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Violation in Mixing

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90 Ã Ë reconstruction and efficiency studies<br />

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Figure 3-10. On resonance data: Ã Ë reconstruction efficiency as function of decay length of the Ã Ë ’s <strong>in</strong><br />

both block 1 (left) and 2 (right) samples. 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 �� � Æ��ÆØÓØ� , Æ� is the number of ÃË <strong>in</strong> the b<strong>in</strong> number �, ÆØÓØ� is the total number of ÃË candidates<br />

<strong>in</strong> the � sample and � � are the correction values for the � sample. The error �� � on the correction is then<br />

given by:<br />

� � � �<br />

× �<br />

�<br />

��� ¡ × � � ℄<br />

where × � �<br />

1 and block 2), the f<strong>in</strong>al correction should be calculated from a weighted average of �� and �� where the weights should be the relative lum<strong>in</strong>osities of the two samples.<br />

values<br />

are the errors on the correction values for the � sample. Tak<strong>in</strong>g <strong>in</strong>to account both samples (block<br />

An example of the f<strong>in</strong>al correction can come from the analysis � ¦ � Ã Ë � ¦ : from the first set of<br />

corrections, one gets � ¦ � � while from second set of corrections with the momentum cut, one gets<br />

� � ¦ � �. The f<strong>in</strong>al correction would be:<br />

�ÃË� � � � ¦ � �(stat) ¦ � (syst)<br />

3.3.5 Run 2 data sample: first look at the Ã Ë reconstruction<br />

These runs correspond to a subsample of the so-called block 1 data set <strong>in</strong> Run 2. The data sample consists<br />

of:<br />

MARCELLA BONA

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