The Complete Cosmic Blueprint Laboratory-Grade Reproducibility PDF

Author’s Technical Note — Laboratory-Grade Reproducibility Package The Complete Cosmic Blueprint: Sub-Percent Determination of the Universe’s Composition after Resolving the Hubble Tension (Paper 3) (Pre-release documentation; executable ZIP forthcoming) This document accompanies the paper, "The Complete Cosmic Blueprint: Sub-Percent Determination of the Universe’s Composition after Resolving the Hubble Tension”, which forms Part III of the Precision Cascade research series. It provides a complete, transparent description of the datasets, computational workflows, and validation framework used to derive the full cosmic energy-density composition and validate universal flatness to sub-percent precision. The reproducibility package includes: • Inverse-variance weighted geometry constraints across Planck, BAO, SN Ia, weak/strong lensing, and gravitational-wave luminosity distances. • A complete multi-probe correlation table linking early- and late-universe curvature estimates. • Minimal and full Python replication workflows for weighted-mean Ωₖ calculation and flatness-significance testing. • Step-by-step replication protocol with environment and checksum verification. • Supplementary derivations and figures illustrating the covariance propagation that underpins the cosmic-closure result. While this PDF serves as a non-executable pre-release snapshot, it faithfully documents the structure and methodology of the forthcoming executable reproducibility archive. That archive will be released on Zenodo with a unique DOI, enabling direct validation of all quantitative results presented in the associated paper. Researchers following the included protocol can reconstruct the weighted-mean curvature (Ωₖ ≈ 0.000 ± 0.0007) and confirm the ≥ 6σ flatness validation reported in the study. This release continues the series’ commitment to audit-grade transparency, rigorous reproducibility, and independent verification of discovery-level cosmological findings. — Daniel JeffreyIndependent Researcher (2025) related DOI: https://doi.org/10.5281/zenodo.17379338