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E Pluribus Unum: Cosmological Analysis of Heterogenous Supernova Ia Datasets

  • Author(s): Rubin, David Arnold
  • Advisor(s): Perlmutter, Saul
  • et al.

This dissertation chronicles the development of the "Union" SN Ia analyses. These analyses address the challenges of supernova cosmology with uniform treatment of light-curve fitting, selection cuts, and outlier rejection. They were the first analyses to propagate systematic uncertainties into a covariance matrix, allowing constraints including systematics to be computed for any cosmological model. To minimize unintentional biases towards the concordance cosmology, each analysis was developed with the cosmology hidden ("blinded"). With each Union compilation version, we combine with BAO and CMB constraints to compute the then-best constraints on dark energy.

Chapter 2 provides the basic analysis outline that remains in place for subsequent compilations. Using the resulting compilation of 307 SNe (after cuts), we combine with BAO and CMB data and find that the equation of state parameter w is constrained to be -0.969^{+0.059}_{-0.063} (statistical uncertainties only) ^{+0.086}_{-0.091} (with systematics) for a flat universe with constant w. For non-constant w, no real constraints (σ_w ~1) are possible above redshift 0.5.

Chapter 3 follows our application of the Union compilation to a range of dynamical dark energy models. We find that many classes of physical models are indistinguishable from LambdaCDM with the current level of data.

In Chapter 4, we present an update of the Union compilation framework, with improved light-curve fitting and an improved treatment of systematic uncertainties. This new compilation, now consisting of 557 supernovae, gives constraints of w = -0.997^{+0.050}_{-0.054} (statistical) ^{+0.077}_{-0.082} (with systematics) when combined with BAO and CMB data.

Chapter 5 outlines supernova discoveries from the HST Cluster Supernova Survey, with 14 cosmologically useful high-redshift SNe passing Union selection cuts. We present the photometry of the undersampled IR images, accomplished by directly modeling the pixels as observed. The photometry quality approaches photon-limited statistics. We also update the Union compilation to remove the effect of host-galaxy environment on corrected supernova distances. Using our updated compilation of 580 SNe, with BAO, CMB, and H_0 measurements, we find a constraint on the equation of state parameter of w = -1.008^{+0.050}_{-0.054} (statistical) or -1.013^{+0.068}_{-0.073} (with systematics).

Chapter 6 presents the analysis of a SN discovered in an SCP search of GOODS that did not have a firm redshift at the time of discovery. An archival WFC3 IR spectrum enabled us to get the redshift of the likely host galaxy. With this redshift in hand, we used a novel PCA-like classification to confirm the supernova as a Ia with 92\% confidence. At z=1.713, this was until recently the highest-redshift SN Ia with spectroscopic confirmation, and it remains the highest one with a precision color measurement. Although limited by our sample size of one, we see no evidence of population evolution.

Finally, Chapter 7 concludes with proposed Bayesian improvements that will yield even better cosmological constraints.

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