A data-driven approach to elucidating the nature of the dark energy , in the form of a joint analysis of a full set of cosmological parameters , utilizing all available observational data is proposed .
A parameterization of a generalized dark energy is developed with the extension of fluid perturbation theory to models which cross through an equation of state of -1 .
This parameterization is selected to be general enough to admit a wide variety of behavior , while still being physical and economical .
A Fisher matrix analysis with future high-precision CMB , cluster survey , and SNIa data suggests the parameters will probably be resolvable in the foreseeable future .
How accurately the parameters can be determined depends sensitively on the nature of the dark energy - particularly how significant of a fraction of the total energy density it has been in the past .
Parameter space will be sampled at a large number of points , with cosmological information such as CMB , power spectra , etc of each point being archived .
Thus the likelihood functions of an arbitrary set of experiments can be applied to parameter space with insignificant new computational cost , making a wide variety of analyses possible .
The resulting tool for Analysis and Resolution of Dark-sector Attributes , ARDA , will be highly versatile and adaptable .
ARDA will allow the scientific community to extract parameters with an arbitrary set of experiments and theoretical priors , test for tension between classes of observations and investigate the effectiveness of hypothetical experiments , while evolving in a data-driven manner .
A proof-of-concept prototype web-tool , The Cosmic Concordance Project , is already available .