Khonina S N, Kazanskiy N L, Efimov A R, Nikonorov A V, Oseledets I V, Skidanov R V, Butt M A
Samara National Research University, 443086 Samara, Russia.
Sber, Moscow, Russia.
iScience. 2024 Jun 18;27(7):110270. doi: 10.1016/j.isci.2024.110270. eCollection 2024 Jul 19.
Artificial intelligence (AI) is transforming diffractive optics development through its advanced capabilities in design optimization, pattern generation, fabrication enhancement, performance forecasting, and customization. Utilizing AI algorithms like machine learning, generative models, and transformers, researchers can analyze extensive datasets to refine the design of diffractive optical elements (DOEs) tailored to specific applications and performance requirements. AI-driven pattern generation methods enable the creation of intricate and efficient optical structures that manipulate light with exceptional precision. Furthermore, AI optimizes manufacturing processes by fine-tuning fabrication parameters, resulting in higher quality and productivity. AI models also simulate diffractive optics behavior, accelerating design iterations and facilitating rapid prototyping. This integration of AI into diffractive optics holds tremendous potential to revolutionize optical technology applications across diverse sectors, spanning from imaging and sensing to telecommunications and beyond.
人工智能（AI）正通过其在设计优化、图案生成、制造改进、性能预测和定制方面的先进能力，改变衍射光学的发展。利用机器学习、生成模型和变压器等人工智能算法，研究人员可以分析大量数据集，以优化针对特定应用和性能要求定制的衍射光学元件（DOE）的设计。人工智能驱动的图案生成方法能够创建复杂而高效的光学结构，以极高的精度操纵光线。此外，人工智能通过微调制造参数来优化制造工艺，从而提高质量和生产率。人工智能模型还能模拟衍射光学行为，加速设计迭代并促进快速原型制作。将人工智能集成到衍射光学中，在从成像和传感到电信等各个领域的光学技术应用中，具有彻底变革的巨大潜力。
