Inverse lithography with adaptive threshold regularization

We introduce an inverse lithography framework where typical grayscale mask tone is penalized toward transparent and opaque transmissions compatible with existing mask writing. Threshold regularization featuring dynamic fine-tuned optimal thresholds for main feature and Sub-Resolution Assist Features (SRAFs) is incorporated into the optimization of lithographic image formation. The optimization flow preludes with the synthesis of a Continuous Transmission Mask (CTM) for the best pattern fidelity; then respective thresholds are applied to main feature and orders of SARF by including the regularization term into the mask synthesis flow where a warp function is devised for binarizing mask transmission with optimal thresholds. Simulations results demonstrate that the proposed approach effectively facilitates the pursuit of comparable lithographic imaging performance while maintaining design flexibility which is essential for both mask design and fabrication.