An Improved Method to Measure the Cosmic Curvature
In this paper, we propose an improved model-independent method to constrain the cosmic curvature by combining the most recent Hubble parameter H(z) and supernovae Ia (SNe Ia) data. Based on the H(z) data, we first use the model-independent smoothing technique, Gaussian processes, to construct a dist...
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Published in | The Astrophysical journal Vol. 838; no. 2; pp. 160 - 168 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Philadelphia
The American Astronomical Society
01.04.2017
IOP Publishing |
Subjects | |
Online Access | Get full text |
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Summary: | In this paper, we propose an improved model-independent method to constrain the cosmic curvature by combining the most recent Hubble parameter H(z) and supernovae Ia (SNe Ia) data. Based on the H(z) data, we first use the model-independent smoothing technique, Gaussian processes, to construct a distance modulus H(z), which is susceptible to the cosmic curvature parameter k. In contrary to previous studies, the light-curve-fitting parameters, which account for the distance estimation of SN ( SN(z)), are set free to investigate whether k has a dependence on them. By comparing H(z) to SN(z), we put limits on k. Our results confirm that k is independent of the SN light-curve parameters. Moreover, we show that the measured k is in good agreement with zero cosmic curvature, implying that there is no significant deviation from a flat universe at the current observational data level. We also test the influence of different H(z) samples and different Hubble constant H0 values, finding that different H(z) samples do not have a significant impact on the constraints. However, different H0 priors can affect the constraints of k to some degree. The prior of H0 = 73.24 1.74 km s−1 Mpc−1 gives a value of k, a little bit above the 1 confidence level away from 0, but H0 = 69.6 0.7 km s−1 Mpc−1 gives it below 1 . |
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Bibliography: | Galaxies and Cosmology AAS01693 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0004-637X 1538-4357 |
DOI: | 10.3847/1538-4357/aa674b |