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A Comparative Study of Dark Energy Constraints from Current Observational Data

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arxiv 1109.3172 v2 pith:HX5SUZ4B submitted 2011-09-14 astro-ph.CO hep-ph

A Comparative Study of Dark Energy Constraints from Current Observational Data

classification astro-ph.CO hep-ph
keywords datadarkenergyconstraintsanalysiscurrentflux-averaginghubble
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We examine how dark energy constraints from current observational data depend on the analysis methods used: the analysis of Type Ia supernovae (SNe Ia), and that of galaxy clustering data. We generalize the flux-averaging analysis method of SNe Ia to allow correlated errors of SNe Ia, in order to reduce the systematic bias due to weak lensing of SNe Ia. We find that flux-averaging leads to larger errors on dark energy and cosmological parameters if only SN Ia data are used. When SN Ia data (the latest compilation by the SNLS team) are combined with WMAP 7 year results (in terms of our Gaussian fits to the probability distributions of the CMB shift parameters), the latest Hubble constant (H_0) measurement using the Hubble Space Telescope (HST), and gamma ray burst (GRB) data, flux-averaging of SNe Ia increases the concordance with other data, and leads to significantly tighter constraints on the dark energy density at z=1, and the cosmic curvature \Omega_k. The galaxy clustering measurements of H(z=0.35)r_s(z_d) and r_s(z_d)/D_A(z=0.35) (where H(z) is the Hubble parameter, D_A(z) is the angular diameter distance, and r_s(z_d) is the sound horizon at the drag epoch) by Chuang & Wang (2011) are consistent with SN Ia data, given the same pirors (CMB+H_0+GRB), and lead to significantly improved dark energy constraints when combined. Current data are fully consistent with a cosmological constant and a flat universe.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Model-Independent Analysis of Type Ia Supernova Datasets and Implications for Dark Energy

    astro-ph.CO 2026-04 unverdicted novelty 5.0

    Apparent dynamical dark energy signals from SNe Ia with DESI data are consistent with LambdaCDM when accounting for dataset-specific Omega_m inconsistencies rather than requiring evolving dark energy.