42 citations · 128 across the 7 of their papers we have counts for
7 papers
A method to extract the redshift distortions beta parameter in configuration space from minimal cosmological assumptions
Domenico Tocchini-Valentini, Michael Barnard, Charles L. Bennett +1
We present a method to extract the redshift-space distortions beta parameter in configuration space with a minimal set of cosmological assumptions. We show that a novel combination…
Exploring Parameter Constraints on Quintessential Dark Energy: the Inverse Power Law Model
Mark Yashar, Brandon Bozek, Augusta Abrahamse +2
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…
A measure of the impact of future dark energy experiments based on discriminating power among quintessence models
Michael Barnard, Augusta Abrahamse, Andreas Albrecht +2
We evaluate the ability of future data sets to discriminate among different quintessence dark energy models. This approach gives an alternative measure for assessing the impact of…
Exploring Parameter Constraints on Quintessential Dark Energy: The Exponential Model
Brandon Bozek, Augusta Abrahamse, Andreas Albrecht +1
We present an analysis of a scalar field model of dark energy with an exponential potential using the Dark Energy Task Force (DETF) simulated data models. Using Markov Chain Monte…
Exploring Parameter Constraints on Quintessential Dark Energy: the Pseudo-Nambu Goldstone Boson Model
Augusta Abrahamse, Andreas Albrecht, Michael Barnard +1
We analyze the constraining power of future dark energy experiments for Pseudo-Nambu Goldstone Boson (PNGB) quintessence. Following the Dark Energy Task Force methodology, we forec…
Exploring Parameter Constraints on Quintessential Dark Energy: the Albrecht-Skordis model
Michael Barnard, Augusta Abrahamse, Andreas Albrecht +2
We consider the effect of future dark energy experiments on ``Albrecht-Skordis'' (AS) models of scalar field dark energy using the Monte-Carlo Markov chain method. We deal with the…