Structural Non-Closure in Galactic Rotation Curves: A Regime-Dependent Diagnostic Using SPARC Data

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Autor principal: Tavella, Danilo
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2026
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author Tavella, Danilo
author_facet Tavella, Danilo
contents <div>Galactic rotation curves remain one of the most persistent empirical challenges in modern astrophysics. Most explanatory frameworks — including dark matter halo models and modified gravity proposals — implicitly assume that a single dynamical law or universal correction should account for the kinematic behavior of spiral galaxies across heterogeneous observational regimes.</div> <div> </div> <div>This technical note explores a different diagnostic perspective. Instead of proposing a new gravitational theory, the analysis examines whether the expectation of global explanatory closure itself may be structurally fragile when galaxies with heterogeneous observational traces are evaluated under a single correction framework.</div> <div> </div> <div>Using the SPARC (Spitzer Photometry and Accurate Rotation Curves) dataset as a diagnostic reference sample, a minimal long-range correction proxy is introduced in order to test the stability of a single global correction scale across galaxies with different structural properties and observational depth.</div> <div> </div> <div>The analysis suggests that improvements obtained under a fixed global correction scale tend to organize according to structural regime: extended spiral systems may exhibit coherent adjustments under the diagnostic proxy, while smaller or observationally limited systems remain inconsistent under the same global parameterization.</div> <div> </div> <div>A second structural aspect concerns the comparability of observational traces. Galaxies in the SPARC dataset differ substantially in radial coverage, sampling density, surface brightness, and signal-to-noise characteristics. These differences affect the informational depth of rotation-curve measurements and complicate the legitimacy of direct cross-system comparison under a single global fitting criterion.</div> <div> </div> <div>Filtering strategies based on trace robustness can stabilize inferred parameters across subsets of the dataset but do not restore universal closure across the full sample.</div> <div> </div> <div>Taken together, these observations suggest that the rotation-curve problem may involve two interacting structural layers: (1) the legitimacy of cross-system trace comparability and (2) the amplitude of regime-dependent corrections.</div> <div> </div> <div>The purpose of this work is methodological rather than theoretical. The correction proxy used in the analysis carries no ontological commitment and is intended solely as a diagnostic tool to illustrate how structural limits of global closure may arise when heterogeneous observational regimes are forced into a single universal correction framework.</div>
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spellingShingle Structural Non-Closure in Galactic Rotation Curves: A Regime-Dependent Diagnostic Using SPARC Data
Tavella, Danilo
galactic rotation curves
SPARC dataset
regime-dependent closure
global closure
observational comparability
astrophysical inference
structural diagnostics
long-range corrections
<div>Galactic rotation curves remain one of the most persistent empirical challenges in modern astrophysics. Most explanatory frameworks — including dark matter halo models and modified gravity proposals — implicitly assume that a single dynamical law or universal correction should account for the kinematic behavior of spiral galaxies across heterogeneous observational regimes.</div> <div> </div> <div>This technical note explores a different diagnostic perspective. Instead of proposing a new gravitational theory, the analysis examines whether the expectation of global explanatory closure itself may be structurally fragile when galaxies with heterogeneous observational traces are evaluated under a single correction framework.</div> <div> </div> <div>Using the SPARC (Spitzer Photometry and Accurate Rotation Curves) dataset as a diagnostic reference sample, a minimal long-range correction proxy is introduced in order to test the stability of a single global correction scale across galaxies with different structural properties and observational depth.</div> <div> </div> <div>The analysis suggests that improvements obtained under a fixed global correction scale tend to organize according to structural regime: extended spiral systems may exhibit coherent adjustments under the diagnostic proxy, while smaller or observationally limited systems remain inconsistent under the same global parameterization.</div> <div> </div> <div>A second structural aspect concerns the comparability of observational traces. Galaxies in the SPARC dataset differ substantially in radial coverage, sampling density, surface brightness, and signal-to-noise characteristics. These differences affect the informational depth of rotation-curve measurements and complicate the legitimacy of direct cross-system comparison under a single global fitting criterion.</div> <div> </div> <div>Filtering strategies based on trace robustness can stabilize inferred parameters across subsets of the dataset but do not restore universal closure across the full sample.</div> <div> </div> <div>Taken together, these observations suggest that the rotation-curve problem may involve two interacting structural layers: (1) the legitimacy of cross-system trace comparability and (2) the amplitude of regime-dependent corrections.</div> <div> </div> <div>The purpose of this work is methodological rather than theoretical. The correction proxy used in the analysis carries no ontological commitment and is intended solely as a diagnostic tool to illustrate how structural limits of global closure may arise when heterogeneous observational regimes are forced into a single universal correction framework.</div>
title Structural Non-Closure in Galactic Rotation Curves: A Regime-Dependent Diagnostic Using SPARC Data
topic galactic rotation curves
SPARC dataset
regime-dependent closure
global closure
observational comparability
astrophysical inference
structural diagnostics
long-range corrections
url https://doi.org/10.5281/zenodo.18936964