Skip to content
#

modified-gravity

Here are 22 public repositories matching this topic...

Raw RINEX validation of distance-structured correlations in GNSS atomic clocks. Detects exponential decay signatures (λ≈1-4 km) in 539 stations using SPP with broadcast ephemerides, eliminating processing artifact hypothesis. Shows E-W>N-S anisotropy, CMB alignment, orbital coupling. TEP-GNSS Paper 3.

  • Updated May 24, 2026
  • Python

RBH-1 runaway black hole as Temporal Topology soliton candidate. Explains 650 km/s velocity discontinuity with cold gas via metric shock. TEP calibration: R_T≈7.8×10⁷ km from GNSS. Alternative to shock physics cooling problem

  • Updated May 24, 2026
  • Python

The ACM Trunk: a rigid holographic framework for galactic dynamics. This repository provides the core analytical engine for predicting galaxy rotation behavior from baryonic distributions via linear holographic screening. Tagline No galaxy-by-galaxy fits. No hidden knobs. Just the physics of the background floor.

  • Updated Mar 29, 2026
  • Python

Deterministic reproducibility capsule for GIFT Paper 1. Reproduces the deep-regime scaling and normalization of the RAR and BTFR from the SPARC dataset using fixed-slope ODR fits. Code, derived data, and verification figures included. Archived snapshot: Zenodo DOI 10.5281/zenodo.18513729.

  • Updated Feb 8, 2026
  • Python

Globular cluster pulsar spin-down anomaly: 197 cluster vs 346 field pulsars show 0.40 dex residual (8.3σ). Suppressed density scaling (Γ=0.39±0.08 vs Newtonian Γ=0.72, 4.1σ). Tests TEP observable response coefficient κ_MSP

  • Updated May 24, 2026
  • Python

The Integrated Toroidal-Syntropic Model (ITSM): A covariant framework replacing dark matter and dark energy with topological superfluid dynamics. This repository contains the formal relativistic manuscript and a complete computational falsifiability suite, featuring Python MCMC solvers for SPARC kinematics, NANOGrav resonance, and DESI 2024 data.

  • Updated May 23, 2026
  • Python

Structural selection framework for nonlinear field systems based on structural free energy and the Critical Coherence Index (CCI). Includes reproducible experiments, cosmological benchmarks, and observable-layer tests (H(z), CCI projection, fσ8 signatures).

  • Updated May 25, 2026
  • Python

Unified Cosmological Model: A single scalar field ($\Phi_{D1}$) simultaneously explains the origin of matter (Baryogenesis) and Dark Energy, statistically, Preliminary model fits suggest tension with a ΛCDM benchmark under the assumptions used here; full independent validation remains necessary.

  • Updated Mar 24, 2026
  • Python

Code & data reproducing the Siamese Interference Cosmology analysis against Son & Lee (2025). We show that cosmic deceleration (q0​>0) emerges naturally from phase interference, predicting a falsifiable hemispheric anisotropy for Euclid/LSST.

  • Updated Nov 24, 2025
  • Python

Reproducible experiments and papers for a geometric-residual/statistical-learning framing of the galaxy missing-mass problem, including SPARC rotation-curve residual diagnostics and masked dictionary learning of residual-of-residual fields.

  • Updated May 4, 2026
  • Python

Comparative cosmology framework showing how CPT-Siamese phase dynamics resolves the main failures of ΛCDM: H₀ tension, σ₈ tension, Axis of Evil, JWST early galaxies and vacuum energy. Includes analytic model, toy simulations, and H(z), q(z) figures. Open reproducible science.

  • Updated Dec 9, 2025
  • Python

Gaia DR3 wide binaries (341,315 systems) show Temporal Shear recovery at R_s=2,646±182 AU (Δχ²=14,845 vs Newtonian). Saturation α_sat=0.366±0.012. Environmental ordering confirmed (p<10⁻⁴). TEP conformal screening transition

  • Updated May 24, 2026
  • Python

Improve this page

Add a description, image, and links to the modified-gravity topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the modified-gravity topic, visit your repo's landing page and select "manage topics."

Learn more