Saved in:
Bibliographic Details
Main Authors: Zhang, Shuai, Guo, Yu-Chen, Yang, Ji-Chong
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2311.15280
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916366798290944
author Zhang, Shuai
Guo, Yu-Chen
Yang, Ji-Chong
author_facet Zhang, Shuai
Guo, Yu-Chen
Yang, Ji-Chong
contents The search of the new physics~(NP) beyond the Standard Model is one of the most important topics in current high energy physics. With the increasing luminosities at the colliders, the search for NP signals requires the analysis of more and more data, and the efficiency in data processing becomes particularly important. As a machine learning algorithm, support vector machine~(SVM) is expected to to be useful in the search of NP. Meanwhile, the quantum computing has the potential to offer huge advantages when dealing with large amounts of data, which suggests that quantum SVM~(QSVM) is a potential tool in future phenomenological studies of the NP. How to use SVM and QSVM to optimize event selection strategies to search for NP signals are studied in this paper. Taking the tri-photon process at a muon collider as an example, it can be shown that the event selection strategies optimized by the SVM and QSVM are effective in the search of the dimension-8 operators contributing to the anomalous quartic gauge couplings.
format Preprint
id arxiv_https___arxiv_org_abs_2311_15280
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Optimize the event selection strategy to study the anomalous quartic gauge couplings at muon colliders using the support vector machine and quantum support vector machine
Zhang, Shuai
Guo, Yu-Chen
Yang, Ji-Chong
High Energy Physics - Phenomenology
The search of the new physics~(NP) beyond the Standard Model is one of the most important topics in current high energy physics. With the increasing luminosities at the colliders, the search for NP signals requires the analysis of more and more data, and the efficiency in data processing becomes particularly important. As a machine learning algorithm, support vector machine~(SVM) is expected to to be useful in the search of NP. Meanwhile, the quantum computing has the potential to offer huge advantages when dealing with large amounts of data, which suggests that quantum SVM~(QSVM) is a potential tool in future phenomenological studies of the NP. How to use SVM and QSVM to optimize event selection strategies to search for NP signals are studied in this paper. Taking the tri-photon process at a muon collider as an example, it can be shown that the event selection strategies optimized by the SVM and QSVM are effective in the search of the dimension-8 operators contributing to the anomalous quartic gauge couplings.
title Optimize the event selection strategy to study the anomalous quartic gauge couplings at muon colliders using the support vector machine and quantum support vector machine
topic High Energy Physics - Phenomenology
url https://arxiv.org/abs/2311.15280