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High Energy Physics event selection with Gene Expression Programming

机译:利用基因表达编程进行高能物理事件选择

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摘要

Gene Expression Programming is a new evolutionary algorithm that overcomes many limitations of the more established Genetic Algorithms and Genetic Programming. Its application to event selection in high energy physics data analysis is presented using as an example application the selection of K-S particles produced in e(+)e(-) interactions at 10 GeV and reconstructed in the decay mode K-S -> pi(+)pi(-). The algorithm was used for automatic identification of classification criteria for signallbackground separation. For the problem studied and for data samples with signal to background ratios between 0.25 and 5, the classification accuracy obtained with the criteria developed by the GEP algorithm was in the range of 92-95%. (C) 2007 Elsevier B.V. All rights reserved.
机译:基因表达编程是一种新的进化算法,它克服了已建立的遗传算法和遗传编程的许多限制。以在10 GeV的e(+)e(-)相互作用中产生并以衰减模式KS-> pi(+)重构的KS粒子的选择为例,介绍了其在高能物理数据分析中的事件选择中的应用。 pi(-)。该算法用于自动识别信号背景分离的分类标准。对于所研究的问题以及信噪比在0.25与5之间的数据样本,使用GEP算法开发的标准获得的分类精度在92%到95%之间。 (C)2007 Elsevier B.V.保留所有权利。

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