Using H(z) data as a probe of the concordance model

TL;DR

This paper demonstrates how H(z) data from cosmic chronometers and BAO can effectively test the standard cosmological model, using Gaussian Processes to reconstruct the expansion history and dark energy properties.

Contribution

It introduces a new Gaussian Processes package, GaPP, for smoothing H(z) data and estimating derivatives, enabling novel consistency tests of the LCDM model.

Findings

Current H(z) data is consistent with LCDM.

Gaussian Processes effectively reconstruct the expansion history.

Simulated data shows future H(z) observations will improve constraints.

Abstract

Direct observations of the Hubble rate, from cosmic chronometers and the radial baryon acoustic oscillation scale, can out-perform supernovae observations in understanding the expansion history, because supernovae observations need to be differentiated to extract H(z). We use existing H(z) data and smooth the data using a new Gaussian Processes package, GaPP, from which we can also estimate derivatives. The obtained Hubble rate and its derivatives are used to reconstruct the equation of state of dark energy and to perform consistency tests of the LCDM model, some of which are newly devised here. Current data is consistent with the concordance model, but is rather sparse. Future observations will provide a dramatic improvement in our ability to constrain or refute the concordance model of cosmology. We produce simulated data to illustrate how effective H(z) data will be in combination with Gaussian Processes.