LAUSR

Source and mask optimization (SMO) remains a key technique to improve the wafer image printability for technology nodes of 22 nm and beyond, enabling the continuation of the immersion lithography. In this paper, we propose a distance level-set regularized reformulation of the SMO maintaining the desired signed distance property, which secures stable curve evolution and accurate computation with a simpler and more efficient numerical implementation. Consequently, computation load caused by convolution operations and memory requirements of the electric-field caching technique (EFCT) is significantly eased by performing computation only in the narrow band; moreover, the convergence of the updating process is further improved by applying larger Euler time steps of the Courant-Friedrichs-Lewy (CFL) condition with reduced optimization dimensionality. Simulation results of the proposed narrow-band level-set based SMO prove to improve the computation efficiency, memory usage and imaging performance of the full domain methods.