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A quantum algorithm for quadratic optimization

Published on:

19 September 2023

Primary Category:

Quantum Physics

Paper Authors:

Hongyi Zhou,

Sirui Peng,

Qian Li,

Xiaoming Sun

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Key Details

Encodes variables in quantum state amplitudes for logarithmic qubit scaling

Handles general quadratic constraints with classical primal-dual method

Outperforms classical algorithms on power flow and graph cut problems

Suitable for current quantum devices unlike prior quantum algorithms

Marks progress on using quantum for large-scale quadratic optimization

AI generated summary

A quantum algorithm for quadratic optimization

This paper proposes a hybrid quantum-classical algorithm to solve quadratically constrained quadratic optimization problems. By encoding variables in quantum states, it requires far fewer qubits than prior methods. It handles general quadratic constraints using a classical primal-dual interior point method. Experiments on power flow and graph cut problems show it can outperform classical algorithms.

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