2014/06/30 by David J. E. Marsh, Philip Bull, Pedro G. Ferreira +1 · 3 citations
Mathematics · Physics and Astronomy · #Astrophysics #Bayesian probability #Cosmology #Cosmology and Gravitation Theories #Dark Matter and Cosmic Phenomena #Dark energy #Galaxies: Formation, Evolution, Phenomena #Galaxy #Mathematics #Parametrization (atmospheric modeling) #Physics #Prior probability #Quantum mechanics #Quintessence #Redshift #Statistical physics #Statistics #Theoretical physics #astro-ph.CO
paper · pdf · doi:10.1103/physrevd.90.105023
published as Phys. Rev. D 90, 105023 (2014) · 5 pages, 3 figures. For the busy reader, Fig. 1 is the money plot. v2: Minor changes, matches published version. Code open source at gitorious.org/random-quintessence
openalex publication_date 2014/11/18 · arxiv created 2014/12/10 · arxiv updated 2014/12/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The archetypal theory of dark energy is quintessence: a minimally coupled scalar field with a canonical kinetic energy and potential. By studying random potentials, we show that quintessence imposes a restricted set of priors on the equation of state of dark energy. Focusing on the commonly used parametrization, w(a)\ensuremath≈w0+wa(1\ensuremath-a), we show that there is a natural scale and direction in the (w0,wa) plane that distinguishes quintessence as a general framework. We calculate the expected information gain for a given survey and show that, because of the nontrivial prior information, it is a function of more than just the figure of merit. This allows us to make a quantitative case for novel survey strategies. We show that the scale of the prior sets target observational requirements for gaining significant information. This corresponds to a figure of merit FOM\ensuremath\gtrsim200, a requirement that future galaxy redshift surveys will meet.