Adversarial Cosmological Auditing: A Framework for Stress-Testing Large-Scale Covariance Claims

This work presents an adversarial auditing framework for stress-testing speculative large-scale covariance claims in cosmological datasets. The framework combines robust-tail diagnostics, preprocessing-invariant harmonic metrics, cross-channel symmetry tests, ring-half temporal stability audits, foreground-template orthogonalization, and polarization-domain consistency checks. The methodology was applied to Planck PR4/NPIPE temperature and polarization maps. While no candidate structure survived the complete adversarial veto chain, the resulting infrastructure provides a reusable methodology for future surveys including Simons Observatory, CMB-S4, and LiteBIRD. The principal contribution of this work is methodological rather than cosmological: a calibrated framework for enforcing interpretation discipline in large-scale anomaly analysis.