自动优化镜片数量与类型，提升成像清晰度与速度
Automated design of compound lenses with discrete-continuous optimization
- 联合优化连续参数与离散结构，支持镜片数量和类型变化
- 在多种任务中生成更优设计，突破速度与清晰度平衡极限
- 适合光学设计自动化、智能制造领域研究人员
我们提出一种方法，可自动联合优化复合透镜的连续参数（如曲率）和离散参数（如透镜数量和类型），以提升成像清晰度或速度。以往方法仅能通过梯度优化调整给定拓扑下的连续参数，需大量专家干预才能更改结构。本方法结合梯度优化与定制化的马尔可夫链蒙特卡洛采样算法，利用跨维突变和近轴投影操作实现高效全局搜索。实验表明，该方法在多种透镜设计任务中有效拓展了设计空间，生成的方案优于现有方法，并显著提升了自动化设计在速度-清晰度权衡上的性能边界。
原文摘要 · Abstract (English)
We introduce a method that automatically and jointly updates both continuous and discrete parameters of a compound lens design, to improve its performance in terms of sharpness, speed, or both. Previous methods for compound lens design use gradient-based optimization to update continuous parameters (e.g., curvature of individual lens elements) of a given lens topology, requiring extensive expert intervention to realize topology changes. By contrast, our method can additionally optimize discrete parameters such as number and type (e.g., singlet or doublet) of lens elements. Our method achieves this capability by combining gradient-based optimization with a tailored Markov chain Monte Carlo sampling algorithm, using transdimensional mutation and paraxial projection operations for efficient global exploration. We show experimentally on a variety of lens design tasks that our method effectively explores an expanded design space of compound lenses, producing better designs than previous methods and pushing the envelope of speed-sharpness tradeoffs achievable by automated lens design.
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