On the functional form of the radial acceleration relation
Harry Desmond, Deaglan J. Bartlett, Pedro G. Ferreira

TL;DR
This study uses Exhaustive Symbolic Regression to analyze the radial acceleration relation in galaxy data, revealing that the relation's functional form is not definitively MOND-like due to data limitations.
Contribution
It introduces ESR as a prior-free method to explore the RAR's functional form, challenging previous assumptions about its law-like nature.
Findings
Best fits show $g_{obs} eq g_{bar}$ at high accelerations
Deep-MOND limit $g_{obs} o oot{2}rom g_{bar}$ is not evident
Data limitations prevent definitive conclusions about the RAR's form
Abstract
We apply a new method for learning equations from data -- Exhaustive Symbolic Regression (ESR) -- to late-type galaxy dynamics as encapsulated in the radial acceleration relation (RAR). Relating the centripetal acceleration due to baryons, , to the total dynamical acceleration, , the RAR has been claimed to manifest a new law of nature due to its regularity and tightness, in agreement with Modified Newtonian Dynamics (MOND). Fits to this relation have been restricted by prior expectations to particular functional forms, while ESR affords an exhaustive and nearly prior-free search through functional parameter space to identify the equations optimally trading accuracy with simplicity. Working with the SPARC data, we find the best functions typically satisfy at high , although the coefficient of proportionality…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · Statistics Education and Methodologies
