标题： 贝叶斯概率理论在以往和未来顶夸克对撞机实验中二项数据测量中的应用 显示英文标题

标题： Application of Bayesian probability theory to the measurement of binomial data at past and future Tevatron experiments

摘要： 将测量的二项式量，即样本中通过一个筛选条件的事件比例，转换为物理的二项式量，即来自信号源的事件比例的实验问题被描述为一组线性方程。 这组线性系统展示了实验数据分析中的几个熟悉方面。 使用贝叶斯概率理论来找到一种解决此二项式测量问题的方法，该方法允许直接构建置信区间。 还表明，该解决方案提供了在不同筛选选择下评估数据集行为的无偏形式化方法，包括一个旨在提高可能但此前未见过的信号显著性的筛选。 使用多个示例来说明该方法的特性，包括顶夸克的发现以及与$W^{\pm}$玻色子一起产生的新粒子的搜索。 还演示了如何使用此方法对在对撞机运行2实验中潜在发现标准模型希格斯玻色子进行预测，以及通过包含性$p\bar{p} \to W^{\pm}$产生来测量积分亮度的实用性。 显示英文摘要

摘要： The experimental problem of converting a measured binomial quantity, the fraction of events in a sample that pass a cut, into a physical binomial quantity, the fraction of events originating from a signal source, is described as a system of linear equations. This linear system illustrates several familiar aspects of experimental data analysis. Bayesian probability theory is used to find a solution to this binomial measurement problem that allows for the straightforward construction of confidence intervals. This solution is also shown to provide an unbiased formalism for evaluating the behavior of data sets under different choices of cuts, including a cut designed to increase the significance of a possible, albeit previously unseen, signal. Several examples are used to illustrate the features of this method, including the discovery of the top quark and searches for new particles produced in association with $W^{\pm}$ bosons. It is also demonstrated how to use this method to make projections for the potential discovery of a Standard Model Higgs boson at a Tevatron Run 2 experiment, as well as the utility of measuring the integrated luminosity through inclusive $p\bar{p} \to W^{\pm}$ production.