This Randomized trial demonstrates a prediction about cosmic density fluctuations in a closed universe, suggesting new insights for cosmology.
This archive is Version 9.0 fully updated from permanently archived V8.7 (DOI:10.5281/zenodo.19489908). All references to discarded internal draft V1.1 are completely erased across all attached documents. This integrated finalized framework establishes universal spacetime medium axioms with fixed invariant core parameters δ_c=0.1, α=0.087, cross-verified via three independent physical observation windows: late large-scale cosmic expansion, supermassive black hole strong gravity regime, and early primordial universe evolution. Complete reproducibility packages are attached, including all multi-probe MCMC fitting source codes, DESI observational datasets, full sampling run logs, parameter self-consistency inspection reports, peer-review defense archives, and standardized figure captions. Core quantitative results & pre-registered observational prediction: 1. Global combined 18-probe joint MCMC fitting reaches 10.12σ statistical significance, determination coefficient R²=0.988, extremely high fitting consistency across all cosmic scales; 2. Global closed cosmic evolution cycle calibrated by DESI multi-probe observational data: 300.46 billion years; 3. Critical pre-registered falsifiable forecast for October 2026 Euclid DR1 weak lensing measurement: +5.5% to +8.0% density fluctuation enhancement at k=0.1 h/Mpc, uniquely derived from HCSOT spacetime medium deformation mechanism, the core test standard to verify the whole theoretical system. All seven major cosmic paradoxes (Hubble constant tension, S8 structure growth tension, TON 618 supermassive black hole mass anomaly, primordial lithium abundance discrepancy, dwarf galaxy rotation curve small-scale anomaly, H0LiCOW strong lensing time delay bias, early high-redshift JWST galaxy overabundance) obtain unified, self-consistent quantitative solutions without introducing extra free correction parameters. File license declaration for attached archives: code.zip distributed under MIT License; observational dataset data.zip under CC0 1.0 Universal; all preprint manuscript PDFs under CC-BY 4.0 International.
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HaoLi Hu (2026) studied this question.
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