arXiv 2409.070102024-09hep-ph

在μ子对撞机上利用量子核k-means探测反常四规规范耦合

Detect anomalous quartic gauge couplings at muon colliders with quantum kernel k-means

Shuai Zhang, Ke-Xin Chen, Ji-Chong Yang

备注：: update journal refence
发表信息：: Eur. Phys. J. C 85:378 (2025)
DOI：: 10.1140/epjc/s10052-025-14069-1

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AI总结：

本文提出利用量子核k-means异常检测策略在μ子对撞机上搜索新物理信号，以$μ^+μ^-\to v\bar{v}γγ$过程为例研究了反常四规规范耦合，结果表明该方法能有效发现aQGCs信号。

摘要：

近年来，随着对撞机亮度的不断提高，处理日益增长的数据量已成为未来新物理（NP）唯象研究的一大挑战。为提高效率，机器学习算法已被引入高能物理领域。作为一种机器学习算法，核k-means已被证明在搜索NP信号方面十分有用。众所周知，核k-means算法可以借助量子计算来实现，这表明量子核k-means（QKKM）也是未来NP唯象研究的潜在工具。本文研究如何利用具有量子核的k-means异常检测事件选择策略来搜索NP信号。以μ子对撞机上的$μ^+μ^-\to v\bar{v}γγ$过程为例，研究了导致反常四规规范耦合（aQGCs）的dimension-8算子。给出了使用三种不同形式量子核的QKKM和k-means算法获得的预期系数约束，结果表明QKKM有助于发现aQGCs的信号。

英文摘要：

In recent years, with the increasing luminosities of colliders, handling the growing amount of data has become a major challenge for future New Physics~(NP) phenomenological research. To improve efficiency, machine learning algorithms have been introduced into the field of high-energy physics. As a machine learning algorithm, kernel k-means has been demonstrated to be useful for searching NP signals. It is well known that the kernel k-means algorithm can be carried out with the help of quantum computing, which suggests that quantum kernel k-means~(QKKM) is also a potential tool for NP phenomenological studies in the future. This paper investigates how to search for NP signals using the k-means anomaly detection event selection strategy with quantum kernels. Taking the $μ^+μ^-\to v\bar{v}γγ$ process at a muon collider as an example, the dimension-8 operators contributing to anomalous quartic gauge couplings~(aQGCs) are studied. The expected coefficient constraints obtained using the QKKM of three different forms of quantum kernels and k-means algorithm are presented, it can be shown that QKKM can help to find the signal of aQGCs.

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