Abstract
Spatial fluctuation in reactions throughout exposed resist films is analyzed by principal component analysis (PCA) or singular value decomposition (SVD), which is known as generalization of Fourie transform. In optical simulations, image is expressed by a wave function obtained from SVD of matrix representation of optical images. We attempt to extend this to density/probability distributions of resist reactions for analyzing probabilistic behavior of resists such as LER/LCDU and stochastic defects. To show its effectiveness, PCA is applied to reaction distributions calculated by the fully coupled Monte-Carlo simulation, which visualizes correlated reaction influences on spatial feature and probability of pattern anomalies.
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