SHRAV：面向物理建模与逆向设计的状态-假设-推理-行动-验证框架
SHRAV: State-Hypothesis-Reason-Action-Verify Framework for Physical Modeling and Inverse Design
- ZhangJiang Laboratory（张江实验室）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出SHRAV框架，通过状态延续核心支持物理建模与逆向设计，在计算光刻中实现交并比从0.5313提升至0.8153。
AI中文摘要：
物理建模与逆向设计需要能够从可复用状态继续进行的计算。我们提出了SHRAV，一个与架构无关的计算框架，围绕状态、假设、推理、行动和验证组织。其核心机制是一个具有声明复用边界的状态延续核心，并为学习演化和数值量分配明确角色。前向配置演化预测状态并读出物理响应；逆向设计配置额外生成目标导向的修改并消费评估器反馈。电磁世界模型研究被映射到前向配置，本文报告了选定的读出和复用诊断。计算光刻展示了一种逆向设计配置：在独立标量光瞳重放下，四次固定权重设计更新将阈值化航空图像交并比从0.5313提升至0.8153，预测器估计与独立重放之间的最大绝对预测-重放差异约为0.000824。
英文摘要：
Physical modeling and inverse design require computation that can continue from reusable state. We introduce SHRAV, an architecture-independent computational framework organized around State, Hypothesis, Reason, Action, and Verify. Its central mechanism is a state-continuation core with declared reuse boundaries and explicit roles for learned evolution and numerical quantities. Forward configurations evolve predictive state and read out physical responses; inverse-design configurations additionally generate target-directed modifications and consume evaluator feedback. Electromagnetic world-model studies are mapped to forward configurations, with selected readout and reuse diagnostics reported here. Computational lithography demonstrates an inverse-design configuration: four fixed-weight design updates improve thresholded aerial-image intersection-over-union from 0.5313 to 0.8153 under independent scalar-pupil replay, with a maximum absolute IoU difference of approximately 0.000824 between predictor estimates and independent replay.
