这篇论文用可微波导法和WGNO做EUV掩模反演光刻，能自动恢复吸收体参数，在11.2nm下针对实际材料验证效果，做光刻仿真的可以看看。
该论文提出一种基于梯度的极紫外（EUV）掩模反演光刻（ILT）框架，将可微波导法和最近提出的波导神经算子（WGNO）作为端到端物理引擎。通过全前向衍射模型的自动微分恢复掩模吸收体的介电常数。在TaBN、La、U等实际2D和3D掩模吸收体上，于11.2nm波长下进行数值实验，验证了该方法可获得符合晶圆目标场的掩模结构。
Gradient-based inverse lithography for EUV masks via the waveguide method and a physics-informed neural operator
Gradient-based inverse lithography technology~(ILT) for extreme ultraviolet~(EUV) masks is presented. A novel framework treats the differentiable waveguide method and the recently proposed waveguide neural operator~(WGNO) as end-to-end physics engines, recovering the permittivity of the absorber of the mask through automatic differentiation of the full forward diffraction model. Numerical experiments on realistic 2D and 3D absorbers of the mask (TaBN, La, U) at $λ{=}11.2$~nm show that the considered ILT methods make it possible to obtain a mask structure that achieves the desired field on the wafer.