10 papers
Late-Time Alleviation of the Hubble Tension in CPL Cosmology with Massive Neutrinos via Bayesian Physics-Informed Neural Networks
Muhammad Yarahmadi, Amin Salehi
We present a comprehensive Bayesian analysis of the Hubble constant within the framework of Physics-Informed Neural Networks (PINNs), focusing on the standard CDM model and its…
Towards a Machine Learning Solution for Hubble Tension: Physics-Informed Neural Network (PINN) Analysis of Tsallis Holographic Dark Energy in Presence of Neutrinos
Muhammad Yarahmadi, Amin Salehi
We present a Physics-Informed Neural Network (PINN) framework for reconstructing the redshift-dependent Hubble parameter \(H(z)\) within the Tsallis Holographic Dark Energy (THDE)…
Neutrino Interactions with perturbed Rastall Gravity: A Novel Approach to Reducing the Hubble Tension
Muhammad Yarahmadi
We investigate the cosmological implications of coupling neutrinos to perturbed Rastall gravity, focusing on its impact on the Hubble constant () and the associated tension be…
A Bayesian PINN Framework for Barrow-Tsallis Holographic Dark Energy with Neutrinos: Toward a Resolution of the Hubble Tension
Muhammad Yarahmadi, Amin Salehi
We investigate the Barrow-Tsallis Holographic Dark Energy (BTHDE) model using both traditional Markov Chain Monte Carlo (MCMC) methods and a Bayesian Physics-Informed Neural Networ…
Cosmic Bulk Flow Analysis in Modified Gravity Theories: and Perturbed Models with Neutrino Coupling
Muhammad Yarahmadi, Amin Salehi
In this study, we explore the characteristics of bulk flow across various redshift ranges within the frameworks of gravity, perturbed gravity, and perturbed gr…
The interaction of neutrinos with Phantom, Quintessence, and Quintum scalar fields and its effect on the formation of structures in the early Universe
Muhammad Yarahmadi, Amin Salehi
Despite the fact that the mass of the neutrinos is so small, they are produced in such vast numbers in the early Universe that their mass induces subtle effects on cosmological obs…