Related papers: Solving the $H_{0}$ tension in $f(T)$ Gravity thro…
We explore the impact of the Sandage-Loeb (SL) test on the precision of cosmological constraints for $f(T)$ gravity theories. The SL test is an important supplement to current cosmological observations because it measures the redshift drift…
$f(Q,T)$ gravity is a novel extension of the symmetric teleparallel gravity where the Lagrangian $L$ is represented through an arbitrary function of the nonmetricity $Q$ and the trace of the energy-momentum tensor $T$ \cite{fqt}. In this…
We propose a theoretical model called "information gravity" to describe the text generation process in large language models (LLMs). The model uses physical apparatus from field theory and spacetime geometry to formalize the interaction…
Estimates of the Hubble constant, $H_0$, from the distance ladder and the cosmic microwave background (CMB) differ at the $\sim$3-$\sigma$ level, indicating a potential issue with the standard $\Lambda$CDM cosmology. Interpreting this…
In this work, we present a method for numerically solving the Friedmann equations of modified $f(\mathcal{G})$ gravity in the presence of pressureless matter. This method enables us to predict the redshift behaviour of the Hubble expansion…
Metallic spin glass systems, such as dilute magnetic alloys, are characterized by randomly distributed local moments coupled to each other through a long-range electron-mediated effective interaction. We present a scalable machine learning…
The $\Lambda$CDM model provides a good fit to most astronomical observations but harbors large areas of phenomenology and ignorance. With the improvements in the precision and number of observations, discrepancies between key cosmological…
We present a Bayesian machine learning architecture that combines a physically motivated parametrization and an analytic error model for the likelihood with a deep generative model providing a powerful data-driven prior for complex signals.…
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…
Model-independent bounds on the Hubble constant $H_0$ are important to shed light on cosmological tensions. We work out a model-independent analysis based on the sum rule, which is applied to late- and early-time data catalogs to determine…
The Hubble tension refers to the discrepancy in the value of the Hubble constant $H_0$ inferred from the cosmic microwave background observations, assuming the concordance $\Lambda$CDM model of the Universe, and that from the distance…
Meta learning is a promising solution to few-shot learning problems. However, existing meta learning methods are restricted to the scenarios where training and application tasks share the same out-put structure. To obtain a meta model…
The unprecedented number of gravitational lenses expected from new-generation facilities such as the ESA Euclid telescope and the Vera Rubin Observatory makes it crucial to rethink our classical approach to lens-modelling. In this paper, we…
The Boltzmann equation, a fundamental equation in kinetic theory, serves as a bridge between microscopic particle dynamics and macroscopic continuum mechanics. However, deriving closed macroscopic moment systems from the Boltzmann equation…
The current cosmological probes have provided a fantastic confirmation of the standard $\Lambda$ Cold Dark Matter cosmological model, that has been constrained with unprecedented accuracy. However, with the increase of the experimental…
A power-law density model, i.e., $\rho(r) \propto r^{-\gamma'}$ has been commonly employed in strong gravitational lensing studies, including the so-called time-delay technique used to infer the Hubble constant $H_0$. However, since the…
The Hubble tension arises from different observations between the late-time and early Universe. We explore a new model with dark fluid, called the exponential Acoustic Dark Energy (eADE) model, to relieve the Hubble tension. The eADE model…
Brane world models have shown to be promising to understand the late cosmic acceleration, in particular because such acceleration can be naturally derived, mimicking the dark energy behaviour just with a five dimensional geometry. In this…
Multi-task learning (MTL) has emerged as a promising approach for deploying deep learning models in real-life applications. Recent studies have proposed optimization-based learning paradigms to establish task-shared representations in MTL.…
Large language models (LLMs) increasingly help people solve problems, from debugging code to repairing machinery. This process requires generating plausible hypotheses from partial descriptions, then updating them as more information…