Evolutionary algorithms converge towards evolved biological photonic structures

TL;DR

This paper demonstrates that evolutionary algorithms can successfully replicate complex natural photonic structures, providing insights into their emergence and potential applications in designing optical devices.

Contribution

It introduces a method using evolutionary algorithms to reproduce natural photonic structures and explores how recombination improves algorithm performance.

Findings

Recombination enhances the evolution of photonic structures.

Evolutionary algorithms can replicate natural photonic architectures.

In silico evolution suggests new optical device designs.

Abstract

Nature features a plethora of extraordinary photonic architectures that have been optimized through natural evolution. While numerical optimization is increasingly and successfully used in photonics, it has yet to replicate any of these complex naturally occurring structures. Using evolutionary algorithms directly inspired by natural evolution, we have retrieved emblematic natural photonic structures, indicating how such regular structures might have spontaneously emerged in nature and to which precise optical or fabrication constraints they respond. Comparisons between algorithms show that recombination between individuals inspired by sexual reproduction confers a clear advantage in this context of modular problems and suggest further ways to improve the algorithms. Such an in silico evolution can also suggest original and elegant solutions to practical problems, as illustrated by the design of counter-intuitive anti-reflective coating for solar cells.