Cosmic Rhythm Consistency: A Physics-Driven, Content-Agnostic Transient Rejection Framework for High-Precision Cosmology

Next-generation cosmology faces a paradox: the demand for sub-percent precision clashes with unsustainable computational costs. As BINGO approaches first light and SKA construction advances, reliance on GPU-intensive machine learning for RFI rejection threatens both carbon budgets and reproducibility. We propose a paradigm shift: a physics-driven, content-agnostic transient rejection framework based on a single fundamental quantity — the Cosmic Rhythm (τ_dwell), the natural timescale imposed by Earth's rotation. Unlike black-box classifiers, our filter uses first principles (τ_dwell = θ_FWHM / v_drift) to distinguish celestial signals from anthropogenic transients. The framework was validated via Monte Carlo simulations (10⁶ events), BINGO HEALPix mocks, HalfDome Stage-IV lightcones, and the First CHIME/FRB Catalog (CHIME/FRB Collaboration 2021), achieving 100% rejection efficiency for real astrophysical transients in the BINGO band (980–1260 MHz). Overall rejection efficiency exceeds 99% for impulsive contaminants with negligible false positives on cosmological signals. The algorithm is deterministic and scales as O(N), eliminating GPU dependency and aligning with Green Computing standards. An integrated Instrumental Event Provenance (IEP) module ensures full auditability and scientific recovery of borderline events via SHA-256 hashing. Wavelength-agnostic, the method generalises from radio drift-scans (BINGO, SKA) to optical surveys (LSST, Simons Observatory). This repository includes the preprint (PDF) and the validation notebook (Jupyter/Python).