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Optimization capability is perhaps the most important feature of modern optical design software. Given a starting system, the software changes automatically the system parameters in order to make the system as good as possible, in a sense that will be made more precise below. The purpose of optical system design is to produce for an optical system a prescription (i.e., a list of all system parameters) that satisfies a set of specifications (e.g., the acceptable tolerances for image defects) required by the envisaged application. The framework for modern optical design is a mathematical model, based mostly on laws of geometrical optics, that predicts various attributes of imaging quality as functions of the system parameters (surface curvatures, distances between lens surfaces, etc.). While evaluating the image quality of a system with known values of the system parameters is a rather straightforward task, the essence of optical design is to solve the inverse problem: Given the required image quality, i.e., zero image defects within the specified tolerances, the designer must find a set of system parameters that leads to the required quality. Considering the fact that optical systems can have dozens of parameters and that the relationship between the system parameters and the image defects is highly nonlinear, solving this inverse problem may involve a daunting complexity. As a result of progress in the field of computer optimization, the design of optical systems is presently done in an increasingly automatic way. For automatic optimization, the designer must specify the following four requisites |
