 $\pm$ 1.4 &168.4 $\pm$ 2.3 & 13.5 $\pm$ 1.0 &309.2 $\pm$ 2.8 \\
927 benhoob 1.1 \hline
928 benhoob 1.5 data & 156 & 178 & 16 & 350 \\
929 benhoob 1.1 \hline
930     \hline
931    
932     \end{tabular}
933     \end{center}
934     \end{table}
935    
936     \begin{table}[htb]
937     \begin{center}
938 benhoob 1.8 \caption{\label{tab:wz2j} Data and Monte Carlo yields passing the WZ preselection and \njets\ $\geq$ 2. }
939 benhoob 1.1 \begin{tabular}{lccccc}
940     \hline
941 benhoob 1.3 \hline
942 benhoob 1.1 Sample & ee & $\mu\mu$ & e$\mu$ & total \\
943     \hline
944 benhoob 1.5
945     %Loading babies at : ../output/V00-01-04
946     %Using selection : (((((((isdata==0 || (run<197556 || run>198913))&&(((leptype==0 && (ee==1 || isdata==0))||(leptype==1 && (mm==1 || isdata==0)))||(leptype==2 && (em==1||me==1||isdata==0))))&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(lep1.pt()>20.0 && lep2.pt()>20.0))&&(nlep==3 && lep3.pt()>20.0))&&(pfmet>50))&&(dilmass>81 && dilmass<101))&&(njets>=2)
947     %Using weight : weight * 9.2 * trgeff * vtxweight
948    
949     WZ & 19.1 $\pm$ 0.3 & 24.6 $\pm$ 0.3 & 1.3 $\pm$ 0.1 & 44.9 $\pm$ 0.5 \\
950     ttV & 3.8 $\pm$ 0.2 & 4.5 $\pm$ 0.2 & 1.0 $\pm$ 0.1 & 9.3 $\pm$ 0.3 \\
951     \ttbar & 0.8 $\pm$ 0.5 & 1.6 $\pm$ 0.7 & 0.9 $\pm$ 0.5 & 3.3 $\pm$ 1.0 \\
952     ZZ & 0.5 $\pm$ 0.0 & 0.7 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 1.2 $\pm$ 0.0 \\
953     \zjets & 0.9 $\pm$ 0.9 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.9 $\pm$ 0.9 \\
954     vvv & 0.9 $\pm$ 0.0 & 1.2 $\pm$ 0.1 & 0.1 $\pm$ 0.0 & 2.2 $\pm$ 0.1 \\
955     single top & 0.0 $\pm$ 0.0 & 0.2 $\pm$ 0.2 & 0.0 $\pm$ 0.0 & 0.2 $\pm$ 0.2 \\
956     WW & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 \\
957     \hline
958     tot SM MC & 25.9 $\pm$ 1.1 & 32.9 $\pm$ 0.8 & 3.3 $\pm$ 0.5 & 62.1 $\pm$ 1.5 \\
959 benhoob 1.1 \hline
960 benhoob 1.5 data & 47 & 51 & 8 & 106 \\
961 benhoob 1.1 \hline
962     \hline
963    
964     \end{tabular}
965     \end{center}
966     \end{table}
967    
968     \begin{figure}[tbh]
969     \begin{center}
970 benhoob 1.5 \includegraphics[width=1\linewidth]{plots/WZ_92fb.pdf}
971 benhoob 1.1 \caption{\label{fig:wz}\protect
972     Data vs. MC comparisons for the WZ selection discussed in the text for \lumi.
973     The number of jets, missing transverse energy, and Z boson transverse momentum are displayed.
974 benhoob 1.5 %Loading babies at : ../output/V00-01-04
975     %Using selection : ((((((isdata==0 || (run<197556 || run>198913))&&(((leptype==0 && (ee==1 || isdata==0))||(leptype==1 && (mm==1 || isdata==0)))||(leptype==2 && (em==1||me==1||isdata==0))))&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(lep1.pt()>20.0 && lep2.pt()>20.0))&&(nlep==3 && lep3.pt()>20.0))&&(pfmet>50))&&(dilmass>81 && dilmass<101)
976     %Using weight : weight * 9.2 * trgeff * vtxweight
977 benhoob 1.1 }
978     \end{center}
979     \end{figure}
980    
981     \clearpage
982    
983     \subsubsection{ZZ Validation Studies}
984     \label{sec:bkg_zz}
985    
986     A pure ZZ sample can be selected in data with the requirements:
987    
988     \begin{itemize}
989     \item Exactly 4 $p_T>20$~GeV leptons passing analysis identication and isolation requirements,
990     \item 2 of the 4 leptons must fall in the $Z$ window 81-101 GeV.
991     \end{itemize}
992    
993 benhoob 1.6 The data and MC yields passing the above selection are in Table~\ref{tab:zz}.
994     In this ZZ-dominated sample we observe good agreement between the data yield and the MC prediction.
995     After requiring 2 jets (corresponding to the requirement in the analysis selection), we observe 4 events
996     in data and the MC predicts $6.6\pm0.1$ events. Due to the limited statistical precision we assign an uncertainty
997     fo 50\% on the ZZ yield.
998 benhoob 1.1
999     \begin{table}[htb]
1000     \begin{center}
1001     \caption{\label{tab:zz} Data and Monte Carlo yields for the ZZ preselection. }
1002     \begin{tabular}{lccccc}
1003     \hline
1004 benhoob 1.3 \hline
1005 benhoob 1.1 Sample & ee & $\mu\mu$ & e$\mu$ & total \\
1006     \hline
1007 benhoob 1.6
1008     %Loading babies at : ../output/V00-01-04
1009     %Using selection : (((((isdata==0 || (run<197556 || run>198913))&&(((leptype==0 && (ee==1 || isdata==0))||(leptype==1 && (mm==1 || isdata==0)))||(leptype==2 && (em==1||me==1||isdata==0))))&&(csc==0 && hbhe==1 && hcallaser==1 && ecaltp==1 && trkfail==1 && eebadsc==1 && hbhenew==1))&&(lep1.pt()>20.0 && lep2.pt()>20.0))&&(nlep==4 && lep3.pt()>20.0 && lep4.pt()>20.0))&&(dilmass>81 && dilmass<101)
1010     %Using weight : weight * 9.2 * trgeff * vtxweight
1011     %SCALING ZJETS BY 111/946
1012     %SCALING ZZ BY 1.92
1013    
1014     ZZ & 25.1 $\pm$ 0.1 & 34.9 $\pm$ 0.1 & 1.6 $\pm$ 0.0 & 61.7 $\pm$ 0.1 \\
1015     ttV & 0.6 $\pm$ 0.1 & 0.6 $\pm$ 0.1 & 0.2 $\pm$ 0.0 & 1.4 $\pm$ 0.1 \\
1016     VVV & 0.3 $\pm$ 0.0 & 0.4 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.7 $\pm$ 0.0 \\
1017     WZ & 0.1 $\pm$ 0.0 & 0.1 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.1 $\pm$ 0.0 \\
1018 benhoob 1.1 \zjets & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 \\
1019     \ttbar & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 \\
1020 benhoob 1.6 single top & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 \\
1021 benhoob 1.1 WW & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 & 0.0 $\pm$ 0.0 \\
1022     \hline
1023 benhoob 1.6 tot SM MC & 26.1 $\pm$ 0.1 & 36.1 $\pm$ 0.1 & 1.8 $\pm$ 0.0 & 63.9 $\pm$ 0.2 \\
1024     \hline
1025     data & 24 & 36 & 0 & 60 \\
1026 benhoob 1.1 \hline
1027     \hline
1028     \end{tabular}
1029     \end{center}
1030     \end{table}
1031    
1032     \begin{figure}[tbh]
1033     \begin{center}
1034 benhoob 1.6 \includegraphics[width=1\linewidth]{plots/ZZ_92fb.pdf}
1035 benhoob 1.1 \caption{\label{fig:zz}\protect
1036 benhoob 1.3 Data vs. MC comparisons for the ZZ selection discussed in the text for \lumi.
1037     The number of jets, missing transverse energy, and Z boson transverse momentum are displayed.
1038 benhoob 1.1 }
1039     \end{center}
1040     \end{figure}
1041    
1042    
1043    
1044    
1045 benhoob 1.4 %\subsection{Estimating the Rare SM Backgrounds with MC}
1046     %\label{sec:bkg_raresm}
1047 benhoob 1.1
1048 benhoob 1.4 %{\bf TODO: list samples, yields in preselection region, and show \MET\ distribution}