The adaptive gradient (AdaGrad) method is an optimization algorithm widely used in the field of artificial intelligence. An adaptive gradient stochastic parallel gradient descent (SPGD) algorithm (AdaSPGD algorithm), combining an AdaGrad algorithm with an SPGD algorithm, is innovatively introduced and implemented in coherent beam synthesis. The performance of a coherent beam combination system utilizing the AdaSPGD method is validated by numerical simulation of straightening static phase aberrations. The results of the simulations indicate that the AdaSPGD algorithm not only can effectively solve the trouble of difficulty in selecting the gain coefficient in the actual beam combining system, but also can accelerate the convergence of the phase control algorithm. Furthermore, the effectiveness of the proposed algorithm is demonstrated by means of the experimental investigation on coherent beam synthesis of a two-channel fiber array. The AdaSPGD algorithm is a satisfactory modific...

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改进的随机平行梯度下降算法相干光束合成的数值和实验研究

自适应梯度（AdaGrad）方法是一种在人工智能领域广泛使用的优化算法。在相干波束合成中创新性地引入了自适应梯度随机并行梯度下降算法（AGDSPGD），该算法将AdaGrad算法与SPGD算法相结合。通过矫正静态相差的数值模拟，验证了采用AdaSPGD方法的相干光束组合系统的性能。仿真结果表明，AdaSPGD算法不仅可以有效解决实际光束合成系统中增益系数选择困难的问题，而且可以加快相位控制算法的收敛速度。此外，通过对两通道光纤阵列相干光束合成的实验研究证明了该算法的有效性。AdaSPGD算法是令人满意的修改...