Browsing by Author "Alam, Ujjaini"

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Case for dynamical dark energy revisited
(2011-07-06) Alam, Ujjaini; Sahni, Varun; Starobinsky, A. A.
We investigate the behaviour of dark energy using the recently released supernova data of Riess et al., 2004 and a model independent parameterization for dark energy (DE). We ﬁnd that, if no priors are imposed on Ω0m and h, DE which evolves with time provides a better ﬁt to the SNe data than ΛCDM. This is also true if we include results from the WMAP CMB data. From a joint analysis of SNe+CMB, the best-ﬁt DE model has w0 < ∼ − 1 at the present epoch and the transition from deceleration to acceleration occurs at zT = 0.39±0.03. However, DE evolution becomes weaker if the ΛCDM based CMB results Ω0m = 0.27 ± 0.04, h = 0.71 ± 0.06 are incorporated in the analysis. In this case, zT = 0.57±0.07. Our results also show that the extent of DE evolution is sensitive to the manner in which the supernova data is sampled.
Confronting braneworld cosmology with supernova data and baryon oscillations
(2006-03-18) Alam, Ujjaini; Sahni, Varun
Braneworld cosmology has several attractive and distinctive features. For instance the eﬀective equation of state in braneworld models can be both quintessence-like (w0 ≥ −1) as well as phantom like (w0 ≤ −1). Models with w0 ≥ −1 (w0 ≤ −1) are referred to as Brane 2 (Brane 1) and correspond to complementary embeddings of the brane in the bulk. (The equation of state in Brane 1 can successfully cross the ‘phantom divide’ at w = −1.) In this paper we compare the predictions of braneworld models to two recently released supernova data sets: the ‘Gold’ data (Riess et al., 2004) and the data from the Supernova Legacy Survey (SNLS) (Astier et al., 2005). We also incorporate the recent discovery of the baryon acoustic peak in the Sloan Digital Sky Survey (Eisenstein et al., 2005) into our analysis. Our main results are that braneworld models satisfy both sets of SNe data. Brane 1 (with w0 ≤ −1) shows very good agreement with data for values of the matter density bounded from below: Ω0m > ∼ 0.25 (Gold) and Ω0m > ∼ 0.2 (SNLS). On the other hand Brane 2 (with w0 ≥ −1) shows excellent agreement with data for values of the matter density which are bounded from above: Ω0m < ∼ 0.45 (Gold) and Ω0m < ∼ 0.35 (SNLS). The DGP model is excluded at 3σ by SNLS and at 1σ by the Gold dataset. Braneworld models with future ‘quiescent’ singularities (at which the Hubble parameter and the matter density remain ﬁnite but higher derivatives of the expansion factor diverge) are excluded by both datasets.
Reconstructing cosmological matter perturbations using standard candles and rulers
(2008-01-31) Alam, Ujjaini; Sahni, Varun; Starobinsky, A. A.
For a large class of dark energy (DE) models, for which the eﬀective gravitational constant is a constant and there is no direct exchange of energy between DE and dark matter (DM), knowledge of the expansion history suﬃces to reconstruct the growth factor of linearized density perturbations in the non-relativistic matter component on scales much smaller than the Hubble distance. In this paper we develop a nonparametric method for extracting information about the perturbative growth factor from data pertaining to the luminosity or angular size distances. A comparison of the reconstructed density contrast with observations of large scale structure and gravitational lensing can help distinguish DE models such as the cosmological constant and quintessence from models based on modiﬁed gravity theories as well as models in which DE and DM are either uniﬁed, or interact directly. We show that for current SNe data, the linear growth factor at z = 0.3 can be constrained to 5%, and the linear growth rate to 6%. With future SNe data, such as expected from the JDEM mission, we may be able to constrain the growth factor to 2−3% and the growth rate to 3−4% at z = 0.3 with this unbiased, model-independent reconstruction method. For future BAO data which would deliver measurements of both the angular diameter distance and Hubble parameter, it should be possible to constrain the growth factor at z = 2.5 to 9%. These constraints grow tighter with the errors on the datasets. With a large quantity of data expected in the next few years, this method can emerge as a competitive tool for distinguishing between diﬀerent models of dark energy.
Smoothing supernova data to reconstruct the expansion history of the universe
(2006-01-10) Shaﬁeloo, Arman; Alam, Ujjaini; Sahni, Varun
We 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.