Model-independent estimation of the cosmography parameters using cosmic chronometers

TL;DR

This paper uses cosmic chronometer data to estimate cosmography parameters in a model-independent way via Gaussian processes, addressing systematic uncertainties and avoiding model bias.

Contribution

It introduces a model-independent Gaussian process method for cosmography parameter estimation from cosmic chronometers, considering systematic uncertainties.

Findings

Cosmic chronometer data constrains Hubble parameters at various redshifts.

Gaussian process analysis provides unbiased cosmography parameters.

Systematic uncertainties impact the precision of the results.

Abstract

Measurement of the universe expansion rate through the cosmic chronometers proves to be a novel approach to understanding cosmic history. Although it provides a direct determination of the Hubble parameters at different redshifts, it suffers from underlying systematic uncertainties. In this work, we analyze the recent cosmic chronometer data with and without systematic uncertainties and investigate how they affect the results. We perform our analysis in both model-dependent and independent methods to avoid any possible model bias. In the model-dependent approach, we consider the $\Lambda$CDM, wCDM and CPL models. On the Other hand, since the Gaussian process provides a unique tool to study data including a non-diagonal covariance matrix, our model-independent analysis is based on the Gaussian process.