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atomic-clocks

Here are 11 public repositories matching this topic...

Global Time Echoes: Distance-Structured Correlations in GNSS Clocks — Multi-center analysis of 62.7M GNSS clock measurements revealing distance-structured correlations with exponential decay (λ = 3,330–4,549 km), consistent with screened scalar field predictions from the Temporal Equivalence Principle.

  • Updated Aug 15, 2026
  • Python

Global Time Echoes: Raw RINEX Consistency Test — Independent replication of GNSS clock correlations from raw RINEX data, confirming that distance-structured TEP signatures persist across independent processing pipelines.

  • Updated Aug 6, 2026
  • Python

Global Time Echoes: 25-Year Analysis of CODE Precise Clock Products — 25-year analysis of 165.2M GNSS clock measurements revealing persistent velocity-dependent correlations, orbital coupling (r=−0.888), 18.6-year lunar nutation detection, and CMB frame alignment.

  • Updated Aug 13, 2026
  • Python

Temporal Topology Saturation Scale: Cross-Scale Consistency of ρ_T — Universal critical density ρ_T ≈ 20 g/cm³ from R ∝ M^(1/3) scaling, GNSS-calibrated and validated across SPARC galaxies, Milky Way, and magnetars. Temporal Topology screening reconciles galactic dynamics with GR tests.

  • Updated Aug 6, 2026
  • HTML

Global Time Echoes: Empirical Synthesis — Empirical synthesis of 25.3 years GNSS timing data (165.2M pairs) revealing distance-structured correlations (λT=4,201±1,967 km) with TEP signatures: EW/NS anisotropy, orbital coupling, CMB alignment, and nutation couplings.

  • Updated Aug 6, 2026
  • HTML

A Monte Carlo simulation in Python to model vacuum-induced frequency drifts in atomic clocks, with code and visuals (experimental setup, simulated vs. real-world comparison, and drift graph), as described in "Probing Vacuum-Induced Clock Drifts via Quantum Metrology: A Testable Hypothesis" (DOI: 10.5281/zenodo.15163879). Licensed under GPL 3.0.

  • Updated Apr 9, 2025
  • Python

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