Etch-ViGen: A Video Generation Model for Etching Simulation

With the scaling down of integrated circuit dimensions and the increasing complexity of transistor structures, the role of etching in manufacturing has become increasingly critical. We propose an etching simulation approach based on a video generation model, which models the evolution of the etching process as a video generation task. By embedding frames into quantized latent codeword representations using VQ-VAE (Vector Quantized Variational Autoencoder), injecting physical conditions with a CLIP projection layer, and leveraging a temporal autoregressive prediction model, we propose a generative model of the etching process. We validate the effectiveness of our model on both simulated and experimental data. Our approach achieves a 6000× speedup over the Monte Carlo method while reducing the simulation MAE (Mean Absolute Error) by 14.4% compared with the state-of-the-art video model. Furthermore, results generated by our video-based model show strong agreement with experimental data.