Diffractive optical elements for implementing spatial demultiplexing and spectral synthesizing simultaneously

Sun, Xiaodong; Liu, Juan; Wang, Yiquan; Zhang, Bo; Hu, Bin; Di, Si; Wang, Shangqi

doi:10.1016/j.optcom.2006.05.022

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…The search algorithms, including local search algorithms and global search algorithms, theoretically can get a better solution, compared with the traditional iterative algorithms. However, the former, including the steepest descent [24], conjugate gradient [25], and direct binary search (DBS) [26] algorithms, tend to fall into local extreme points and cannot jump out. The latter mainly includes the simulated annealing (SA) algorithm [27], genetics algorithm (GA) [28][29][30], particle swarm optimization (PSO) [31][32][33], etc.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Diffractive Optical Element Design Algorithm Combining Particle Swarm Optimization and a Simulated Annealing Algorithm

Cai

Song

et al. 2020

Applied Sciences

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With the rapid development of computer hardware and the emergence of the parallel calculation of diffraction fields, a breakthrough has been made in terms of the limitation of the unacceptable amount of computational cost to design diffractive optical elements (DOEs), and more accurate global search algorithms can be introduced to the design of complex DOEs and holographic projections instead of traditional iterative algorithms. In this paper, a hybrid algorithm which combines particle swarm optimization (PSO) with a simulated annealing (SA) algorithm is proposed for the designing of DOEs and projecting holographic images with less noise. PSO is used to reduce the invalid disturbance in SA, and SA can jump out from local extreme points to find the global extreme points. Compared with the traditional Gerchberg–Saxton (GS) algorithm, the simulation and experimental results demonstrate that the proposed SA–PSO hybrid algorithm can improve uniformity by more than 10%.

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