7 March 2008 Fitness and runtime correlation of compact model complexity
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Abstract
The development of efficient resist models for optical and process proximity correction (OPC) is a problem of particular importance in microlithography. A resist model is considered efficient if it is fast and accurate and properly accounts for the transfer of latent image patterns into resist shapes. Here we study the runtime-accuracy tradeoff of the Compact Model 1 (CM1) resist model. The model is represented as a linear combination of the aerial image, orthogonal basis functions, and other terms designed to mimic various effects such as acid and base diffusion, slope, maximum and minimum local intensity, etc. Clearly, the greater the number of terms involved the more flexible and accurate the model becomes. On the other hand, adding too many terms to the model substantially increases the OPC runtime and may lead to overfitting. Our goal is to find model forms that are optimal with respect to both runtime and accuracy. This is achieved using a consecutive descent method for multi-objective optimization that seeks so-called Pareto optimal solutions. We found that model forms which include the diffused acid term and orthogonal basis functions almost always represent a reasonable compromise between fitness and performance.
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Alexander N. Drozdov, Monica L. Kempsell, Yuri Granik, "Fitness and runtime correlation of compact model complexity", Proc. SPIE 6924, Optical Microlithography XXI, 692445 (7 March 2008); doi: 10.1117/12.777403; https://doi.org/10.1117/12.777403
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