Related papers: Gaussian Process Estimation of Transition Redshift
Simulation based inference has seen increasing interest in the past few years as a promising approach to model the non linear scales of galaxy clustering. The common approach using Gaussian process is to train an emulator over the…
Assuming only a homogeneous and isotropic universe and using both the 'Gold' Supernova Type Ia sample of Riess et al. and the results from the Supernova Legacy Survey, we calculate the Bayesian evidence of a range of different…
In this paper we present an alternative explanation to the acceleration of the universe and the dark energy problems in terms of the Friedmann Thermodynamics. This model has the capability of making definite predictions in-line with the…
The results from the Supernova Cosmology Project indicate a relation between cosmic distance and redshift that corresponds to an accelerating Universe, and, as a consequence, the presence of an energy component with negative pressure. This…
Cosmographic approach, a Taylor expansion of the Hubble function, has been used as a model-independent method to investigate the evolution of the universe in the presence of cosmological data. Apart from possible technical problems like the…
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…
We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has…
We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…
We propose a non-parametric method of smoothing supernova data over redshift using a Gaussian kernel in order to reconstruct important cosmological quantities including H(z) and w(z) in a model independent manner. This method is shown to be…
Context. Explaining the accelerated expansion of the Universe is one of the fundamental challenges in physics today. Cosmography provides information about the evolution of the universe derived from measured distances, assuming only that…
Recently, using Bayesian Machine Learning, a deviation from the cold dark matter model on cosmological scales has been put forward. Such model might replace a proposed non-gravitational interaction between dark energy and dark matter, and…
Radio observations of the neutral hydrogen signal from the Cosmic Dawn and Epoch of Reionisation have helped to provide constraints on the properties of the first stars and galaxies. Since this global 21-cm cosmological signal from the…
We use Gaussian processes in combination with MCMC method to place constraints on cosmological parameters of three dark energy models including flat and curved FRW and Bianchi type I spacetimes. To do so, we use recently compiled 36…
Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…
We further investigate slowing down of acceleration of the universe scenario for five parametrizations of the equation of state of dark energy using four sets of supernovae data. In a maximal probability analysis we also use the baryon…
We study the orientation dependence of the reconstructed deceleration parameter as a function of redshift. We use the Union 2 and Loss datasets, by using the well known preferred axis discussed in the literature, finding the best fit…
The accelerated cosmic expansion could be due to dark energy within general relativity (GR), or modified gravity. It is of interest to differentiate between them, by using both the expansion history and the growth history. In the…
We present and test a new method for the reconstruction of cosmological initial conditions from a full-sky galaxy catalogue. This method, called ZTRACE, is based on a self-consistent solution of the growing mode of gravitational…
The velocity distributions of stellar tracers in general exhibit weak non-Gaussianity encoding information on the orbital composition of a galaxy and the underlying potential. The standard solution for measuring non-Gaussianity involves…
With a model independent method the expansion history $H(z)$, the deceleration parameter $q(z)$ of the universe and the equation of state $w(z)$ for the dark energy are reconstructed directly from the 192 Sne Ia data points, which contain…