We propose a general method called convolution-variation separation (CVS) to enable efficient optical imaging calculations without sacrificing accuracy when simulating images for a wide range of process variations. The CVS method is derived from first principles using a series expansion, which consists of a set of predetermined basis functions weighted by a set of predetermined expansion coefficients. The basis functions are independent of the process variations and thus may be computed and stored in advance, while the expansion coefficients depend only on the process variations. Optical image simulations for defocus and aberration variations with applications in robust inverse lithography technology and lens aberration metrology have demonstrated the main concept of the CVS method.
Aerial image simulation is one of the most critical components in the model-based optical proximity correction (OPC), which has become a necessary part of resolution enhancement techniques used to improve the performance of subwavelength optical lithography. In this paper, a fast aerial image simulation method is proposed for partially coherent systems by decomposing the transmission cross coefficient (TCC) into analytical kernels. The TCC matrix is projected onto a function space whose basis is analytical circle-sampling functions (CSFs) and converted into a much smaller projected matrix. By performing singular value decomposition (SVD) to the projected matrix, its eigenvectors together with the CSFs are used to generate a set of analytical TCC kernels. The proposed method avoids directly performing SVD to the large TCC matrix, making it much more runtime efficient than the conventional SVD method. Furthermore, the grid size of the kernels can be flexibly set to any desired value in aerial image simulations, which is not realizable with the conventional SVD method. The comparison of aerial image intensity errors and edge placement errors calculated by the proposed method and the conventional SVD method has confirmed the validity of the proposed method. An OPC example is also provided to further demonstrate its efficiency.
This paper proposes a parametric analytical source model for overall representation of the physical distribution property of partially coherent illumination sources in lithographic tools. A set of smooth kernels is adopted to construct the analytical model for the multiple mainstream illumination sources. Corrected parametrical terms are subsequently presented for characterization of different physical distortions of and deviations from actual illumination sources. The corrected parametrical terms can be decomposed into Fourier series, which have special physical meanings of respectively indicating different distortion types, including shift of the center, tilt, and ellipticity, etc. We fully expected that the proposed analytical model will provide both simulation conditions and a theoretical basis for the resolution enhancement technique and related research fields.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.