Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2503.21243

Cosmological Implications of the Gong-Zhang Parameterization in Rastall Gravity: A Deep Learning and Observational Study

Vinod Kumar Bhardwaj·Anil Kumar Yadav·Manish Kalra·Pankaj·Rajendra Prasad
View original source ↗Read source document ↗Export metadata ↓

Abstract

In this study, we have explored the cosmological dynamics of an isotropic, homogeneous universe in Rastall gravity. For this purpose, we use the parameterization of the EoS parameter in the form $\omega(z) = \frac{\omega_{0}}{(z+1)} $ to derive the explicit solution of the field equations in Rastall gravity. We constrained the cosmological parameters for the derived model by the Markov Chain Monte Carlo (MCMC) approach utilizing OHD, BAO, and Pantheon plus compilation of SN Ia datasets. We also constrained the model parameters using deep learning techniques and the CoLFI Python package. This paper introduces an innovative deep-learning approach for parameter inference. The deep learning method significantly surpasses the MCMC technique regarding optimal fit values, parameter uncertainties, and relationships among parameters. This conclusion is drawn from a comparative analysis of the two methodologies. Additionally, we determined the transition redshift $z_t = 0.941$, which signifies the shift in the Universe's model from an early deceleration phase to the present acceleration phase. The diagnosis of the model with diagnostic tools like statefinders, jerk parameter, and $O_m$ diagnostics are presented and analyzed. The validation of the model's energy conditions is also examined.

Explore related subjects

gr-qc

Keep this discovery

BibTeXRIS

Vinod Kumar Bhardwaj, Anil Kumar Yadav, Manish Kalra, Pankaj, Rajendra Prasad. 2025-03-27. Cosmological Implications of the Gong-Zhang Parameterization in Rastall Gravity: A Deep Learning and Observational Study. https://arxiv.org/abs/2503.21243

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Electrovacuum Black Hole Uniqueness

We prove the black hole uniqueness conjecture in the axially symmetric, stationary, electrovacuum setting, subject to the refined asymptotic analysis of the associated singular harmonic maps, which includes an analyticity hypothesis at the axes. More precisely, it is shown that any asymptotically flat solution of the Einstein--Maxwell equations in this class, with more than one black hole horizon component is either: Majumdar--Papapetrou, up to a duality rotation, in which case all logarithmic angle defects vanish, or every finite axis rod logarithmic angle defect is strictly negative and hence every interaction force is strictly attractive. The proof extends the singular harmonic map method used for vacuum Kerr uniqueness in [18].

gr-qc↗
arXiv2026

Constraining Modified Mass-to-Horizon Cosmology Through Primordial Inflationary Observables

We investigate slow-roll inflation in a modified cosmological framework inspired by a generalized mass-to-horizon relation (MHR), $M=\gamma {c^2 L^n}/{G}$, where $n$ is a real parameter and $\gamma$ a dimensional constant. Using Padmanabhan's emergence paradigm, we derive the modified Friedmann equations for a flat FRW universe and analyze the dynamics of a canonical scalar field (inflaton) under the slow-roll approximation. We study the resulting inflationary phenomenology for power-law and Starobinsky potentials. For power-law potentials, the MHR modification fails to reconcile these models with current CMB constraints on $r$ and $n_s$. In contrast, Starobinsky inflation exhibits significant sensitivity to deviations from $n=1$. A perturbative analysis ($n=1+\Delta$) yields corrections to inflationary observables. We observe that the scalar power-spectrum normalization, under a fixed-Starobinsky prescription, imposes the stringent constraint $0.960 \lesssim n \lesssim 1.040$ for $N=60$ efolds. This is considerably tighter than spectral-index bounds. Our results establish inflation, particularly Starobinsky-like models, as a sensitive probe of generalized horizon thermodynamics and departures from standard MHR scaling.

gr-qc↗
arXiv2026

Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction

In the last decade, kilometre-scale interferometric gravitational-wave detectors have observed hundreds of compact binary mergers, the majority of which are binary black holes. However, the data are noise-dominated, and multiple independent search algorithms (pipelines) are used to enhance sensitivity and improve robustness. Rather than the standard approach of selecting the most significant pipeline output, we combine the outputs from all pipelines using a conformal prediction-based framework to provide statistically rigorous confidence estimates for candidate events. While combining pipelines improves sensitivity and ranking robustness, it requires a principled statistical framework that remains valid as data properties evolve across observing runs. A key challenge is distribution shifts between simulated datasets used for training and calibration and the real, unlabelled, observations used for testing, which can invalidate coverage guarantees and bias confidence estimates. In this work, we address this challenge by incorporating likelihood-ratio reweighting into our conformal prediction framework to account for covariate shift. Using mock datasets containing simulated signals, we demonstrate that weighted conformal prediction restores well-calibrated coverage under covariate shift and increases the confidence of events near the detection threshold, recovering true signals that would otherwise be missed.

gr-qc↗