Exploring Parameter Constraints on Quintessential Dark Energy: the Inverse Power Law Model

TL;DR

This paper uses simulated future dark energy data to analyze how well an inverse power law quintessence model's parameters can be constrained, highlighting the potential to distinguish it from a cosmological constant with upcoming experiments.

Contribution

It applies MCMC analysis to IPL quintessence models using DETF simulated data, comparing constraints with standard dark energy parameterizations and assessing future experiment capabilities.

Findings

Stage 4 data could exclude a cosmological constant at >3 sigma if the IPL model is correct.

The constraining power on IPL parameters is similar to that on w0-wa parameters.

Simulated data demonstrates the potential to differentiate between dark energy models.

Abstract

We report on the results of a Markov Chain Monte Carlo (MCMC) analysis of an inverse power law (IPL) quintessence model using the Dark Energy Task Force (DETF) simulated data sets as a representation of future dark energy experiments. We generate simulated data sets for a Lambda-CDM background cosmology as well as a case where the dark energy is provided by a specific IPL fiducial model and present our results in the form of likelihood contours generated by these two background cosmologies. We find that the relative constraining power of the various DETF data sets on the IPL model parameters is broadly equivalent to the DETF results for the w_{0}-w_{a} parameterization of dark energy. Finally, we gauge the power of DETF "Stage 4" data by demonstrating a specific IPL model which, if realized in the universe, would allow Stage 4 data to exclude a cosmological constant at better than the 3-sigma level.