Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances.
翻译:从2015年到2019年,由地平线(Foround 2020)资助、名为“AMVA4NewPhysics”的创新培训网络的成员研究了先进多变分析方法和统计学习工具对高能物理问题的定制和应用,并开发了全新的方法,其中许多方法成功地用于提高ATLAS和CMS在CERN大型哈德龙对撞机实验中进行的数据分析的敏感性;其他一些仍在测试阶段的网络成员则承诺进一步提高基本物理参数测量的精确度和寻找新现象的覆盖范围;本文介绍了研究与开发中最相关的新工具,其中包括对其性能的评估。