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Quantum Optimization
Analog Quantum Approximate Optimization Algorithm
arXiv
Authors: Nancy Barraza, Gabriel Alvarado Barrios, Jie Peng, Lucas Lamata, Enrique Solano, Francisco Albarrán-Arriagada
Year
2021
Paper ID
40666
Status
Preprint
Abstract Read
~2 min
Abstract Words
87
Citations
N/A
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.
Why This Paper Matters
- This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- We present an analog version of the quantum approximate optimization algorithm suitable for current quantum annealers.
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