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Bandwidth analysis and improvement of the beam phasing of fiber amplifiers using the stochastic parallel gradient descent algorithm

机译:随机并行梯度下降算法对光纤放大器的光束相位进行带宽分析和改进

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摘要

We present the numerical analysis and improvement of the bandwidth of the beam phasing of fiber amplifiers using the stochastic parallel gradient descent (SPGD) algorithm. Time-varying phase distortions are incorporated into the dynamic simulation. It is shown by numerical calculation that the bandwidth of the standard SPGD algorithm is dependent on the phase distortions and on the number of lasers. The time-averaged cost function will decrease with an increase in the amplitude and frequency of phase distortions, and in the number of lasers. A cross-grouped SPGD algorithm is proposed, which offers attractive performance due to its robustness to various time-vary ing phase distortions and faster convergence rate for beam phasing of larger number of lasers. Dynamic simulation shows that the control bandwidth can be improved using the cross-grouped SPGD algorithm.
机译:我们提出了使用随机并行梯度下降(SPGD)算法对光纤放大器的光束定相带宽进行数值分析和改进。时变相位畸变被纳入动态仿真中。通过数值计算表明,标准SPGD算法的带宽取决于相位失真和激光器的数量。时间平均成本函数将随着相位失真的幅度和频率以及激光器数量的增加而降低。提出了一种交叉分组的SPGD算法,该算法由于其对各种随时间变化的相位畸变的鲁棒性以及对大量激光器的光束定相具有更快的收敛速度而具有出色的性能。动态仿真表明,使用交叉分组的SPGD算法可以提高控制带宽。

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