Title: Pandemonium: a clustering tool to partition parameter space -- application to the B anomalies Show Chinese title

Title: 混乱：一种用于划分参数空间的聚类工具——应用于B介子异常

Abstract: We introduce the interactive tool pandemonium to cluster model predictions that depend on a set of parameters. The model predictions are used to define the coordinates in observable space which go into the clustering. The results of this partitioning are then visualized in both observable and parameter space to study correlations between them. The tool offers multiple choices for coordinates, distance functions and linkage methods within hierarchical clustering. It provides a set of diagnostic statistics and visualization methods to study the clustering results in order to interpret the outcome. The methods are most useful in an interactive environment that enables exploration, and we have implemented them with a graphical user interface in R. We demonstrate the concepts with an application to phenomenological studies in flavor physics in the context of the so-called B anomalies. Show Chinese abstract

Abstract: 我们引入了交互式工具pandemonium，用于对依赖于一组参数的模型预测进行聚类。 模型预测用于定义可观测空间中的坐标，这些坐标进入聚类过程。 然后在可观测空间和参数空间中可视化此划分的结果，以研究它们之间的相关性。 该工具在层次聚类中提供了多种坐标选择、距离函数和链接方法。 它提供了一组诊断统计量和可视化方法，以研究聚类结果，从而解释结果。 这些方法在交互式环境中最为有用，可以实现探索，我们已在R中用图形用户界面实现了它们。 我们通过在所谓B异常背景下味物理现象学研究的应用来演示这些概念。