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Model-independent constraints on dark energy and modified gravity with the SKA

Zhao, Gong-Bo and Bacon, David and Maartens, Roy and Santos, Mario and Raccanelli, Alvise (2015) Model-independent constraints on dark energy and modified gravity with the SKA. In: Advancing Astrophysics with the Square Kilometre Array. Proceedings of Science. Vol.215. SISSA , Trieste, Italy, Art. No. 165. ISBN 9781909204706.

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Employing a nonparametric approach of the principal component analysis (PCA), we forecast the future constraint on the equation of state w(z) of dark energy, and on the effective Newton constant µ(k; z), which parameterise the effect of modified gravity, using the planned SKA HI galaxy survey. Combining with the simulated data of Planck and Dark Energy Survey (DES), we find that SKA Phase 1 (SKA1) and SKA Phase 2 (SKA2) can well constrain 3 and 5 eigenmodes of w(z) respectively. The errors of the best measured modes can be reduced to 0.04 and 0.023 for SKA1 and SKA2 respectively, making it possible to probe dark energy dynamics. On the other hand, SKA1 and SKA2 can constrain 7 and 20 eigenmodes of µ(k; z) respectively within 10% sensitivity level. Furthermore, 2 and 7 modes can be constrained within sub percent level using SKA1 and SKA2 respectively. This is a significant improvement compared to the combined datasets without SKA.

Item Type:Book Section
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Santos, Mario0000-0003-3892-3073
Additional Information:© 2015 owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-ShareAlike. Published on: 2015 May 29. GBZ is supported by Strategic Priority Research Program “The Emergence of Cosmological Structures” of the Chinese Academy of Sciences, Grant No. XDB09000000, by the 1000 Young Talents program in China, and by the 973 Program grant No. 2013CB837900, NSFC grant No. 11261140641, and CAS grant No. KJZD-EW-T01. All numeric calculations were performed on the SCIAMA2 supercomputer at University of Portsmouth. RM and MS are supported by the South African SKA Project and the National Research Foundation. DB and RM are supported by the UK Science & Technology Facilities Council (grant No. ST/K0090X/1).
Funding AgencyGrant Number
Chinese Academy of SciencesXDB09000000
1000 Young Talents ProgramUNSPECIFIED
973 Program2013CB837900
National Natural Science Foundation of China11261140641
Chinese Academy of SciencesKJZD-EW-T01
Square Kilometre Array (SKA)UNSPECIFIED
National Research Foundation (South Africa)UNSPECIFIED
Science and Technology Facilities Council (STFC)ST/K0090X/1
Series Name:Proceedings of Science
Record Number:CaltechAUTHORS:20180821-145413879
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:88993
Deposited By: Tony Diaz
Deposited On:21 Aug 2018 22:51
Last Modified:09 Mar 2020 13:19

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