Qsun: an open-source platform towards practical quantum machine learning applications

TL;DR

Qsun is an open-source quantum virtual machine designed to facilitate the development and testing of variational quantum algorithms for practical quantum machine learning applications, supporting quantum differentiable programming.

Contribution

The paper introduces Qsun, a quantum virtual machine that supports variational quantum algorithms and quantum differentiable programming, enabling practical quantum machine learning development.

Findings

Successfully implemented quantum linear regression.

Developed quantum neural network models.

Demonstrated the platform's capability for quantum ML tasks.

Abstract

Currently, quantum hardware is restrained by noises and qubit numbers. Thus, a quantum virtual machine that simulates operations of a quantum computer on classical computers is a vital tool for developing and testing quantum algorithms before deploying them on real quantum computers. Various variational quantum algorithms have been proposed and tested on quantum virtual machines to surpass the limitations of quantum hardware. Our goal is to exploit further the variational quantum algorithms towards practical applications of quantum machine learning using state-of-the-art quantum computers. This paper first introduces our quantum virtual machine named Qsun, whose operation is underlined by quantum state wave-functions. The platform provides native tools supporting variational quantum algorithms. Especially using the parameter-shift rule, we implement quantum differentiable programming essential for gradient-based optimization. We then report two tests representative of quantum machine learning: quantum linear regression and quantum neural network.