Document-Grounded Generation of Verified, Interactive and Photoreal Physics Experiments

Most scientific documents convey physical processes through static figures, which leave the dynamics for readers to figure out. Generative models can turn such documents into interactive simulations and videos. These outputs often look plausible, yet it is hard to ensure they obey the physical laws the document states. Our goal is to turn a document's figures into interactive simulations and videos that help readers understand the physics. These simulations must follow the physical laws stated in the document. We represent the document as a graph over its equations, quantities, and validity regimes. Retrieval on this graph continues until the collected equations form a closed, solvable system. This system is recorded as a physics scenario card. The card states what to solve, the governing dynamics, the quantities a reader controls, and their valid ranges. The same card drives generation and supplies tests derived from the document. Generated behavior is therefore checked against the document's own relations. Closure-terminated retrieval recovers substantially more of the required context than similarity search. An evaluator answers figure-specific questions from our interactive artifacts at 0.923, against 0.389 for single-call generation. In photorealistic videos, motion measured from the frames matches the closed form derived from the document. Without physical conditioning, the same video model produces no measurable period. This work enables a scientific document to demonstrate the physical behavior it describes. It opens a path from the static figures of education, science communication, and engineering to interactive, verifiable representations.