IUCAA Preprints
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Item Exploring the expanding universe and dark energy using the statefinder diagnostic(2011-07-05) Ujjaini, Alam; Sahni, Varun; Saini, Tarun Deep; et al.The coming few years are likely to witness a dramatic increase in high quality Sn data as current surveys add more high redshift supernovae to their inventory and as newer and deeper supernova experiments become operational. Given the current variety in dark energy models and the expected improvement in observational data, an accurate and versatile diagnostic of dark energy is the need of the hour. This paper examines the Statefinder diagnostic in the light of the proposed SNAP satellite which is expected to observe about 2000 supernovae per year. We show that the Statefinder is versatile enough to differentiate between dark energy models as varied as the cosmological constant on the one hand, and quintessence, the Chaplygin gas and braneworld models, on the other. Using SNAP data, the Statefinder can distinguish a cosmological constant (w = −1) from quintessence models with w > −0.9 and Chaplygin gas models with κ 6 15 at the 3σ level if the value of Ωm is known exactly. The Statefinder gives reasonable results even when the value of Ωm is known to only ∼ 20% accuracy. In this case, marginalizing over Ωm and assuming a fiducial LCDM model allows us to rule out quintessence with w > −0.85 and the Chaplygin gas with κ 6 7 (both at 3σ). These constraints can be made even tighter if we use the Statefinders in conjunction with the deceleration parameter. The Statefinder is very sensitive to the total pressure exerted by all forms of matter and radiation in the universe. It can therefore differentiate between dark energy models at moderately high redshifts of z < 10.Item Smoothing supernova data to reconstruct the expansion history of the universe(2006-01-10) Shafieloo, Arman; Alam, Ujjaini; Sahni, VarunWe propose a non-parametric method of smoothing supernova data over redshift using a Gaussian kernel in order to reconstruct important cosmological quantities including H(z) and w(z) in a model independent manner. This method is shown to be successful in discriminating between different models of dark energy when the quality of data is commensurate with that expected from the future SuperNova Acceleration Probe (SNAP). We find that the Hubble parameter is especially well-determined and useful for this purpose. The look back time of the universe may also be determined to a very high degree of accuracy ( < ∼ 0.2%) in this method. By refining the method, it is also possible to obtain reasonable bounds on the equation of state of dark energy. We explore a new diagnostic of dark energy– the ‘w-probe’– which can be calculated from the first derivative of the data. We find that this diagnostic is reconstructed extremely accurately for different reconstruction methods even if Ω0m is marginalized over. The w-probe can be used to successfully distinguish between ΛCDM and other models of dark energy to a high degree of accuracy.