随机并行梯度下降自适应光学对主振荡功率放大器激光系统的光束净化实验

Beam Cleanup Experiments for Master Oscillator Power Amplifier Laser System by Adaptive Optics Based on Stochastic Parallel Gradient Descent Algorithm

主振荡功率放大器(MOPA)固体激光系统中的功率放大器会将热致波前畸变引入到被放大的激光束中,造成输出光束质量变差,可以通过自适应光学(AO)系统实时补偿光束的波前畸变以改善光束质量。采用随机并行梯度下降(SPGD)算法控制一个37单元变形镜,通过光电探测器测量远场光斑的桶中功率作为评价光束质量的判据,建立了一个迭代速率为100 Hz的最优化自适应光学系统,对由Nd:YAG主振荡器与Nd:YAG功率放大器组成的MOPA激光系统在不同抽运电流情况下的输出光束进行了净化实验。结果显示,净化后光束质量都得到了提高,甚至β因子大于9的光束在净化后其β因子也减小了58%,表明基于随机并行梯度下降算法的自适应光学方法确实可以用于光束净化。

Thermal aberrations are introduced into the amplified laser beam in power amplifier of a master oscillator power amplifier （MOPA） solid state laser system and degrade the beam quality. Adaptive optics （AO） system can be used to compensate for the wavefront aberrations in real time to improve the beam quality. An optimization-type adaptive optics system with the iteration rate of 100 Hz was built up. In this system, a 37-element deformable mirror is controlled by the stochastic parallel gradient descent （SPGD） algorithm with the power-in-bucket of the far-field laser beam as the metric, which is measured by a photoelectric detector. The beam cleanup experiments were performed by the SPGD AO system for the MOPA laser system comprised of Nd： YAG master oscillator and Nd： YAG power amplifier at different pumping currents. The results show that the beam quality is improved in all cases, and even for the beam with a beam quality of β〉9, the fl factor is decreased by 58% after cleanup. It is indicated that adaptive optics based on stochastic parallel gradient descent algorithm can be used to beam cleanup.