# Current Constraints on Anisotropic and Isotropic Dark Energy Models

## TL;DR

This study employs Gaussian processes and MCMC methods to constrain parameters of various dark energy models using Hubble parameter data, comparing their fits and estimating the deceleration-acceleration transition redshift.

## Contribution

It introduces a combined Gaussian process and MCMC approach to analyze multiple dark energy models with recent Hubble data, including Bianchi type I and curved FRW spacetimes.

## Key findings

- Bianchi type I model slightly outperforms non-flat FRW in data fitting.
- The analysis estimates the deceleration-acceleration transition redshift.
- Results are consistent with Planck 2015 and WMAP data.

## Abstract

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 measurements of the Hubble parameter $H(z)$ in the redshifts intermediate $0.07\leqslant z \leqslant 2.36$. Moreover, we use these models to estimate the redshift of the deceleration-acceleration transition. We consider two Gaussian priors for current value of the Hubble constant i.e $H_{0}=73\pm1.74 (68\pm 2.8)$ km/s/Mpc to investigate the effect of the assumed $H_{0}$ on our parameters estimations. For statistical analysis we use NUTS sampler which is an extension of Hamiltonian Monte Carlo algorithm to generate MCMC chains for parameters of dark energy models. To compare the considered cosmologies, we perform Akaike information criterion (AIC) and Bayes factor ($\Psi$). In general, when we compared our results with 9 years WMAP as well as Planck 2015 Collaboration, we found that Bianchi type I model is slightly fits better to the observational Hubble data with respect to the non-flat FRW model.