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Alignment Errors vs. Measurability for Null-Measurements of Aspheres

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Abstract

We show that an imperfectly aligned asphere-CGH-measurement leads to artifacts that are indistinguishable from common manufacturing errors such as trefoil and spherical aberration. We apply a machine learning approach to correct for these artifacts.

© 2019 The Author(s)

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