Contrast Optimization technique allows for robust and efficient optimization on the system MTF at a given spatial frequency. The method minimizes the wavefront differences between pairs of rays separated by a pupil shift corresponding to the targeted spatial frequency, which maximizes the MTF. Further computational efficiency is achieved by using Gaussian Quadrature to determine the pattern of rays sampled.
Contrast Optimization is much faster than a direct optimization on the MTF value
To use the Contrast Optimization default merit function
The Contrast Loss Map shows exactly which areas in the pupil are causing the most loss of MTF
Optimization of a Double Gauss design shows that Contrast Optimization can be comparable in speed to wavefront optimization
Optimizing a singlet on its shape factor confirms that the Contrast Optimization merit function has the same minimum as an MTF
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