Wu Kenan, Sun Yang, Huai Ying, Jia Shuqin, Chen Xi, Jin Yuqi
Opt Express. 2015 Feb 9;23(3):2933-44. doi: 10.1364/OE.23.002933.
The multi-perturbation stochastic parallel gradient descent (SPGD) method for adaptive optics is presented in this work. The method is based on a new architecture. The incoming beam with distorted wavefront is split into N sub-beams. Each sub-beam is modulated by a wavefront corrector and its performance metric is measured subsequently. Adaptive system based on the multi-perturbation SPGD can operate in two modes - the fast descent mode and the modal basis updating mode. Control methods of the two operation modes are given. Experiments were carried out to prove the effectiveness of the proposed method. Analysis as well as experimental results showed that the two operation modes of the multi-perturbation SPGD enhance the conventional SPGD in different ways. The fast descent mode provides faster convergence than the conventional SPGD. The modal basis updating mode can optimize the modal basis set for SPGD with global coupling.
本文提出了用于自适应光学的多扰动随机并行梯度下降（SPGD）方法。该方法基于一种新架构。具有畸变波前的入射光束被分成N个子光束。每个子光束由一个波前校正器调制，随后测量其性能指标。基于多扰动SPGD的自适应系统可以在两种模式下运行——快速下降模式和模态基更新模式。给出了两种运行模式的控制方法。通过实验证明了所提方法的有效性。分析和实验结果表明，多扰动SPGD的两种运行模式以不同方式增强了传统的SPGD。快速下降模式比传统SPGD收敛更快。模态基更新模式可以为具有全局耦合的SPGD优化模态基集。
