摘要
粒子群优化算法具有良好的全局寻优能力,但也存在容易陷入局部极值、后期收敛速度慢、收敛精度低等问题。为此,首先优化了传统粒子群算法,将其简化并引入随机扰动,赋予粒子跳出局部极值的能力,提高算法的全局寻优性能。然后结合贪心算法并引入梯度下降法作为算法自动切换的判据,从而构造一种针对光子器件逆向设计的混合算法。相较于传统粒子群算法,该混合算法具有更优的全局寻优能力,并且提高了收敛速度和收敛精度,具备更高的设计效率。利用该混合算法逆向设计了一种1∶1分光器,在120 nm带宽内,输出端插入损耗介于0.125 dB~0.197 dB,并具有可制造的鲁棒性。
Particle swarm optimization(PSO)algorithm has good global optimization ability.However,PSO has some disadvantages such as the tendency to easily fall into local extremes,slow convergence speed,and low convergence accuracy at the late stage of the algorithm.Therefore,this study optimizes the traditional PSO algorithm,affording a simplified version and introducing random disturbances to facilitate the falling out of local extremes,thus enhancing its performance on global optimization.Moreover,a hybrid algorithm for the inverse design of photonic devices is proposed by combining PSO and the greedy algorithm with the gradient descent method to evaluate automatic switching between algorithms.Compared with the traditional PSO algorithm,the proposed hybrid algorithm shows better performance on global optimization with a faster convergence speed,higher accuracy,and superior design efficiency.A 1∶1 optical splitter is inversely designed using the proposed hybrid algorithm.At a bandwidth of 120 nm,the range of insertion loss at the output of the device is 0.125 dB‒0.197 dB.Moreover,the device is manufacturable robustness.
作者
李映函
吕杰
江琳
程凌浩
Li Yinghan**;LüJie;Jiang Lin;Cheng Linghao(Institute of Photonics Technology,Jinan University,Guangzhou 510632,Guangdong,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2022年第11期274-281,共8页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61875246)
广州市科技计划项目(201904020032)。
关键词
集成光学
光学器件
逆向设计
粒子群算法
贪心算法
梯度下降法
分光器
integrated optics
optics devices
inverse design
particle swarm optimization algorithm
greedy algorithm
gradient descent
optical splitter