Block-based inverse lithography technology with adaptive level-set algorithm

Abstract

Inverse lithography technology (ILT) is a key computational lithography approach aimed at inversely optimizing the photomask pattern to compensate for the image distortion in advanced optical lithography process. Traditional ILT algorithms, despite their capacity of significantly enhancing the image quality, bring challenges to the computational efficiency and mask manufacturability. To overcome those problems, this paper proposes a novel block-based ILT method driven by the level-set algorithm. This method leverages overlapped basis blocks with a level-set support area for mask representation, thus reducing the mask complexity. To circumvent the slow convergence rate dictated by the conventional Euler time step of the Courant-Friedrichs-Lewy condition, this research adopts the Barzilai-Borwein algorithm to update level set function using adaptive time step, which accelerates the optimization process. In addition, a testbed of digital lithography system is established to verify the proposed ILT method with a calibrated imaging model. It shows that the proposed method is superior over the widely-used and state-of-the-art ILT methods in terms of convergence speed and mask manufacturability.