Abstract
We present a process to locate the desired local optimum of high-dimensional design problems such as the optimization of freeform mirror systems. By encoding active design variables into a binary vector imitating DNA sequences, we are able to perform a genetic optimization of the optimization process itself. The end result is an optimization route that is effectively able to sidestep local minima by warping the variable space around them in a way that mimics the expertise of veteran designers. The generality of the approach is validated through the automated generation of high-performance designs for off-axis three- and four-mirror free-form systems.
© 2020 Optical Society of America
Full Article | PDF ArticleMore Like This
Xiaoxia Luo, Hua Liu, Zhenwu Lu, and Yao Wang
Appl. Opt. 50(20) 3412-3418 (2011)
Ziyao Tang, Matthias Sonntag, and Herbert Gross
Appl. Opt. 58(23) 6357-6364 (2019)
Chang Liu and Herbert Gross
Appl. Opt. 57(20) 5758-5768 (2018)