The Annals of Applied Statistics

Inference for the dark energy equation of state using Type IA supernova data

Christopher Genovese, Peter Freeman, Larry Wasserman, Robert Nichol, and Christopher Miller

Full-text: Open access

Abstract

The surprising discovery of an accelerating universe led cosmologists to posit the existence of “dark energy”—a mysterious energy field that permeates the universe. Understanding dark energy has become the central problem of modern cosmology. After describing the scientific background in depth, we formulate the task as a nonlinear inverse problem that expresses the comoving distance function in terms of the dark-energy equation of state. We present two classes of methods for making sharp statistical inferences about the equation of state from observations of Type Ia Supernovae (SNe). First, we derive a technique for testing hypotheses about the equation of state that requires no assumptions about its form and can distinguish among competing theories. Second, we present a framework for computing parametric and nonparametric estimators of the equation of state, with an associated assessment of uncertainty. Using our approach, we evaluate the strength of statistical evidence for various competing models of dark energy. Consistent with current studies, we find that with the available Type Ia SNe data, it is not possible to distinguish statistically among popular dark-energy models, and that, in particular, there is no support in the data for rejecting a cosmological constant. With much more supernova data likely to be available in coming years (e.g., from the DOE/NASA Joint Dark Energy Mission), we address the more interesting question of whether future data sets will have sufficient resolution to distinguish among competing theories.

Article information

Source
Ann. Appl. Stat., Volume 3, Number 1 (2009), 144-178.

Dates
First available in Project Euclid: 16 April 2009

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1239888366

Digital Object Identifier
doi:10.1214/08-AOAS229

Mathematical Reviews number (MathSciNet)
MR2668703

Zentralblatt MATH identifier
1161.62086

Keywords
Dark energy nonlinear inverse problems nonparametric inference

Citation

Genovese, Christopher; Freeman, Peter; Wasserman, Larry; Nichol, Robert; Miller, Christopher. Inference for the dark energy equation of state using Type IA supernova data. Ann. Appl. Stat. 3 (2009), no. 1, 144--178. doi:10.1214/08-AOAS229. https://projecteuclid.org/euclid.aoas/1239888366


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