MACHINE LEARNING BASED EVENT RECONSTRUCTION FOR THE MUONE EXPERIMENT

被引：0

作者：

Zdybal, Mi losz ^{[1
]}

Kucharczyk, Marcin ^{[1
]}

Wolter, Marcin ^{[1
]}

机构：

[1] Polish Acad Sci, Henryk Niewodniczanski Inst Nucl Phys, Krakow, Poland

来源：

COMPUTER SCIENCE-AGH | 2024年 / 25卷 / 01期

关键词：

machine learning; artificial neural networks; track reconstruction; high energy physics;

D O I：

10.7494/csci.2024.25.1.5690

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A proof-of-concept solution based on the machine learning techniques has been implemented and tested within the MUonE experiment designed to search for New Physics in the sector of anomalous magnetic moment of a muon. The results of the DNN based algorithm are comparable to the classical reconstruction, reducing enormously the execution time for the pattern recognition phase. The present implementation meets the conditions of classical reconstruction, providing an advantageous basis for further studies.

引用

页码：25 / 46

页数：22

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