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SHRAV: State-Hypothesis-Reason-Action-Verify Framework for Physical Modeling and Inverse Design

arXiv 人工智能论文 · 发布
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arXiv:2609.27621v2 Announce Type: new Abstract: 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.

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arXiv 人工智能论文 · 社区 / 第三方
来源发布
2026/09/24 12:00
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2026/09/25 11:59

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