Quantum Approximate Bayesian Optimization Algorithms With Two Mixers and Uncertainty Quantification

Quantum Approximate Bayesian Optimization Algorithms With Two Mixers and Uncertainty Quantification

The searching efficiency of the quantum approximate optimization algorithm is dependent on both the classical and quantum sides of the algorithm. Recently, a quantum approximate Bayesian optimization algorithm (QABOA) that includes two mixers was developed, where surrogate-based Bayesian optimizatio...

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Bibliographic Details
Main Authors: Jungin E. Kim, Yan Wang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Quantum Engineering
Subjects:
Exploration–exploitation
mixed-integer optimization
noisy intermediate-scale quantum algorithms and devices
quantum approximate optimization algorithm
uncertainty quantification
Online Access:https://ieeexplore.ieee.org/document/10296859/

Internet

https://ieeexplore.ieee.org/document/10296859/

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