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We present a neural net algorithm for parameter estimation in the context of large cosmological data sets. Cosmological data sets present a particular challenge to pattern-recognition algorithms since the input patterns (galaxy redshift…
The behavior of the dark energy equation of state (EOS) is crucial in distinguishing different cosmological models. With a model independent approach, we constrain the possible evolution of the dark energy EOS. Gamma-ray bursts (GRBs) of…
We study the late-time evolution of the Universe within the f(R,G) gravity framework, where R is the Ricci scalar and G is the Gauss-Bonnet term. To make the model tractable, we propose a parametrization scheme and determine its parameters…
This paper rigorously examines the potential of the $f(T, \mathcal{T})$ theory as a promising framework for understanding the dark sector of the universe, particularly in relation to cosmic acceleration. The $f(T, \mathcal{T})$ theory…
Recent estimates of cosmological parameters derived from Cosmic Microwave Background (CMB) anisotropies are based on the assumption that we know the precise amount of energy density in relativistic particles in the universe, $\omega_{rel}$,…
We investigate the cosmological implications of entropy-based approaches in the context of Holographic Dark Energy (HDE) and Gravity-Thermodynamics (GT) formalisms. We utilise the extended Barrow entropy form, with the index parameter…
The stable critical points and their corresponding cosmology are derived in the teleparallel gravity with an added Gauss-Bonnet topological invariant term. We have analyzed the dynamics of the Universe by presenting two cosmological viable…
A novel function for modified gravity is proposed, $f(R, T)=R+\lambda R^2+2\beta\ln(T)$, with constants $\lambda$ and $\beta$, scalar curvature $R$, and the trace of stress energy tensor $T$, satisfying $T=\rho-3p>0$. Subsequently, two…
In this work, we construct the logical framework of the Poincar\'e gauge gravity cosmology based on five postulations, and introduce the modified redshift relation within this framework. Then we solve a system with quadratic action and some…
We study the predictions for structure formation in an induced gravity dark energy model with a quartic potential. By developing a dedicated Einstein-Boltzmann code, we study self-consistently the dynamics of homogeneous cosmology and of…
We present CosmicANNEstimator (Cosmological Parameters Artificial Neural Network Estimator), a machine learning approach for constraining cosmological parameters within the Lambda Cold Dark Matter ($\Lambda$CDM) framework. Our methodology…
We propose how to calibrate long gamma-ray burst (GRB) correlations employing intermediate redshift data sets, instead of limiting to $z\simeq0$ catalogs. To do so, we examine the most updated observational Hubble data (OHD) and baryonic…
As cosmology rapidly approaches the data-dominated phase of stage IV large scale structure surveys, the modelling of nonlinear scales has become a serious challenge that faces the community, particularly when analysing models beyond $w$CDM.…
We consider the cosmologies that arise in a subclass of f(R) gravity with f(R)=R+\mu ^{2n+2}/(-R)^{n} and -1<n<0 in the metric (as opposed to the Palatini) variational approach to deriving the gravitational field equations. The calculations…
Mapping the expansion history of the universe is a compelling task of physical cosmology, especially in the context of the observational evidence for the recent acceleration of the universe, which demonstrates that canonical theories of…
Constraining the dark energy deceleration parameter is one of the fascinating topics in the recent cosmological paradigm. This work aims to reconstruct the dark energy using parametrization of the deceleration parameter in a flat FRW…
We give a Lagrangian formulation for the theory of Rastall of gravitation. After proposing a Lagrangian density that reproduces the equations of motion postulated by Rastall, we study the cosmological consequences and fit the parameters…
Data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…
We derive a theory-independent version of the momentum constraint equation for use in cosmology, as a part of the Parameterised Post-Newtonian Cosmology (PPNC) framework. Our equations are constructed by adapting the corresponding…
We present a path-integral likelihood formalism that extends parameterized likelihood analyses to include continuous functions. The method finds the maximum likelihood point in function-space, and marginalizes over all possible functions,…