Modeling the Persistent Bow Shock of RXJ0528+2838 with Standardized Parameters
Abstract
This paper applies the Gravity of Probability (GoP) framework to a recently observed compact-object system, using the persistent bow shock of the polar cataclysmic variable RXJ0528+2838 as a local astrophysical benchmark. The analysis employs the same standardized parameter set developed in the main GoP thesis and does not introduce any new free parameters.The full theoretical formalism, cosmological motivation, and galaxy- and cluster-scale validations of the Gravity of Probability framework are presented in the companion thesis:J. Waters, The Gravity of Probability: Replicating Dark Matter Effects Through Quantum Decoherence Curvature (2025), https://figshare.com/articles/thesis/The_Gravity_of_Probability_i_Replicating_Dark_Matter_Effects_Through_Quantum_Decoherence_Curvature_i_/29815934The GoP framework also makes preregistered predictions for large-scale structure and void thermodynamics to be tested by upcoming DESI Value Added Catalogs and Euclid releases in 2026. This compact-object application is intended as an independent cross-domain test of the same fixed-parameter theory.A compact Python script is provided to reproduce the numerical results presented here and to allow direct insertion of future observational data for falsifiability tests. Within standard compact-binary physics, no known mechanism reproduces the observed bow-shock power of RXJ0528+2838 without invoking an additional energy channel beyond canonical accretion and wind modelsConsistent application of the same untuned parameters from thesis and other papers:• κA=1.5×10−15 — normalization of the probabilistic curvature coupling • E_0=1012erg — characteristic decoherence energy scale • f_ent=0.20 — coherent–decoherent entanglement fraction • A_CP=0.0245 — asymmetry parameter governing net probabilistic flux
Fields of Study & Subjects
Astrophysical Phenomena and Observations
Pulsars and Gravitational Waves Research
Cosmology and Gravitation Theories
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026
- Document type
- Preprint