Algorithm-Driven Paradigms for Freeform Optical Engineering
Algorithm-Driven Paradigms for Freeform Optical Engineering
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DOI：
10.1021/acsphotonics.2c00612
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发表时间：
2022-08-09
期刊：
影响因子：
7
通讯作者：
Jiang, Jiaqi
中科院分区：
文献类型：
--
作者：
Fan, Jonathan A.;Chen, Mingkun;Jiang, Jiaqi
现代制造业的进步使电介质的多标量图案化具有几乎任意的布局，为光子技术的设计和制造流程带来了革命性的独特机会。在这个视角中，我们讨论了基于经典优化和深度学习的算法如何为自由光学工程建立一个新的概念框架。这些工具可以为所需目标指定合适的设计参数，自动化自由成型器件的高速优化，并增强制造工艺，以减轻自由成型制造带来的挑战。这些算法中的许多算法的中心特征是它们利用数据和物理来建模和利用在麦克斯韦方程的约束内的几何结构和电磁响应之间的高维关系。我们预计，这些算法驱动的方法将简化光学系统的设计在结构化介质的物理限制，并成为科学家和工程师的标准学术和工业工具。
Advances in modern manufacturing have enabled the multiscalar patterning of dielectric media with nearly arbitrary layouts, presenting unique opportunities to revolutionize the design and fabrication pipeline for photonic technologies. In this Perspective, we discuss how algorithms based on classical optimization and deep learning are establishing a new conceptual framework for freeform optical engineering. These tools can specify suitable design parameters for a desired objective, automate the high-speed optimization of freeform devices, and augment manufacturing processes to mitigate challenges set by freeform fabrication. A central feature of many of these algorithms is their utilization of data and physics to model and exploit high-dimensional relationships between geometric structure and electromagnetic response within the constraints of Maxwell's equations. We anticipate that these algorithm-driven methods will streamline optical systems design at the physical limits of structured media and become standard academic and industry tools for scientists and engineers.