Reconstructing thawing quintessence with multiple datasets

Lima, Nelson A., Liddle, Andrew R., Sahlen, Martin and Parkinson, David (2016) Reconstructing thawing quintessence with multiple datasets. Physical Review D, 93 6: . doi:10.1103/PhysRevD.93.063506

Author Lima, Nelson A.
Liddle, Andrew R.
Sahlen, Martin
Parkinson, David
Title Reconstructing thawing quintessence with multiple datasets
Journal name Physical Review D   Check publisher's open access policy
ISSN 2470-0010
Publication date 2016-03-09
Year available 2016
Sub-type Article (original research)
DOI 10.1103/PhysRevD.93.063506
Open Access Status Not Open Access
Volume 93
Issue 6
Total pages 9
Place of publication College Park, MD, United States
Publisher American Physical Society
Collection year 2017
Language eng
Abstract In this work we model the quintessence potential in a Taylor series expansion, up to second order, around the present-day value of the scalar field. The field is evolved in a thawing regime assuming zero initial velocity. We use the latest data from the Planck satellite, baryonic acoustic oscillations observations from the Sloan Digital Sky Survey, and supernova luminosity distance information from Union2.1 to constrain our models parameters, and also include perturbation growth data from the WiggleZ, BOSS, and 6dF surveys. The supernova data provide the strongest individual constraint on the potential parameters. We show that the growth data performance is competitive with the other datasets in constraining the dark energy parameters we introduce. We also conclude that the combined constraints we obtain for our model parameters, when compared to previous works of nearly a decade ago, have shown only modest improvement, even with new growth of structure data added to previously existent types of data.
Keyword Thawing quintessence
Taylor series expansion
Scalar field
Supernova data
Dark energy parameters
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
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