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Parametric Uncertainty in Optical Image Modeling



James E. Potzick, Egon Marx, M P. Davidson


Optical photomask feature metrology and wafer exposure process simulation both rely on optical image modeling for accurate results. While it is fair to question the accuracies of the available models, model results also depend on several input parameters describing the object and imaging system. Errors in these parameter values can lead to significant errors in the modeled image. These parameters include wavelength, illumination and objective NA?s, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k, etc. for the object. In this paper each input parameter is varied over a range about its nominal value and the corresponding images simulated. Second order parameter interactions are not explored. Using the scenario of the optical measurement of photomask features, these parametric sensitivities are quantified by calculating the apparent change of the measured linewidth for a small change in the relevant parameter. Then, using reasonable values for the estimated uncertainties of these parameters, the parametric linewidth uncertainties can be calculated and combined to give a lower limit to the linewidth measurement uncertainty for those parameter uncertainties.
Proceedings Title
Proceedings of SPIE
Conference Dates
September 18, 2006
Conference Location
Monterey, CA
Conference Title
Photomask Technology (BACUS) 2006


feature size., measurement uncertainty, Optical image modeling, photomask


Potzick, J. , Marx, E. and Davidson, M. (2006), Parametric Uncertainty in Optical Image Modeling, Proceedings of SPIE, Monterey, CA (Accessed May 24, 2024)


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Created September 18, 2006, Updated February 19, 2017