Inverse Lithography

Inverse lithography technology (ILT) aims to optimize photomask designs for semiconductor manufacturing, compensating for imperfections in the lithographic process to achieve highly accurate chip patterns. Current research focuses on improving ILT's efficiency and accuracy through hybrid approaches combining traditional numerical optimization with machine learning, particularly deep neural networks and level-set methods, often incorporating physics-based constraints to enhance performance and reduce computational cost. These advancements are crucial for enabling the continued miniaturization of integrated circuits, addressing the growing challenges of producing ever-smaller and more complex chip features at scale.