Paper
24 May 2023 Optical design of off-axis three-mirror reflective system by neural networks
Author Affiliations +
Proceedings Volume 12706, First International Conference on Spatial Atmospheric Marine Environmental Optics (SAME 2023); 127060J (2023) https://doi.org/10.1117/12.2682144
Event: First International Conference on Spatial Atmospheric Marine Environmental Optics (SAME 2023), 2023, Shanghai, China
Abstract
We incorporate neural networks into the optical design of off-axis three-mirror reflective system, enabling us to achieve design outcomes without relying on iteration or ray tracing methods. Our approach involves combining analytical relations with neural networks during the design process, which yields results covering the entire parameter space with a single user input, and each design is scored simultaneously. Our results demonstrate that neural networks can simulate the complex relationship between performance requirements and structural parameters of an optical system. As such, the structural parameters can be directly obtained from the performance requirements, replacing the iterative optimization process traditionally used. This approach leads to relatively efficient and straightforward optical design. We anticipate that this method can be extended to various optical systems, reducing the experience threshold and difficulty of optical design.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wanqing Huang, Xibo Sun, Yu Xie, Yuanchao Geng, Lanqing Liu, Wenyi Wang, and Ying Zhang "Optical design of off-axis three-mirror reflective system by neural networks", Proc. SPIE 12706, First International Conference on Spatial Atmospheric Marine Environmental Optics (SAME 2023), 127060J (24 May 2023); https://doi.org/10.1117/12.2682144
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KEYWORDS
Neural networks

Design and modelling

Optical design

Artificial neural networks

Ray tracing

Mirrors

Off axis mirrors

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