Model independent tests of cosmic growth versus expansion

Shafieloo, Arman; Kim, Alex; Linder, Eric V.

doi:10.1103/physrevd.87.023520

Cited by 62 publications

(49 citation statements)

References 38 publications

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“…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%

Ultra-compact structure in intermediate-luminosity radio quasars: building a sample of standard cosmological rulers and improving the dark energy constraints up to z ~ 3

Cao

Zheng

Biesiada

et al. 2017

A&A

127

191

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In this paper, we present a new compiled milliarcsecond compact radio data set of 120 intermediate-luminosity quasars in the redshift range 0.46 < z < 2.76. These quasars show negligible dependence on redshifts and intrinsic luminosity, and thus represents, in the standard model of cosmology, a fixed comoving-length of standard ruler. We implement a new cosmology-independent technique to calibrate the linear size of of this standard ruler as l m = 11.03 ± 0.25 pc, which is the typical radius at which AGN

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Section: Methodsmentioning

confidence: 99%

Ultra-compact structure in intermediate-luminosity radio quasars: building a sample of standard cosmological rulers and improving the dark energy constraints up to z ~ 3

Cao

Zheng

Biesiada

et al. 2017

A&A

127

191

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“…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%

A Model-independent Determination of the Hubble Constant from Lensed Quasars and Supernovae Using Gaussian Process Regression

Liao

Shafieloo

Keeley

et al. 2019

ApJL

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116

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Strongly lensed quasar systems with time delay measurements provide "time delay distances", which are a combination of three angular diameter distances and serve as powerful tools to determine the Hubble constant H 0 . However, current results often rely on the assumption of the ΛCDM model. Here we use a model-independent method based on Gaussian process to directly constrain the value of H 0 . By using Gaussian process regression, we can generate posterior samples of unanchored supernova distances independent of any cosmological model and anchor them with strong lens systems. The combination of a supernova sample with large statistics but no sensitivity to H 0 with a strong lens sample with small statistics but H 0 sensitivity gives a precise H 0 measurement without the assumption of any cosmological model. We use four well-analyzed lensing systems from the state-of-art lensing program H0LiCOW and the Pantheon supernova compilation in our analysis. Assuming the Universe is flat, we derive the constraint H 0 = 72.2 ± 2.1 km/s/Mpc, a precision of 2.9%. Allowing for cosmic curvature with a prior of Ω k = [−0.2, 0.2], the constraint becomes H 0 = 73.0 +2.8 −3.0 km/s/Mpc.

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“…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%

Debiasing cosmic gravitational wave sirens

Keeley

Shafieloo

L’Huillier

et al. 2019

Monthly Notices of the Royal Astronomical Society

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Accurate estimation of the Hubble constant, and other cosmological parameters, from distances measured by cosmic gravitational wave sirens requires sufficient allowance for the dark energy evolution. We demonstrate how model independent statistical methods, specifically Gaussian process regression, can remove bias in the reconstruction of H(z), and can be combined model independently with supernova distances. This allows stringent tests of both H 0 and ΛCDM, and can detect unrecognized systematics. We also quantify the redshift systematic control necessary for the use of dark sirens, showing that it must approach spectroscopic precision to avoid significant bias.

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Model independent tests of cosmic growth versus expansion

Cited by 62 publications

References 38 publications

Ultra-compact structure in intermediate-luminosity radio quasars: building a sample of standard cosmological rulers and improving the dark energy constraints up to z ~ 3

Ultra-compact structure in intermediate-luminosity radio quasars: building a sample of standard cosmological rulers and improving the dark energy constraints up to z ~ 3

A Model-independent Determination of the Hubble Constant from Lensed Quasars and Supernovae Using Gaussian Process Regression

Debiasing cosmic gravitational wave sirens

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