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Pupil-difference moments for estimating relative modulation from general mid-spatial frequency surface errors.

Luke A DeMars, Thomas J Suleski

|May 1, 2023

Summary

This summary is machine-generated.

Standard surface specifications fail to capture complex topography. This study introduces pupil-difference probability distribution (PDPD) moments to better assess mid-spatial frequency (MSF) errors and link them to optical performance.

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Area of Science:

Optical engineering
Surface metrology

Background:

Standard surface specifications for mid-spatial frequency (MSF) errors often oversimplify complex surface topography.
This simplification leads to a loss of critical information and difficulty in correlating surface specifications with actual optical performance.

Purpose of the Study:

To introduce and evaluate the use of pupil-difference probability distribution (PDPD) moments for assessing general MSF surface errors.
To establish a relationship between PDPD moments and relative modulation for improved optical performance prediction.

Main Methods:

Utilizing pupil-difference probability distribution (PDPD) moments as a novel metric for surface error assessment.
Analyzing the correlation between PDPD moments and relative modulation in optical systems.

Main Results:

Demonstrated that PDPD moments can effectively characterize complex MSF surface errors.
Established a quantifiable relationship between PDPD moments and relative modulation, offering a more accurate link to optical performance.

Conclusions:

PDPD moments provide a more comprehensive approach to specifying and evaluating MSF surface errors compared to standard methods.
This new method enhances the ability to predict and control optical performance by better understanding surface topography.