Nonparametric reconstruction of the dark energy equation of state

被引:120
作者
Holsclaw, Tracy [1 ]
Alam, Ujjaini [2 ]
Sanso, Bruno [1 ]
Lee, Herbert [1 ]
Heitmann, Katrin [2 ]
Habib, Salman [2 ]
Higdon, David [2 ]
机构
[1] Univ Calif Santa Cruz, Dept Appl Math & Stat, Santa Cruz, CA 95064 USA
[2] Los Alamos Natl Lab, Los Alamos, NM 87545 USA
来源
PHYSICAL REVIEW D | 2010年 / 82卷 / 10期
关键词
SUPERNOVA; CONSTRAINTS; REDSHIFT; UNIVERSE; COSMOLOGY; EXPANSION; HISTORY; MODELS; PROBE;
D O I
10.1103/PhysRevD.82.103502
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues that can lead to a more fundamental understanding. One way to view this characterization is the improved determination of the redshift-dependence of the dark energy equation of state parameter, w(z). To do this requires a robust and bias-free method for reconstructing w(z) from data that does not rely on restrictive expansion schemes or assumed functional forms for w(z). We present a new nonparametric reconstruction method that solves for w(z) as a statistical inverse problem, based on a Gaussian process representation. This method reliably captures nontrivial behavior of w(z) and provides controlled error bounds. We demonstrate the power of the method on different sets of simulated supernova data; the approach can be easily extended to include diverse cosmological probes.
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页数:16
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