SEA–G: A Coherence Diagnostic for Galactic Architecture in Large Surveys

This paper introduces SEA–G (Synthesis & Estimation Architecture – Galactic), a survey-scale diagnostic framework for evaluating internal architectural consistency in galaxy populations using large observational datasets. The method applies coverage-weighted coherence metrics to characterize structural alignment across galaxy properties without imposing dynamical evolution models, causal narratives, or stability assumptions. SEA–G is demonstrated using over 500,000 galaxies from DESI, with independent validation against MaNGA integral-field spectroscopy. The framework identifies statistically significant coherence regimes, enrichments in known transitional populations, and robust separation between architecturally aligned and disrupted systems. Extensive falsification tests, permutation controls, and robustness analyses confirm that the coherence signal is not attributable to trivial correlations, normalization artifacts, or sample bias. The framework is explicitly diagnostic rather than causal. It is designed to complement, not replace, forward modeling, simulation-based galaxy evolution studies, and mechanistic interpretations. SEA–G generalizes coherence-based diagnostics to modern survey scales and provides a principled way to assess architectural consistency, anomaly structure, and observability limits in large astronomical ensembles.