New capabilities for predicting image degradation from optical surface metrology data

Narak Choi; James E. Harvey; Andrey Krywonos

doi:10.1117/12.859758

27 August 2010 New capabilities for predicting image degradation from optical surface metrology data

Narak Choi, James E. Harvey, Andrey Krywonos

Proceedings Volume 7801, Advances in Metrology for X-Ray and EUV Optics III; 78010E (2010) https://doi.org/10.1117/12.859758
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

Image degradation due to scattered radiation form residual optical fabrication errors is a serious problem in many short wavelengths imaging system. Most currently-available image analysis codes require the bidirectional scattering distribution function (BSDF) data as an input in order to calculate the image quality from such systems. This BSDF data is difficult to measure and rarely available for the operational wavelengths of interest. Since the smooth-surface approximation is often not satisfied at these short wavelengths, the classical Rayleigh-Rice expression that indicates the BSDF is directly proportional to the surface PSD cannot be used to calculate BSDFs from surface metrology data for even slightly rough surfaces. An FFTLog numerical Hankel transform algorithm enables the practical use of the computationally intensive Generalized Harvey-Shack surface scatter theory to calculate BRDFs for increasingly short wavelengths that violate the smooth surface approximation implicit in the Rayleigh-Rice surface scatter theory. A generalized Peterson analytical scatter model is then used to make accurate image quality predictions. The generalized Peterson model is numerically validated by both ASAP and ZEMAX.

Citation Download Citation

Narak Choi, James E. Harvey, and Andrey Krywonos "New capabilities for predicting image degradation from optical surface metrology data", Proc. SPIE 7801, Advances in Metrology for X-Ray and EUV Optics III, 78010E (27 August 2010); https://doi.org/10.1117/12.859758

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