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Violation in Mixing

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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

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