Future supernovae observations as a probe of dark energy

Abstract

We study the potential impact of improved future supernovae data on our understanding of the dark energy problem. We carefully examine the relative utility of different fitting functions that can be used to parameterize the dark energy models, and provide concrete reasons why a particular choice (based on a parameterization of the equation of state) is better in almost all cases. We discuss the details of a representative sample of dark energy models and show how future supernova observations could distinguish among these. As a specific example, we consider the proposed "SNAP" satellite which is planned to observe around 2000 supernovae. We show how a SNAP-class data set taken alone would be a powerful discriminator among a family of models that would be approximated by a constant equation of state for the most recent epoch of cosmic expansion. We show how this family includes most of the dark energy models proposed so far. We then show how an independent measurement of Ωm can allow SNAP to probe the evolution of the equation of state as well, allowing further discrimination among a larger class of proposed dark energy models. We study the impact of the satellite design parameters on this method to distinguish the models and compare SNAP to alternative measurements. We establish that if we exploit the full precision of SNAP it provides a very powerful probe.

5 Dark Matter and Dark Energy

“…In practice the first few terms in either series (67), (68) is sufficient since the current Sn data is quite noisy; see [46,212,54,77,113,2] for a discussion of these issues. An example of cosmological reconstruction of the Hubble parameter from Sn data is shown in figure (9); see also [208,134].…”

Quintessential kination and thermal production of gravitinos and axinos

“…Although this model does not possess a tracker-type solution [11,39] in the allowed range of its parameters, it can produce a viable present-day cosmology in conjunction with the domination of an early KD era, for a reasonable region of initial conditions [40,41,42,43]. We then investigate the impact of KD on the thermal production of e-WIMPs, solving the relevant equations both numerically and semianalytically.…”

Direct reconstruction of the dark energy scalar-field potential

“…As discussed and noted elsewhere [8,10], the scalar-field potential reconstruction is also subject to prior assumptions on the fitting form. To avoid biases and to make statements that are not subject to assumed parametrization, it is useful to directly construct the potential from data.…”

“…Under the assumption that the dark energy is due to a single scalar field rolling down a potential, several studies have considered how future data might be used to reconstruct the potential, either based on various analytical descriptions of the luminosity distance [6], or through specific assumptions about the potential, such as a polynomial function in the scalar field [7]. It is already well established that certain parametric descriptions of the distance lead to biased estimates for the dark energy equation of state (EOS) and the potential [8,9]. While improved parametric forms of fitting functions have been suggested [10,11], it is unclear how to select an optimal approach for reconstructing the dark energy scalar-field potential from SN distances (for a review of various possibilities, see Ref.…”

“…We compare and contrast a variety of methods to reconstruct the potential and the dark energy EOS. We write the luminosity distance either as a simple polynomial expansion in redshift, or as a Padé approximation [15] (which avoids some of the known problems in the polynomial expansion when taking derivatives [8,10,16]). In addition to approximating the luminosity distance, we also explore two approximations to the EOS: w z w 0 w a 1 ÿ a [17,18] and w z w 0 ÿ ln 1 z [10].…”