Locating the local minima in lens design with machine learning

Anna V. Kononova; Ofer M. Shir; Teus Tukker; Pierluigi Frisco; Shutong Zeng; Thomas Bäck

doi:10.1117/12.2593199

1 August 2021 Locating the local minima in lens design with machine learning

Anna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, Thomas Bäck

Proceedings Volume 11814, Current Developments in Lens Design and Optical Engineering XXII; 1181402 (2021) https://doi.org/10.1117/12.2593199
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

Abstract

We applied an extended version of the Niching-CMA-ES heuristic to search for local minima of the Cooke triplet, a renowned photographic lens design, of which 21 local minima were already known. The considered problem is defined by 6 input (decision) variables, namely the curvatures of the three lenses present in the Cooke triplet, and is driven by a single objective function, that is the RMS spot size. The applied approach found: (i) 19 out of the 21 known minima in a single run; (ii) 540 new local minima with objective values lower/equal to those of the known 21 minima; (iii) a large number of infeasible designs.

Conference Presentation

Citation Download Citation

Anna V. Kononova, Ofer M. Shir, Teus Tukker, Pierluigi Frisco, Shutong Zeng, and Thomas Bäck "Locating the local minima in lens design with machine learning", Proc. SPIE 11814, Current Developments in Lens Design and Optical Engineering XXII, 1181402 (1 August 2021); https://doi.org/10.1117/12.2593199

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