Lens design: Global optimization of both performance and tolerance sensitivity

摘要

We have previously developed a global optimization method using an escape function that finds multiple local solutions in the multidimensional parameter space of a lens. We have applied this method to various actual design problems and have been able to understand some topological features of the merit function in its parameter space. These experiences have led us to develop an improved global optimization method that takes into account the robustness of the lens with respect to manufacturing and assembly errors. The method uses a technique that we call 'θ-segmentation' to perform the escape function search in a smaller parameter space. After reaching an acceptable solution with the escape function, it often seems impossible to reduce the sensitivity in tolerance without degrading the image quality already acquired. Generally speaking, performance and robustness are in a trade-off relation, i.e. reduced sensitivity can be obtained only by increasing the merit function of the system. However, in reality, it is often possible to reduce sensitivity without substantial increase of the merit function. Furthermore, in many cases, it is possible to reduce the merit function and the sensitivity simultaneously by using our new method.