  This paper aims to solve machine learning optimization problem by using
quantum circuit. Two approaches, namely the average approach and the Partial
Swap Test Cut-off method (PSTC) was proposed to search for the global
minimum/maximum of two different objective functions. The current cost is
$O(\sqrt{|\Theta|} N)$, but there is potential to improve PSTC further to
$O(\sqrt{|\Theta|} \cdot sublinear \ N)$ by enhancing the checking process.

Quantum Physics;Machine Learning;Machine Learning