A lithography tool-matching (scanner matching) method based on covariance matrix adaptation evolution strategy is proposed to effectively reduce critical dimension errors due to inter-scanners differences by optimizing illumination sources with pixelated sources sampling. With a one-dimensional line/space mask pattern as the matching target, we have simulated matching scanners with annular, dipole, quasar and freeform sources by the proposed method. The results of these simulations show that the root-mean-square of critical dimension error was reduced by more than 90% after matching. Compared with matching methods based on other heuristic algorithms, such as self-adaptive differential evolution (JADE), particle swarm optimization (PSO) and genetic algorithms (GA), this method has effectively improved the efficiency of scanner matching, and achieved excellent matching results at the same time. Simulations have shown the effectiveness of the proposed method on scanner matching of standard-illumination sources and freeform-illumination sources. Simulations verify the stability of the proposed method.
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