信号和背景不对称性的同时测定
Simultaneous Determination of Signal and Background Asymmetries
摘要：
本文讨论了不对称性的确定。我们考虑一个样本的事件组成的信号事件的峰值上的一些背景事件。信号和背景都具有未知的不对称性，例如自旋或前后不对称性。提出了一种利用事件加权同时确定信号和背景不对称性的方法。对于消失的不对称性的统计误差达到最小方差界（MVB）的Cramér-Rao不等式给出的，它是非常接近它为大的不对称性。因此，与背景不对称性的边带减法的经典方法相比，该方法提供了显著的统计增益。相对于未分箱的极大似然方法，它具有优点，也达到了MVB，即它不需要在最小化过程中对事件样本进行循环。
英文摘要：
This article discusses the determination of asymmetries. We consider a sample of events consisting of a peak of signal events on top of some background events. Both signal and background have an unknown asymmetry, e.g. a spin or forward-backward asymmetry. A method is proposed which determines signal and background asymmetries simultaneously using event weighting. For vanishing asymmetries the statistical error of the asymmetries reaches the minimal variance bound (MVB) given by the Cramér-Rao inequality and it is very close to it for large asymmetries. The method thus provides a significant gain in statistics compared to the classical method of side band subtraction of background asymmetries. It has the advantage with respect to the unbinned maximum likelihood approach, reaching the MVB as well, that it does not require loops over the event sample in the minimization procedure.
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