Evolving expertise for automated lens Optimization

Caleb Gannon; Rongguang Liang

doi:10.1364/AO.391888

Evolving expertise for automated lens Optimization

Caleb Gannon, Rongguang Liang

Optical Sciences, College of

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

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 performa 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- A nd four-mirror free-form systems.

Original language	English (US)
Pages (from-to)	G129-G136
Journal	Applied optics
Volume	59
Issue number	22
DOIs	https://doi.org/10.1364/AO.391888
State	Published - 2020

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Engineering (miscellaneous)
Electrical and Electronic Engineering

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Evolving expertise for automated lens Optimization

Abstract

ASJC Scopus subject areas

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