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随机并行梯度下降算法(SPGD)是控制多路激光束的相位锁定,实现相干合成的一种有效方式。在分析平移误差和倾斜误差对相干合成(CBC)影响的基础上,建立2×2排布的光束模型探讨了该算法中的增益系数和扰动幅值对平移误差和倾斜误差控制的影响,并对增益系数的优化进行了分析。研究结果表明,要提高相干合成的效果,必须同时校正平移误差和倾斜误差;随着增益系数和扰动幅值的增加,SPGD算法的收敛速度加快,但计算精度降低,系统会发生振荡;自适应更新增益系数是一种有效的参数优化方式,可很好平衡算法收敛速度和计算精度问题。为大型固体短脉冲激光装置中基于SPGD算法进行相干合成研究提供了理论参考。
The Stochastic Parallel Gradient Descent Algorithm (SPGD) is an effective way to control the phase locking of multiple laser beams and achieve coherent synthesis. Based on the analysis of the effects of translation error and tilt error on CBC, the influence of the gain coefficient and the disturbance amplitude on the translation error and tilt error control of the algorithm is discussed based on the 2 × 2 beam model. The optimization of the gain coefficient is analyzed. The results show that to improve the effect of coherent synthesis, translation error and tilt error must be corrected at the same time. With the increase of gain coefficient and disturbance amplitude, the convergence speed of SPGD algorithm accelerates, but the calculation accuracy decreases and the system oscillates. Adaptive Updating the gain coefficient is an effective way to optimize the parameters, which can well balance the convergence speed and accuracy of the algorithm. It provides a theoretical reference for the research of coherent synthesis based on SPGD algorithm in large solid short pulse laser devices.