Application and Research of Quantum Optimisation Control Algorithms in Adaptive Optics Systems

Hui Zhang; Runchu Zou; Zihao Lv; Zhao Wang

doi:10.54097/rh2zpm28

Authors

Hui Zhang
Runchu Zou
Zihao Lv
Zhao Wang

DOI:

https://doi.org/10.54097/rh2zpm28

Keywords:

Quantum Network, Fiber Coupling, Adaptive Optics, Optimization Algorithm, QPSO

Abstract

Adaptive optics plays a crucial role in improving the stability and correcting aberrations of optical systems, whose performance largely depends on the optimization capability and convergence characteristics of control algorithms. Traditional control algorithms, such as genetic algorithm (GA), simulated annealing (SA), and stochastic parallel gradient descent (SPGD), have been widely applied; however, they exhibit certain limitations in global optimization ability, convergence speed, and noise immunity. In recent years, quantum optimization algorithms have attracted extensive attention owing to their potential advantages in global search and acceleration. Focusing on the application scenario of using adaptive optics to enhance fiber coupling efficiency, this paper investigates the feasibility of quantum optimization control algorithms. Taking quantum particle swarm optimization (QPSO) as a representative, a systematic comparison is conducted with traditional methods including GA, SA, and SPGD. The results demonstrate that under typical disturbance conditions, quantum optimization methods show significant advantages in improving fiber coupling efficiency, reducing the search time for optimal solutions, and enhancing system stability. This study indicates that adaptive optics control methods based on quantum optimization can provide a novel technical approach for stable and efficient coupling of optical links, and possess important application potential in the construction of quantum networks with ion traps as nodes.

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