Analog Quantum Approximate Optimization Algorithm
Quantum Physics
2022-10-11 v2 Mesoscale and Nanoscale Physics
Abstract
We present an analog version of the quantum approximate optimization algorithm suitable for current quantum annealers. The central idea of this algorithm is to optimize the schedule function, which defines the adiabatic evolution. It is achieved by choosing a suitable parametrization of the schedule function based on interpolation methods for a fixed time, with the potential to generate any function. This algorithm provides an approximate result of optimization problems that may be developed during the coherence time of current quantum annealers on their way toward quantum advantage.
Cite
@article{arxiv.2112.07461,
title = {Analog Quantum Approximate Optimization Algorithm},
author = {Nancy Barraza and Gabriel Alvarado Barrios and Jie Peng and Lucas Lamata and Enrique Solano and Francisco Albarrán-Arriagada},
journal= {arXiv preprint arXiv:2112.07461},
year = {2022}
}
Comments
13 pages, 4 figures