  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.
