| Issue |
J. Eur. Opt. Society-Rapid Publ.
Volume 22, Number 1, 2026
|
|
|---|---|---|
| Article Number | 42 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/jeos/2026024 | |
| Published online | 25 May 2026 | |
Research Article
Automatic search for cemented doublets using the saddle point construction method
1
ICube, Université de Strasbourg, CNRS, INSA, F-67000 Strasbourg, France
2
Optiive, 300 Boulevard Sebastien Brant, 67400 Illkirch-Graffenstaden, France
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
4
December
2025
Accepted:
8
March
2026
Abstract
Conventional optical design relies on iterative and time-consuming optimization methods. Finding the right starting system facilitates the design of relevant optical systems. It has been demonstrated that Saddle Point Construction Method (SPCM) can be used to design innovative optical systems based on pre-existing systems, or from scratch. This paper presents the results of a Python program using Code V’s Application Programming Interface (API) and applying the special version of SPCM to automatically design optical systems using a reduced glass map. To illustrate its robustness, cemented doublets have been automatically designed. A reduced glass map with thirty-four Schott glasses was combined with the SPCM for the design of 68 achromatic cemented doublets. They were then compared with achromatic cemented doublets from well-known manufacturers and with those described in the literature using a semi-analytical approach. The achromatic cemented doublets were first designed with a total field of view (FOV) of 0° and were subsequently designed with a FOV of 5°. The best achromatic cemented doublets obtained performed better or as well as existing achromatic cemented doublets.
Key words: Optical Design / Optimization method / Saddle Point Construction Method / CODE V / Python / Reduced Glass Map
© The Author(s), published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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