Variational quantum support vector machine based on Gamma matrix expansion and variational universal-quantum-state generator

Abstract

We analyze a binary classification problem by using a support vector machine based on variational quantum-circuit model. We propose to solve a linear equation of the support vector machine by using a Gamma matrix expansion. In addition, it is shown that an arbitrary quantum state is prepared by optimizing a universal quantum circuit representing an arbitrary U(2^N) based on the steepest descent method. It may be a quantum generalization of Field-Programmable-Gate Array (FPGA).