Void Velocity Prediction v2: A Phenomenological Bridge Between Local Hubble Measurements and Pasterski Spin Memory via Time Density Contrast

We present a phenomenological toy model that links the Hubble tension to local underdensity and to celestial spin memory. In v1 (DOI: 10.5281/zenodo.22839912), we proposed H0_obs = H0_bare * [1 + α' ln(1/(1+δ))], where δ = (ρ_local - ρ_b)/ρ_b is the matter density contrast, H0_bare = 67.4 km/s/Mpc, and α' = 0.1348. This single-parameter model reproduces local H0 measurements without new physics: KBC void (δ=-0.46) → 73.00, Local volume (δ=-0.30) → 71.03, Bootes supervoid (δ=-0.75) → 76.62, Eridanus supervoid (δ=-0.20) → 69.81 km/s/Mpc. In v2, we provide full executable Python code and propose a formal correspondence to Pasterski et al. (2015) spin memory. We define a dimensionless time density ρ_t,local = ρ_crit/(ρ_b,local + ρ_vac) and note that ΔH0/H0 ~ Δu/u0, where Δu is the spin memory observable Δu = (1/2πL) ∮ C_zz dz. We propose the phenomenological correspondence: <ρ_t>_void ∝ <|C_zz|>_void, i.e., the average celestial shear over a void region encodes the local time density contrast. In this picture, a deep void (large C_zz) yields large Δu, interpreted as lighter local time and higher H0 ≈73 km/s/Mpc (SH0ES), while a dense wall (C_zz→0) yields Δu→0, heavier time, and H0≈67.4 km/s/Mpc (Planck). This is a phenomenological bridge, not a derivation from first principles. It is falsifiable via the relation between void depth and measured H0, and suggests future tests using spin memory templates. Reference: Pasterski, Strominger, Zhiboedov, arXiv:1502.06120 License: CC BY 4.0 Code included in PDF.

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Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-21
DOI
https://doi.org/10.5281/zenodo.22870300
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Cosmology and Gravitation Theories
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article
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Void Velocity Prediction v2: A Phenomenological Bridge Between Local Hubble Measurements and Pasterski Spin Memory via Time Density Contrast

Maury Vega Rodriguez
Zenodo (CERN European Organization for Nuclear Research)
Cosmology and Gravitation Theories
article

Void Velocity Prediction v2: A Phenomenological Bridge Between Local Hubble Measurements and Pasterski Spin Memory via Time Density Contrast

Maury Vega Rodriguez
article en

Abstract

We present a phenomenological toy model that links the Hubble tension to local underdensity and to celestial spin memory. In v1 (DOI: 10.5281/zenodo.22839912), we proposed H0_obs = H0_bare * [1 + α' ln(1/(1+δ))], where δ = (ρ_local - ρ_b)/ρ_b is the matter density contrast, H0_bare = 67.4 km/s/Mpc, and α' = 0.1348. This single-parameter model reproduces local H0 measurements without new physics: KBC void (δ=-0.46) → 73.00, Local volume (δ=-0.30) → 71.03, Bootes supervoid (δ=-0.75) → 76.62, Eridanus supervoid (δ=-0.20) → 69.81 km/s/Mpc. In v2, we provide full executable Python code and propose a formal correspondence to Pasterski et al. (2015) spin memory. We define a dimensionless time density ρ_t,local = ρ_crit/(ρ_b,local + ρ_vac) and note that ΔH0/H0 ~ Δu/u0, where Δu is the spin memory observable Δu = (1/2πL) ∮ C_zz dz. We propose the phenomenological correspondence: <ρ_t>_void ∝ <|C_zz|>_void, i.e., the average celestial shear over a void region encodes the local time density contrast. In this picture, a deep void (large C_zz) yields large Δu, interpreted as lighter local time and higher H0 ≈73 km/s/Mpc (SH0ES), while a dense wall (C_zz→0) yields Δu→0, heavier time, and H0≈67.4 km/s/Mpc (Planck). This is a phenomenological bridge, not a derivation from first principles. It is falsifiable via the relation between void depth and measured H0, and suggests future tests using spin memory templates. Reference: Pasterski, Strominger, Zhiboedov, arXiv:1502.06120 License: CC BY 4.0 Code included in PDF.

Zenodo (CERN European Organization for Nuclear Research)
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Cosmology and Gravitation Theories
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Void Velocity Prediction v2: A Phenomenological Bridge Between Local Hubble Measurements and Pasterski Spin Memory via Time Density Contrast — Maury Vega Rodriguez · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS