Violation in Mixing
Violation in Mixing
Violation in Mixing
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
104 Strategy and Tools for Charmless Two-body � Decays Analysis<br />
Events/2.5 MeV/c 2<br />
150<br />
100<br />
50<br />
BABAR<br />
mES(D 0 0<br />
5.22 5.24 5.26 5.28 5.3<br />
π)<br />
Events/10 MeV/c 2<br />
100<br />
50<br />
0<br />
BABAR<br />
ΔE(D 0 -0.1 0 0.1<br />
π)<br />
Figure 4-3. Ñ�Ë and ¡� distributions for � � � � candidates.<br />
For consistency, the same charmless two-body selection is applied to the � � � � decays. � and �<br />
candidates are reconstructed us<strong>in</strong>g the vertex algorithm and the mass constra<strong>in</strong>t is applied to the � . The<br />
kaon from the � has been required to be selected by the loose kaon selector. Figure 4-3 shows the Ñ�Ë and<br />
¡� distributions of the selected events <strong>in</strong> the signal region (�¡�� � � Å�Î). Fits to these distributions<br />
<strong>in</strong>dicate approximately ��� �’s <strong>in</strong> the Ñ�Ë peak.<br />
When background subtraction is required, the signal region is def<strong>in</strong>ed as ��� Ñ�Ë around � Ñ�Ë of<br />
�� � ��Î (� Ñ�Ë � ��Å�Î). The side-band is taken as �� �Ñ�Ë � �� � ��Î. Proper normalization<br />
of this side-band to the signal region is obta<strong>in</strong>ed us<strong>in</strong>g the ARGUS background parameterization (see<br />
Eq. 4.12).<br />
For validation of ¡� resolution, a Gaussian plus first other polynomial fit to ¡� <strong>in</strong> data <strong>in</strong>dicates a<br />
resolution of � ¦ � Å�Î. In Monte Carlo the resolution is found to be �� ¦ � � Å�Î.<br />
4.3 Background fight<strong>in</strong>g<br />
In addiction to the previous def<strong>in</strong>ed topological variables, a Fisher discrim<strong>in</strong>ant technique is used to separate<br />
signal from background. The Fisher discrim<strong>in</strong>ant � is calculated from a l<strong>in</strong>ear comb<strong>in</strong>ation of Æ<br />
discrim<strong>in</strong>at<strong>in</strong>g variables �,<br />
� �<br />
�<br />
��<br />
«�Ü�� (4.7)<br />
where the coefficients «� are called Fisher coefficients. They are chosen to maximize the statistical separation<br />
between signal (Ë) and background (�) events through the function Ë � � Ë � . The coefficients<br />
MARCELLA BONA