Physics & Spacepreprint2026-08-22

A Nonlocal, Baryon-Anchored Analysis of Galactic Acceleration Excess

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Abstract

This preprint presents a fully nested, galaxy-separated test of whether the positive galactic acceleration excess in SPARC rotation curves can be reconstructed from a nonlocal, scale-dependent, baryon-anchored model family. The analysis uses 175 SPARC galaxies and 3391 radial measurements. The nonlocal model reaches prediction accuracy statistically indistinguishable from a foldwise fitted radial acceleration relation (RAR). The dynamical kernel remains positive in all 4500 galaxy-wise bootstrap fits, and a leave-one-out kernel with its local self-contribution removed remains positive in all outer-fold models. A conditional out-of-fold galaxy-profile reassignment test yields p = 1/2001 in all three quality samples. An additional soft-saturation correction shows no consistent incremental predictive gain and does not determine a unique transition scale. A fixed nonlocal q = 0.5 gradient response is therefore specified only as a parsimonious candidate for future external testing. The results identify a reproducible cross-radial, baryon-anchored, scale-dependent predictive structure in the SPARC development sample. They do not establish a fundamental physical mechanism, exclude particle dark matter, or constitute external validation of the frozen candidate model. Version 2 This version contains minor revisions made in preparation for journal submission. The main changes are the removal of earlier self-references to broader theoretical work, a clearer separation of the present empirical analysis from broader interpretive frameworks, several small editorial and clarification changes, and an updated disclosure of the AI-assisted tools used during manuscript preparation and analysis development. The underlying data basis, numerical results, validation procedures, figures, and principal conclusions remain unchanged.

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View paper (DOI)Open access versionOpenAlexZenodo (CERN European Organization for Nuclear Research)Published 2026-08-22

Authors: Ukshin Q. Rexhepi