Related papers: Configurational entropy in $f(R,T)$ brane models

$f(T,B)$ teleparallel gravity is a recently proposed straightforward generalization of the popular $f(T)$ teleparallel gravity by the incorporation of a boundary term $B=\frac{2}{e}\partial_{i}(e T ^{i}) = \bigtriangledown_{i}T^{i}$ where…

Making decisions freely presupposes that there is some indeterminacy in the environment and in the decision making engine. The former is reflected on the behavioral changes due to communicating: few changes indicate rigid environments;…

In this work we study braneworld configurations in the scalar-tensor representation of the $f\left(R,T\right)$ gravity theory in the presence of a Cuscuton term in the source field matter Lagrangian. We start by deriving the scalar-tensor…

We introduce a novel approach, inspired from the theory of renewal processes, to determine the configurational entropy of ensembles of constrained configurations of particles on the one-dimensional lattice. The proposed method can deal with…

We generalize nested multiply warped braneworld models by incorporating non-zero brane curvature caused by an effective cosmological constant {\Omega} induced on the 3-branes. Starting with the doubly warped model, we first analyze the case…

We present cosmological constraints on deviations from general relativity (GR) from the first-year of clustering observations from Dark Energy Spectroscopic Instrument (DESI) in combination with other datasets. We first consider…

Braneworld scenarios consider our observable universe as a brane embedded in a 5D space, named bulk. In this work, I derive the field equations of a braneworld model in a generalized theory of gravitation, namely $f(R,T)$ gravity, with $R$…

Invariance-principle-based methods such as Invariant Risk Minimization (IRM), have recently emerged as promising approaches for Domain Generalization (DG). Despite promising theory, such approaches fail in common classification tasks due to…

We establish constraints on $f(T)$ gravity by considering the possibility of a scenario that supports a phantom crossing of the equation of state parameter $\omega_{DE}$. After determining the viable parameter space of the model, while…

We study the dynamics of brane worlds coupled to a scalar field and gravity, and find that self-tuning of the cosmological constant is generic in theories with at most two branes or a single brane with orbifold boundary conditions. We…

Entropic tilting (ET) is a Bayesian decision-analytic method for constraining distributions to satisfy defined targets or bounds for sets of expectations. This report recapitulates the foundations and basic theory of ET for conditioning…

An exact cosmological solution of Einstein field equations (EFEs) is derived for a dynamical vacuum energy in $f(R,T)$ gravity for Friedmann-Lemaitre-Robertson-Walker (FLRW) space-time. A parametrization of the Hubble parameter is used to…

We study the behavior of spatially homogeneous brane-worlds close to the initial singularity in the presence of both local and nonlocal stresses. It is found that the singularity in these brane-worlds can be locally either isotropic or…

The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric…

In this work we perform an observational data analysis on the $f(R,T)$ gravity with the aim of constraining the parameter space of the model. Five different models are considered and the 30 point $z-H(z)$ cosmic chronometer data is used in…

Simulations of complex physical systems are typically realized by discretizing partial differential equations (PDEs) on unstructured meshes. While neural networks have recently been explored for surrogate and reduced order modeling of PDE…

In the present work, we present a detailed discussion of a Riemannian metric structure originally introduced in [Gori et al., \textit{J. Stat. Mech.}, \textbf{9} 093204 (2018)] on the configuration space and on phase space allowing us to…

We present an operator-free, measure-theoretic approach to the conditional mean embedding (CME) as a random variable taking values in a reproducing kernel Hilbert space. While the kernel mean embedding of unconditional distributions has…

We propose a new scheme for constraining the dark energy equation of state parameter/parameters based on the study of the evolution of the configuration entropy. We analyze a set of one parameter and two parameter dynamical dark energy…

For frontier experiments operating at the edge of detectability, instrument design directly determines the probability of discovery. We introduce Conditional Neural Bayes Ratio Estimation (cNBRE), which extends neural Bayes ratio estimation…