Cosmic homogeneity: a spectroscopic and model-independent measurement

Gonçalves, R. S.; Carvalho, G C; Bengaly, Carlos A. P.; Carvalho, J. C.; Bernui, Armando; Alcaniz, J. S.; Maartens, Roy

doi:10.1093/mnrasl/slx202

Cited by 33 publications

(28 citation statements)

References 65 publications

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“…Although the 2σ error bars include zero for D s > 30 Mpc, the best-fit for ∆H s is only compatible with zero at 2σ confidence level for D s > 80 Mpc. This is consistent with typical results on the homogeneity scale in galaxy number counts [18,19,20,21,22,23,24,25]. Table I For the MC-boost test, consistency with the real data indicates that the CMB and LG rest-frames are not special relative to 1,000 others, and hence there is no significant evidence for a violation of statistical isotropy in the local Universe.…”

Section: A ∆Hs From the Cf3 Datasupporting

confidence: 87%

Is the local Hubble flow consistent with concordance cosmology?

Bengaly

Larena

Maartens

2019

J. Cosmol. Astropart. Phys.

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Yes. In a perturbed Friedmann model, the difference of the Hubble constants measured in two restframes is independent of the source peculiar velocity and depends only on the relative velocity of the observers, to lowest order in velocity. Therefore this difference should be zero when averaging over sufficient sources, which are at large enough distances to suppress local nonlinear inhomogeneity. We use a linear perturbative analysis to predict the Doppler effects on redshifts and distances. Since the observed redshifts encode the effect of local bulk flow due to nonlinear structure, our linear analysis is able to capture aspects of the nonlinear behaviour. Using the largest available distance compilation from CosmicFlows-3, we find that the data is consistent with simulations based on the concordance model, for sources at 20 − 150 Mpc. I. INTRODUCTIONThe flat + vacuum dark energy (Λ) + cold dark matter model (LCDM) is widely regarded as the concordance model of cosmology, providing the best available phenomenological explanation for observations of the cosmic microwave background (CMB) [1] and the large-scale structure of the Universe (e.g. [2]).The fundamental pillars of the concordance model are General Relativity and the Cosmological Principle (CP), i.e. the assumption of large-scale statistical isotropy and homogeneity. Statistical isotropy is straightforward to test directly, for example via the temperature of the CMB, but direct tests of homogeneity are more difficult (see e.g. [3,4,5]).Here we consider an indirect test of the CP via measurements of the rate of expansion H 0 , averaged in spherical shells at increasing distances. The test is affected by the observer's position, which produces an observer velocity relative to the CMB frame. The CP implies that spherically-averaged H 0 measurements should not depend on the velocities of the sources or the observer, or on the distance of the sources, provided that they are distant enough to suppress the effect of coherent bulk flows induced by local nonlinear structure. Since measurements of H 0 are plagued by systematics, we mitigate this problem by determining the difference of Hubble constants in two rest-frames, which should be consistent with zero if the CP holds [6,7,8,9].We use the latest available data from the CosmicFlows-3 (CF3) distance compilation [10], which is roughly twice the size of CF2 [11], enabling an improved test of the CP and the concordance model. We check whether the H 0 difference in the CMB and the Local Group (LG) rest-frames (hereafter CRF and LRF), is compatible with cosmological distances based on a fiducial LCDM cosmology. In addition, we test how CRF-and LRF-like boosts applied in random directions affect the Hubble flow. This enables a practical test of the isotropy of H 0 . Any significant discrepancy in these two tests could be interpreted as a potential deviation from the concordance model due to a failure of the CP. In our analysis, we do not find evidence of such discrepancy.The paper is organised as follows: §II describe...

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Section: A ∆Hs From the Cf3 Datasupporting

confidence: 87%

Is the local Hubble flow consistent with concordance cosmology?

Bengaly

Larena

Maartens

2019

J. Cosmol. Astropart. Phys.

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“…At ð64 MpcÞ 3 , samples share similar types of features but also exhibit considerable variation by eye. The large variation on these scales is expected, as the homogeneity scale of the Universe is typically accepted as ≳100 h −1 Mpc [44,45]. Some periodic artifacts can be seen in synthetic samples, however these are low density features that do not significantly affect the cosmological summary statistics shown in the following subsections.…”

Section: Resultsmentioning

confidence: 94%

Nonlinear 3D cosmic web simulation with heavy-tailed generative adversarial networks

2020

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Fast and accurate simulations of the nonlinear evolution of the cosmic density field are a major component of many cosmological analyses, but the computational time and storage required to run them can be exceedingly large. For this reason, we use generative adversarial networks (GANs) to learn a compressed representation of the 3D matter density field that is fast and easy to sample, and for the first time show that GANs are capable of generating samples at the level of accuracy of other conventional methods. Using subvolumes from a suite of GADGET-2 N-body simulations, we demonstrate that a deepconvolutional GAN can generate samples that capture both large-and small-scale features of the matter density field, as validated through a variety of n-point statistics. The use of a data scaling that preserves high-density features and a heavy-tailed latent space prior allow us to obtain state of the art results for fast 3D cosmic web generation. In particular, the mean power spectra from generated samples agree to within 5% up to k ¼ 3 and within 10% for k ≤ 5 when compared with N-body simulations, and similar accuracy is obtained for a variety of bispectra. By modeling the latent space with a heavy-tailed prior rather than a standard Gaussian, we better capture sample variance in the high-density voxel PDF and reduce errors in power spectrum and bispectrum covariance on all scales. Furthermore, we show that a conditional GAN can smoothly interpolate between samples conditioned on redshift. Deep generative models, such as the ones described in this work, provide great promise as fast, low-memory, high-fidelity forward models of large-scale structure.

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“…First we fit a model-independent polynomial to the D 2 (θ) data points calculated as described in previous sections. Then, to determine the scale of transition to homogeneity, θ H , we consider the 1%-criterium commonly adopted in the literature [8,36,37,43]: we identify the scale at which the fitted curve reach 99% of the D H 2 threshold value expected for a homogeneous distribution. For the case of a 2D (3D) Euclidean space this value is a constant, D H 2 = 2 (D H 2 = 3), while for a distribution on the 2D celestial sphere S 2 it is a function of θ [43],…”

Section: The Homogeneity Scale Criteriummentioning

confidence: 99%

“…However, despite the robustness of these studies, they used the standard cosmological model to calculate distances which, in some way, may bias the results. With this in mind, some authors [43][44][45] worked on an independent model analysis, studying the homogeneity with projected 2D data.…”

Section: Introductionmentioning

confidence: 99%