Constraints on the tensor-to-scalar ratio for non-power-law models

被引:15
作者
Vazquez, J. Alberto [1 ,2 ]
Bridges, M. [1 ,2 ]
Ma, Yin-Zhe [3 ,4 ]
Hobson, M. P. [2 ]
机构
[1] Kavli Inst Cosmol, Cambridge CB3 0HA, England
[2] Univ Cambridge, Cavendish Lab, Astrophys Grp, Cambridge CB3 0HE, England
[3] Univ British Columbia, Dept Phys & Astron, Vancouver, BC V6T 1Z1, Canada
[4] Univ Toronto, Canadian Inst Theoret Astrophys, Toronto, ON M5S 3H8, Canada
关键词
inflation; CMBR experiments; physics of the early universe; cosmological parameters from CMBR; HUBBLE-SPACE-TELESCOPE; COSMOLOGICAL PARAMETERS; GRAVITATIONAL-WAVES; BAYESIAN-INFERENCE; POLARIZATION; EFFICIENT; PRECISION; INFLATION; SPECTRUM; SKY;
D O I
10.1088/1475-7516/2013/08/001
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Recent cosmological observations hint at a deviation from the simple power-law form of the primordial spectrum of curvature perturbations. In this paper we show that in the presence of a tensor component, a turn-over in the initial spectrum is preferred by current observations, and hence non-power-law models ought to be considered. For instance, for a power-law parameterisation with both a tensor component and running parameter, current data show a preference for a negative running at more than 2.5 sigma C.L. As a consequence of this deviation from a power-law, constraints on the tensor-to-scalar ratio r are slightly broader. We also present constraints on the inflationary parameters for a model-independent reconstruction and the Lasenby & Doran (LD) model. In particular, the constraints on the tensor-to-scalar ratio from the LD model are: r(LD) = 0.11 +/- 0.024. In addition to current data, we show expected constraints from Planck-like and CMB-Pol sensitivity experiments by using Markov-Chain-Monte-Carlo sampling chains. For all the models, we have included the Bayesian Evidence to perform a model selection analysis. The Bayes factor, using current observations, shows a strong preference for the LD model over the standard power-law parameterisation, and provides an insight into the accuracy of differentiating models through future surveys.
引用
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页数:15
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