Optimizing Observational Strategy for Future Fgas Constraints

TL;DR

This paper explores how to optimize the redshift distribution of galaxy clusters observed via the Sunyaev-Zeldovich effect to improve constraints on dark energy parameters using future X-ray follow-up data from Planck, XMM-Newton, and Chandra.

Contribution

It determines the optimal redshift distribution of galaxy clusters for dark energy constraints and quantifies the expected improvement from future observations.

Findings

Optimal redshift distribution is non-trivial for standard dark energy models.

Upcoming data can improve the dark energy figure-of-merit by at least a factor two.

Combines Markov Chain Monte Carlo and Fisher Matrix analyses for predictions.

Abstract

The Planck cluster catalog is expected to contain of order a thousand galaxy clusters, both newly discovered and previously known, detected through the Sunyaev-Zeldovich effect over the redshift range 0 < z < 1. Follow-up X-ray observations of a dynamically relaxed sub-sample of newly discovered Planck clusters will improve constraints on the dark energy equation-of-state found through measurement of the cluster gas mass fraction fgas. In view of follow-up campaigns with XMM-Newton and Chandra, we determine the optimal redshift distribution of a cluster sample to most tightly constrain the dark energy equation of state. The distribution is non-trivial even for the standard w0-wa parameterization. We then determine how much the combination of expected data from the Planck satellite and fgas data will be able to constrain the dark energy equation-of-state. Our analysis employs a Markov Chain Monte Carlo method as well as a Fisher Matrix analysis. We find that these upcoming data will be able to improve the figure-of-merit by at least a factor two.