"Processed SDSS DR16 Quasar Data for VEQF H-model Validation"
收藏资源简介：
VEQF H-model: Processed SDSS DR16 Quasar Data for Hubble Drift Validation This dataset contains the processed quasar data used to validate the Vacuum Energy Quanta Field (VEQF) Hubble Expansion Model (H-model), which proposes a resolution to the Hubble Tension through a thermodynamic drift mechanism in a structured vacuum field. Dataset Overview:- File: sdss_dr16_quasars_calibrated_no_redshift_v1.csv- Entries: 500 high-redshift quasars- Redshift range: 0.2 ≤ z ≤ 2.3- Source catalog: SDSS DR16 Quasar Catalog (Lyke et al. 2020)- Purpose: Validation of H_VEQF(r) predictions across cosmic distances Columns:- zHD: Hubble Diagram redshift (heliocentric)- MAG_G: Observed g-band magnitude (PSFMAG)- M_g: Absolute magnitude, computed as M_g = -25 - 2 log10(1 + z)- d_L: Luminosity distance (meters)- comoving_distance_m: Comoving distance r = d_L / (1+z) (meters)- predicted_H: Predicted drift rate H_VEQF(r) in s⁻¹, from the VEQF model- outlier: Boolean: True if H_VEQF > 2.5e-18 s⁻¹ Scientific Context:The VEQF H-model interprets cosmic expansion as a thermodynamic drift process driven by energy density gradients in a quantized vacuum field. The model separates the observed drift rate into:- H_base = 2.18e-18 s⁻¹ (~67.4 km/s/Mpc) — primordial "Big Bang kick"- H_TD(r): local thermodynamic enhancement due to vacuum coherence At large distances (z > 0.2), H_TD diminishes, so H_VEQF → H_base, matching Planck CMB measurements. Locally, H_VEQF ≈ 2.37e-18 s⁻¹ (~73.2 km/s/Mpc), matching SH0ES. Key Result:- No outliers above 2.5e-18 s⁻¹ were found- All 500 quasars have H_VEQF in [2.18, 2.37] × 10⁻¹⁸ s⁻¹- This supports the model’s prediction that the Hubble Tension is not a contradiction, but a separation of physical components Data Processing:The raw data was extracted from:- SDSS DR16 Quasar Catalog (DR16Q_v4.fits)- Publicly available at: https://www.sdss.org/dr16/ Processing steps:1. Filtered for 0.2 ≤ z ≤ 2.32. Sampled 500 quasars (random state = 42)3. Computed luminosity and comoving distances4. Applied H_VEQF(r) = H_base + (c³ ρ(r) ΔT Δτ²) / (k_B T²), with ρ(r) = ρ₀ (r₀ / (r + r_offset))³5. Saved to CSV Full Python script and raw FITS file are available in the VEQF research repository. References:- Lyke, B. W., et al. 2020, AJ, 159, 108 (SDSS DR16) https://doi.org/10.3847/1538-3881/ab6bea- Scolnic, D. M., et al. 2022, ApJ, 938, 113 (Pantheon+) https://doi.org/10.3847/1538-4357/ac8b7a- Oliphant, T. E. 2006, Comput. Sci. Eng., 8, 66 (NumPy) https://doi.org/10.1109/MCSE.2007.55- Virtanen, P., et al. 2020, Nat Methods, 17, 261 (SciPy) https://doi.org/10.1038/s41592-019-0686-2- Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 (Matplotlib) https://doi.org/10.1109/MCSE.2007.55- McKinney, W. 2010, Proc. 9th Python Sci. Conf., 56–61 (pandas) https://doi.org/10.25080/Majora-92bf1922-00a Author:Enver TorlakovicIndependent Researcher, Sydney, AustraliaEmail: etorlakovic@gmail.comORCID: https://orcid.org/0009-0001-2867-0769Zenodo: https://zenodo.org/communities/veqf This work is part of the VEQF Theory series, which redefines gravity, mass, and cosmic structure as emergent thermodynamic phenomena.
