SPARC Disk Galaxy Coherence Tests and Analysis Code for Observer-Normalized Scale Relativity

SPARC Coherence / J-Variant Stress Tests This archive provides the computational analyses supporting the results reported in Stress Testing Observer-Normalized Coherence in Disk Galaxies: Distance, Radius, and Surface-Brightness Robustness Using SPARC (DOI: 10.5281/zenodo.18284091). The contents include the analysis code, a fixed snapshot of the input data, and generated outputs used to evaluate the robustness of the acceleration-domain coherence form under distance perturbations, alternate radius definitions, and surface-brightness diagnostics using the SPARC galaxy sample. The analyses are diagnostic and adversarial in intent. They are designed to test whether the observed coherence survives known catalog systematics and correlated quantities, rather than to optimize, fit, or tune the relation. Contents sparc_j_tests.py — Computes the Q=1 (Newtonian) acceleration-domain coherence formJ3=Mb/(V2R)J_3 = M_b / (V^2 R)J3=Mb/(V2R) and evaluates scatter stability across intrinsic morphology bins, distance-covariance Monte Carlo perturbations, alternate radius definitions (Reff, Rdisk, RHI), and surface-brightness splits (effective and disk-averaged). sparc_j_tests_with_residuals.py — Auxiliary diagnostic script that computes log-space residuals of the baseline coherence form and generates residual plots with respect to radius, baryonic mass, and rotation velocity. This script is used only for post-hoc residual diagnostics and does not modify the coherence form or any reported scatter statistics. Raw SPARC.xlsx — Input dataset (SPARC v1 summary table, reformatted for Excel). The data are read directly and are not altered by the analysis. ExecutionPlace the analysis scripts and Raw SPARC.xlsx in the same directory and run: python sparc_j_tests.py (Optional diagnostic step) python sparc_j_tests_with_residuals.py Output CSV files and residual plots are written to the outputs/ directory. Notes Column headers are auto-detected to ensure compatibility with SPARC summary tables. No fitting, tuning, or data-dependent parameter selection is performed. All reported results are direct evaluations of the coherence form using catalog-reported quantities. The analysis pipeline is intentionally frozen to minimize researcher degrees of freedom. This version is synchronized with the SPARC-native reproducibility fixes archived in the associated GitHub repository (release v1.1). No scientific conclusions have changed; the update ensures consistent execution against the raw SPARC summary tables.