Machine learning regressors trained on Rapster simulations forecast that globular clusters rarely host black holes above 100 solar masses while a few nuclear star clusters may exceed this threshold.
Villaescusa-Navarro, D
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LPT-matched integrators for cosmological simulations outperform FastPM with O(1-100) timesteps while convergence is limited to order 3/2 post-shell-crossing due to acceleration field irregularity.
Einstein-Cartan model with torsion and H = -α φ assumption fitted via MCMC to CC data produces H0 values of 66-69 km/s/Mpc favoring the CMB side of the Hubble tension.
citing papers explorer
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Predicting intermediate-mass black hole formation in star clusters with machine learning
Machine learning regressors trained on Rapster simulations forecast that globular clusters rarely host black holes above 100 solar masses while a few nuclear star clusters may exceed this threshold.
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Perturbation-theory informed integrators for cosmological simulations
LPT-matched integrators for cosmological simulations outperform FastPM with O(1-100) timesteps while convergence is limited to order 3/2 post-shell-crossing due to acceleration field irregularity.
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Cosmic Dynamics in Einstein-Cartan Theory: Analysing Hubble Tension through Curvature and Torsion field
Einstein-Cartan model with torsion and H = -α φ assumption fitted via MCMC to CC data produces H0 values of 66-69 km/s/Mpc favoring the CMB side of the Hubble tension.