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In this work, we present a methodology for predicting the optical performance impacts of random and structured MSF surface errors using pupil-difference probability distribution (PDPD) moments. In addition, we show that, for random mid-spatial frequency (MSF) surface errors, performance estimates from the PDPD moments converge to performance estimates that assume random statistics. Finally, we apply these methods to several MSF surface errors with different distributions and compare estimated optical performance values to predictions based on earlier methods assuming random error distributions.
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Pupil-difference moments for estimating relative modulation from general mid-spatial frequency surface errors
Standard surface specifications for mid-spatial frequency (MSF) errors do not capture complex surface topography and often lose critical information by making simplifying assumptions about surface distribution and statistics. As a result, it is challenging to link surface specifications with optical performance. In this work, we present use of the pupil-difference probability distribution (PDPD) moments to assess general MSF surface errors and show how the PDPD moments relate to the relative modulation.
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- PAR ID:
- 10410499
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optics Letters
- Volume:
- 48
- Issue:
- 9
- ISSN:
- 0146-9592; OPLEDP
- Format(s):
- Medium: X Size: Article No. 2492
- Size(s):
- Article No. 2492
- Sponsoring Org:
- National Science Foundation
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