Violation in Mixing
Violation in Mixing
Violation in Mixing
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3.3 Studies on data 85<br />
0.03<br />
0.025<br />
0.02<br />
0.015<br />
0.01<br />
0.005<br />
observed Ks candidates<br />
0<br />
-3 -2 -1 0 1 2 3<br />
ks daughter phi angle<br />
nks<br />
0.03<br />
0.025<br />
0.02<br />
0.015<br />
0.01<br />
0.005<br />
observed Ks candidates<br />
0<br />
-3 -2 -1 0 1 2 3<br />
ks daughter phi angle<br />
nks<br />
Figure 3-5. On resonance data: number of reconstructed Ã Ë as function of the � angle of the Ã Ë daughters<br />
<strong>in</strong> both b1 (left) and b2 (right) data-sets. The data-Monte Carlo comparison is presented: the empty dots<br />
come from the Monte Carlo sample and the black po<strong>in</strong>ts come from the on resonance data.<br />
where � Ø ÃË is the number of Ã Ë per event <strong>in</strong> each sample. From table 3-2, we can evaluate � corr and<br />
� corr<br />
ÃË<br />
for both block 1 and block 2 Monte Carlo samples: this estimate can be found <strong>in</strong> Tab. 3-3. From the<br />
corrected cross section we can estimate the expected number of hadronic events <strong>in</strong> the on-resonance data,<br />
while from the number of Ã Ë per event we can calculate the expected number of Ã Ë <strong>in</strong> the data samples.<br />
The efficiency can be evaluated <strong>in</strong> both Monte Carlo and data. The same technique is used on both samples:<br />
an <strong>in</strong>variant mass w<strong>in</strong>dow between ��� and ��� ��� is taken <strong>in</strong>to account and a double Gaussian fit<br />
with l<strong>in</strong>ear background is performed on the <strong>in</strong>variant mass distribution of � � pairs without any selection<br />
apart from the hadronic one described <strong>in</strong> Sec. 3.3. The number of the reconstructed Ã Ë is taken from the<br />
area under the two Gaussians. The reason of the fit with a double Gaussian distribution can be understood<br />
look<strong>in</strong>g at the distribution of the <strong>in</strong>variant mass of true Monte Carlo Ã Ë : <strong>in</strong> Fig. 3-8 the tails of the second<br />
Gaussian can be clearly seen.<br />
Table 3-3 conta<strong>in</strong>s the number of observed Ã Ë : this is the result of the fits to the plots <strong>in</strong> Fig.3-9. Therefore<br />
the efficiency can be calculated:<br />
sample variable block 1 block 2<br />
Monte Carlo �corr ���� �� �<br />
� corr<br />
ÃË<br />
� � ks/ev � � ks/ev<br />
on-res data # of expected ÃË ��� ��� ��<br />
# of reconstructed Ã Ë � � ¦ � ¦ �<br />
Table 3-3. Number of Ã Ë per event, number of expected and reconstructed events.<br />
Ã Ë RECONSTRUCTION AND EFFICIENCY STUDIES
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