AI 中文总结
本研究提出基于自动微分的二元干涉光刻掩模优化框架，采用可微角谱法，通过移位ASM等技术降低内存占用，实现了含0.1%像素缺陷的非周期性图案掩模设计，为复杂IL掩模设计提供了新方法。
AI 中文摘要
干涉光刻（IL）是制备高分辨率周期性纳米结构的有力工具，但设计掩模以生成非周期性图案仍具挑战性。我们引入一种基于梯度的优化框架，用于采用自动微分的二元IL掩模设计。正向模型通过可微角谱法（ASM）实现。逆掩模设计被表述为优化问题，其中掩模logits通过模拟场振幅与目标图案之间损失的反向传播进行更新。我们优化出的掩模可复现目标图案，仅存在0.1%的孤立像素级缺陷，能分辨出为掩模像素间距一半的特征。为扩展掩模优化规模，我们采用移位ASM，将掩模划分为多个子区域，各子区域独立传播后在像平面求和。对于3.84 mm×3.84 mm的掩模，含16个子区域的移位ASM相比标准ASM，峰值GPU内存减少3.8倍，仅增加1.3倍的运行时间成本。结合梯度检查点，峰值内存减少7.4倍，运行时间为标准ASM的2倍。多GPU分布式计算进一步加速优化。本研究建立了一种物理信息驱动、机器学习辅助的IL掩模设计方法，向实现复杂非周期性图案迈出重要一步。源代码可在指定URL获取。
英文摘要
Interference lithography (IL) is powerful for fabricating high-resolution periodic nanostructures, but designing masks to produce non-periodic patterns remains challenging. We introduce a gradient-based optimization framework for binary IL mask design using automatic differentiation. The forward model is implemented using the differentiable angular spectrum method (ASM). The inverse mask design is formulated as an optimization problem, where the mask logits are updated through backpropagation of the loss between the simulated field amplitude and the target pattern. We optimize a mask that reproduces a target pattern with only 0.1% isolated pixel-level defects, resolving features at half the mask pixel pitch. To scale mask optimization, we employ the shifted ASM, which partitions the mask into patches that are propagated independently and summed at the image plane. For a 3.84 mm$\times$3.84 mm mask, shifted ASM with 16 patches reduces peak GPU memory by 3.8$\times$ at only 1.3$\times$ runtime cost relative to standard ASM. With gradient checkpointing, peak memory is reduced by 7.4$\times$ at 2$\times$ runtime. Distributing across multiple GPUs further accelerates the optimization. This work establishes a physics-informed, machine learning-driven approach for IL mask design, moving a step further towards complex, non-periodic patterns. The source code is available at https://github.com/chuntian236/holography-optimization.git .
Comments11 pages, 4 figures. To be published in Proceedings of SPIE Optics + Photonics 2026, Optical Engineering + Applications
