PCAR-Flow: Physics-Calibrated Allocation of Residuals for Metalens Imaging

Metalens measurements exhibit highly nonuniform recoverability across field position, wavelength, spatial frequency, and signal level. Generative priors can recover detail in weakly constrained regions, but may also introduce content that is not uniquely supported by the measurement. We propose Physics-Calibrated Adaptive Residual Flow (PCAR-Flow), which allocates generative freedom according to effective local observability, a calibrated measure combining optical transfer, sensor noise, and local image statistics. PCAR-Flow recovers measurement-supported content through a deterministic path and applies conditional flow matching only to unresolved high-frequency residuals. Under the local Gaussian model, the complement of observability equals normalized posterior band uncertainty and, for channel-separable transfer, approaches the classical null-space limit as measurement noise vanishes. Experiments show that PCAR-Flow improves reconstruction quality while keeping forward inconsistency close to the deterministic solution.