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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.
Why This Paper Matters
- This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
- It adds a 2023 reference point for readers tracking recent quantum research.
- Quadratically Constrained Quadratic Programs (QCQPs) are an important class of optimization problems with diverse real-world applications.
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