Optimization of the Seidel image errors by bending of lenses using a 4th-degree merit function

Friedrich A. Aurin

doi:10.1117/12.47948

1 January 1991 Optimization of the Seidel image errors by bending of lenses using a 4th-degree merit function

Friedrich A. Aurin

Proceedings Volume 1354, 1990 Intl Lens Design Conf; (1991) https://doi.org/10.1117/12.47948
Event: 1990 International Lens Design Conference, 1990, Monterey, CA, United States

Abstract

The proposed procedure works on the basis of a merit function of the 4th degree and is used for the optimization of the Seidel image errors of a system composed of thin lenses by means of lens bendings. Between the thin lenses air spaces may exist. All solutions which lie within the permissible intervals of bending are taken into consideration when the sums and the corresponding surface contributions of the Seidel image errors are situated below a limit that may be selected at will. The search for a relative minimum is successful too if a relative maximum lies on the path to the relative minimum. The procedure is especially suitable when in a given system thin lenses are preferred for reasons of weight material price transmission or broadband colour correction. 1. Procedure Lens bending means equal curvature change at each surface of a lens. The advantage of bending lenses of thickness zero is that the angles and heights of all paraxial rays the focal length the axial color the lateral color and the Petzvalsum of the lens system remain constant. The sums of the Seidel image errors are constant linear or square functions of the lens bendings. The merit function is the sum of the squared Seidel sums. In the general case of in independent lens bendings the merit function is a function of 4th degree of in independent variables. These

Citation Download Citation

Friedrich A. Aurin "Optimization of the Seidel image errors by bending of lenses using a 4th-degree merit function", Proc. SPIE 1354, 1990 Intl Lens Design Conf, (1 January 1991); https://doi.org/10.1117/12.47948

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