The Rail for Computational Imaging: A Physics World Model for Industrializing Image Reconstruction

The computational imaging community has built increasingly powerful reconstruction algorithms, yet real-world deployments routinely fail. We show that a 5-parameter sub-pixel operator mismatch -- well within manufacturing tolerances -- degrades the state-of-the-art CASSI transformer (MST-L) by 13.98 dB, erasing years of algorithmic progress. This paper argues that the bottleneck is not the solver but the infrastructure around it: evaluation protocols, physics representations, calibration pipelines, and benchmarks. Drawing on the SolveEverything.org framework, we present the Physics World Model (PWM) as the "rail" for computational imaging -- a standardized evaluation harness comprising: (i) OperatorGraph intermediate representation (IR), a universal DAG representation spanning 64 modalities across 5 physical carriers with 89 validated templates; (ii) a 4-scenario evaluation protocol separating solver quality from operator fidelity; (iii) the Leaderboard for Imaging Physics (LIP-Arena), a prospective Commit-Measure-Score competition eliminating benchmark overfitting; and (iv) a Red Team adversarial verification module. Across a 26-modality benchmark, we demonstrate that operator correction improves reconstruction by +0.54 to +48.25 dB across 9 correction configurations spanning 7 distinct modalities, with mismatch (Gate 3) identified as the binding constraint in every modality tested. PWM provides the infrastructure to move computational imaging from artisanal practice to industrial standardization.