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Quantum Optimization

A hybrid algorithm for quadratically constrained quadratic optimization problems

arXiv
Authors: Hongyi Zhou, Sirui Peng, Qian Li, Xiaoming Sun

Year

2023

Paper ID

54690

Status

Preprint

Abstract Read

~2 min

Abstract Words

103

Citations

N/A

Abstract

Quadratically Constrained Quadratic Programs (QCQPs) are an important class of optimization problems with diverse real-world applications. In this work, we propose a variational quantum algorithm for general QCQPs. By encoding the variables on the amplitude of a quantum state, the requirement of the qubit number scales logarithmically with the dimension of the variables, which makes our algorithm suitable for current quantum devices. Using the primal-dual interior-point method in classical optimization, we can deal with general quadratic constraints. Our numerical experiments on typical QCQP problems, including Max-Cut and optimal power flow problems, demonstrate a better performance of our hybrid algorithm over the classical counterparts.

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  • This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
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  • Quadratically Constrained Quadratic Programs (QCQPs) are an important class of optimization problems with diverse real-world applications.

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