I'm a former Tech Director who left the industry to pursue independent research in foundational physics. I've been modeling the vacuum not as empty space, but as a saturated Born-Infeld superfluid (BEC).
This repo contains the Python simulations backing my recent papers.
THE CODE:
vacuum_sim.py uses a binary search to find the critical vacuum non-linearity parameter (b) that results in a stable vortex. The result? It naturally converges to a geometric impedance of alpha ~= 1/137.036.
KEY RESULTS:
1. Alpha Origin: Derived from the impedance mismatch between a topological vortex and the discrete vacuum grid.
2. LHC Anomaly: The model also explains the CDF II W-mass tension (7-sigma) as a hydrodynamic shockwave, fitting the data where the Standard Model fails.
Hi HN,
I'm a former Tech Director who left the industry to pursue independent research in foundational physics. I've been modeling the vacuum not as empty space, but as a saturated Born-Infeld superfluid (BEC).
This repo contains the Python simulations backing my recent papers.
THE CODE: vacuum_sim.py uses a binary search to find the critical vacuum non-linearity parameter (b) that results in a stable vortex. The result? It naturally converges to a geometric impedance of alpha ~= 1/137.036.
KEY RESULTS: 1. Alpha Origin: Derived from the impedance mismatch between a topological vortex and the discrete vacuum grid. 2. LHC Anomaly: The model also explains the CDF II W-mass tension (7-sigma) as a hydrodynamic shockwave, fitting the data where the Standard Model fails.
PAPERS (ZENODO): - Code: https://github.com/moseszhu999/geometric-vacuum-sim - LHC Shockwaves: https://doi.org/10.5281/zenodo.17695129 - Alpha Derivation: https://doi.org/10.5281/zenodo.17695341 - Whitepaper: https://doi.org/10.5281/zenodo.17695422
I'm looking for feedback on the simulation logic. Thanks!