Cosmography: Supernovae Union2, Baryon Acoustic Oscillation, Observational Hubble Data and Gamma Ray Bursts
Lixin Xu, Yuting Wang

TL;DR
This paper employs a cosmographic approach to analyze cosmic observational data, constraining key parameters without relying on specific gravity or dark energy models, thus providing a model-independent insight into the universe's kinematics.
Contribution
It introduces a model-independent cosmographic analysis using multiple observational datasets and constrains cosmographic parameters with improved precision via MCMC methods.
Findings
Cosmographic parameters are constrained with $1\sigma$ uncertainties.
Results are consistent with flat $\Lambda$CDM for $q_0$ and $j_0$.
The snap parameter $s_0$ shows deviation from $\Lambda$CDM predictions.
Abstract
In this paper, a parametrization describing the kinematical state of the universe via cosmographic approach is considered, where the minimum input is the assumption of the cosmological principle, i.e. the Friedmann-Robertson-Walker metric. A distinguished feature is that the result does not depend on any gravity theory and dark energy models. As a result, a series of cosmographic parameters (deceleration parameter , jerk parameter and snap parameter ) are constrained from the cosmic observations which include type Ia supernovae (SN) Union2, the Baryon Acoustic Oscillation (BAO), the observational Hubble data (OHD), the high redshift Gamma ray bursts (GRBs). By using Markov Chain Monte Carlo (MCMC) method, we find the best fit values of cosmographic parameters in regions: , ,…
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