Precision Cascade Reproducibility Archive for "Covariance Completeness in the Distance Ladder"
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下载链接:
https://zenodo.org/doi/10.5281/zenodo.20016484
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资源简介:
This archive provides a complete, deterministic, and self-auditing reproducibility framework for the manuscript:
“Resolving the Hubble Tension Through Systematic Correlation Analysis (Revised Version)”.
The archive implements the Precision Cascade Engine, a provenance-encoded, covariance-driven inference system designed to reproduce and audit the full statistical pathway from declared inputs to final cosmological estimates.
All numerical results are generated internally from:
declared measurements
structural provenance mappings
covariance construction rules
systematic bias models
The archive reproduces the primary result:H₀ = 69.9 ± 0.8 km s⁻¹ Mpc⁻¹,reducing the Hubble tension from ~5.9σ to 2.4–2.8σ through explicit inclusion of cross-rung covariance.
Key features:
Fully deterministic execution (no stochastic elements)
Single self-contained archive (no external dependencies beyond environment setup)
Explicit construction of correlation and covariance matrices from provenance structure
Inverse-covariance estimator implementation
Executable worked examples (2×2 and 3×3 covariance systems)
Sensitivity analyses for correlation strength and systematic variation
Internal validation against golden outputs
Checksum closure with ROOT_HASH for chain-of-custody integrity
Self-auditing framework with PASS/FAIL governance
Explicit handling and disclosure of residual differences between illustrative and exact computational layers
The archive is designed to:
enable full independent replication
support adversarial testing of assumptions
provide a transparent audit trail for all reported results
This work represents a reproducibility-first implementation of cosmological inference, prioritising process integrity over narrative presentation.
Keywords
Hubble tension, H0, cosmology, covariance modelling, reproducibility, statistical inference, systematics, Bayesian inference, scientific computing, auditability, precision cascade
提供机构:
Zenodo
创建时间:
2026-05-03



