2013
DOI: 10.1103/physrevd.87.023520
|View full text |Cite
|
Sign up to set email alerts
|

Model independent tests of cosmic growth versus expansion

Abstract: We use Gaussian Processes to map the expansion history of the universe in a model independent manner from the Union2.1 supernovae data and then apply these reconstructed results to solve for the growth history. By comparing this to BOSS and WiggleZ large scale structure data we examine whether growth is determined wholly by expansion, with the measured gravitational growth index testing gravity without assuming a model for dark energy. A further model independent analysis looks for redshift dependent deviation… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
48
0

Year Published

2014
2014
2024
2024

Publication Types

Select...
10

Relationship

3
7

Authors

Journals

citations
Cited by 57 publications
(49 citation statements)
references
References 38 publications
1
48
0
Order By: Relevance
“…This method was firstly proposed to test both cosmology (Holsclaw et al 2010a,b) and cosmography (Shafieloo et al 2013), and then extensively applied to the derivation of the Hubble constant H 0 (Busti et al 2014), the reconstructions of the equation of state of dark energy (Seikel et al 2013) and the distance-duality relation (Zhang 2014). The advantage of Gaussian processes is, that we do not need to assume any parametrized model for H(z) while reconstructing this function from the data (Holsclaw et al 2010a,b).…”
Section: Methodsmentioning
confidence: 99%
“…This method was firstly proposed to test both cosmology (Holsclaw et al 2010a,b) and cosmography (Shafieloo et al 2013), and then extensively applied to the derivation of the Hubble constant H 0 (Busti et al 2014), the reconstructions of the equation of state of dark energy (Seikel et al 2013) and the distance-duality relation (Zhang 2014). The advantage of Gaussian processes is, that we do not need to assume any parametrized model for H(z) while reconstructing this function from the data (Holsclaw et al 2010a,b).…”
Section: Methodsmentioning
confidence: 99%
“…To combine the Pantheon SNe and the H0LiCOW strong lenses datasets, we generate a posterior sampling of the H 0 -independent quantity H 0 D L (z) from the Pantheon dataset. To do the posterior sampling in a manner independent of a cosmological model, we use GP regression (Holsclaw et al 2010a(Holsclaw et al ,b, 2011Shafieloo et al 2012Shafieloo et al , 2013. The GP regression used here is based on the GPHist code (Kirkby & Keeley 2017) first used in Joudaki et al (2018).…”
Section: Methodsmentioning
confidence: 99%
“…If σ f is consistent with zero this means there is no statistically significant evidence for deviations from the fiducial, i.e. ΛCDM cosmology (Shafieloo et al 2013;Aghamousa et al 2017). If the correlation length is very small this may mean one is fitting for noise in the data; if it is very large this may mean the data is uninformative about the expansion history.…”
Section: Gaussian Processmentioning
confidence: 99%