Will Accurate Fields Mislead Photonic Design? FromGlobal Accuracy to Port Readout

Title:Will Accurate Fields Mislead Photonic Design? FromGlobal Accuracy to Port Readout

Abstract:Neural field surrogates can accelerate photonic design loops, but a surrogate that looks accurate in global field error can still mis-rank candidate devices when the final decision depends on localized output-port readouts. This risk is acute in propagation-dominated MMI splitters and couplers, where port power, splitting, phase, and coupling are determined by accumulated modal interference and output-window aggregation rather than by average field similarity alone. We study this field-to-design mismatch through a Field/Mediator/Readout view that separates dense complex-field error from propagation-profile and output-window errors before port aggregation. To align the surrogate with this chain, we propose PaNO, a propagation-aligned neural operator that keeps the full-field prediction interface while organizing latent states around local boundary structure, transverse modal content, axial propagation, and cross-mode interaction. We also evaluate PaNO-R2, an output-aware feedback variant for residual field components near the port region. On a 15-wavelength tunable $3{\times}3$ MMI benchmark with 4608 held-out fields, PaNO lowers NeurOLight's port-power error from 0.2018 to 0.0739 despite slightly higher cMAE, showing that global field accuracy alone is not sufficient for design-relevant readout fidelity. PaNO-R2 attains the best cMAE, propagation-profile error, output-profile error, and port-power error, reducing NeurOLight's port-power and output-profile errors by 72.7\% and 72.5\%.

Machine Learning (cs.LG); Computational Physics (physics.comp-ph); Optics (physics.optics)

arXiv:2606.03038 [cs.LG]

(or arXiv:2606.03038v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2606.03038 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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