Violation in Mixing

5.3 Analysis Strategy 125
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0 5 10 15 20 25 30 35 40 45 50
ks candidate lifetime significance
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Kshort lifetime significance
Figure 5-5. The variable ØÃË��Ø distributions. Left plot: lifetime significance for fake (histogram) and
ÃË
true (dots) ÃË continuum Monte Carlo data. Right plot: Data-MC agreement in Â��Ã Ë events in data (dots)
and in the Â��ÃË signal MC (histogram). The plots are background subtracted (Ã Ë mass side-bands) and
the histograms are normalized to equal area.
Since à ˒s in �� events have typically lower momenta with respect to Ã Ë in charmless two-body decays,,
we have also used, as a control sample for our channel, a sample of reconstructed Â��Ã Ë events: the
momentum spectrum of these Ã Ë goes from 1 GeV up to 3 GeV. Right plot in figure 5-5 shows the good
agreement of the lifetime significance distribution for data and MC in this control sample.
The statistical significance Ë � Ë � (Ë and � are the number of expected signal and background events
respectively) of a cut on ØÃË��Ø ÃË
is shown in Fig. 5-6. For this exercise a branching fraction of �Ê � �
� Ã Ë � ��¢ � is assumed.
From this optimization, we require Ø ÃË ��Ø ÃË
� �: the uncertainty on this cut will be taken into account in
the systematic study, where we vary the lifetime significance cut and calculate from the global likelihood fit
the difference of the yields found with respect to the nominal results (see Sec. 5.4.5).
5.3 Analysis Strategy
Signal yields in � � Ã Ë � and � � Ã Ë Ã channels are determined using an unbinned maximum
likelihood technique. The background suppression variables and parameterization of the probability density
functions (PDFs) are discussed in Sec. 5.4. The results of a fit to the full Run1 data-set are presented in
Sec. 5.5. As a crosscheck, background suppression and particle identification cuts have been applied to
MEASUREMENT OF BRANCHING FRACTIONS FOR � ¦ � Ã � ¦ DECAYS