Published April 12, 2026 | Version v41

TT-DAV Pantheon+SH0ES Interactive Enviroment: A Bayesian Framework for Comparing Geometric and Standard Cosmological Models Across 1,701 SNe Ia

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Latest: https://doi.org/10.5281/zenodo.20419109

 

 

Abstract:
We present an open-access, a bayesian framwork, self-contained web application for the interactive exploration of the Pantheon+SH0ES Type Ia supernova dataset (N=1,701 observations, 1,543 unique SNe Ia, 0.001 ≤ z ≤ 2.261) within the framework of the Time-Triptych Dynamic Active Vacuum (TT-DAV) geometric cosmological model. The tool allows real-time comparison between TT-DAV distance modulus predictions — derived exclusively from two geometric invariants of the discrete Platonic scaffold, δ_T ≈ 0.12839 and δ_I ≈ 0.17985, with zero free parameters — and standard ΛCDM predictions with user-adjustable H₀ and Ω_m. For each supernova, the application displays the full set of Pantheon+SH0ES observational quantities (redshift in three frames, corrected apparent magnitude, stretch x₁, color c, host galaxy stellar mass, sky coordinates, and survey membership), alongside model-predicted distance moduli and per-object residuals in magnitudes and sigma units. A logarithmic Hubble diagram renders all 1,543 data points with both model curves overlaid, with interactive hover and click-to-select functionality. Global weighted least-squares χ²/ν statistics are computed in real time for both models across the full dataset. The application runs entirely in the browser with no external dependencies, server, or internet connection required after download.
Palabras clave:
Type Ia supernovae · Pantheon+SH0ES · distance modulus · Hubble diagram · TT-DAV framework · geometric cosmology · discrete vacuum scaffold · Regge calculus · tetrahedral angular deficit · cosmological model comparison · interactive visualization · zero free parameters · χ² goodness of fit · redshift · web application

 

 

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Latest:
 
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Related works

Is supplement to
Preprint: 10.5281/zenodo.18913856 (DOI)
Patent: 10.5281/zenodo.19024899 (DOI)
Preprint: 10.5281/zenodo.17855918 (DOI)