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Bounding the Cosmological Constant using Galactic Rotation Curves from the SPARC Dataset
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abstract
Dark energy (and its simplest model, the Cosmological Constant or $\Lambda$) acts as a repulsive force that opposes gravitational attraction. Assuming galaxies maintain a steady state over extended periods, the estimated upper limit on $\Lambda$ studies its pushback to the attractive gravitational force of dark matter. From the SPARC dataset, we select galaxies that are best fitted by the Navarro-Frenk-White (NFW) and Hernquist density models. Introducing the presence of $\Lambda$ in these galaxies helps to establish the upper limit on its repulsive force. This upper limit on $\Lambda$ is around $\rho_{\left(<\Lambda\right)} \sim 10^{-25}$~kg/m$^3$, only two orders of magnitude higher than the one measured by Planck. {We show that for galaxies with detectable velocities far from the galaxy core, the upper limit on $\Lambda$ is lower. Furthermore, we show that galaxies and other systems follow the same principle: for larger orbital periods the upper limit on $\Lambda$ is lower. Consequently, we address the implications for future measurements on the upper limit and the condition for detecting the impact of $\Lambda$ on galactic scales.
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Cited by 1 Pith paper
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Learning from galactic rotation curves: a neural network approach
Neural networks trained on simulated rotation curves can infer ultra-light dark matter and baryonic parameters from SPARC dwarf galaxies, with uncertainties comparable to MCMC.
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