Search arXivSearch

arXiv · 1609.04081

Hubble trouble or Hubble bubble?

Abstract

The recent analysis of low-redshift supernovae (SN) has increased the apparent tension between the value of $H_0$ estimated from low and high redshift observations such as the cosmic microwave background (CMB) radiation. At the same time other observations have provided evidence of the existence of local radial inhomogeneities extending in different directions up to a redshift of about $0.07$. About $40\%$ of the Cepheids used for SN calibration are directly affected because are located along the directions of these inhomogeneities. We derive a new simple formula relating directly the luminosity distance to the monopole of the density contrast, which does not involve any metric perturbation. We then use it to develop a new inversion method to reconstruct the monopole of the density field from the deviations of the redshift uncorrected observed luminosity distance respect to the $ΛCDM$ prediction based on cosmological parameters obtained from large scale observations. The inversion method confirms the existence of inhomogeneities whose effects were not previously taken into account because the $2M++$ density field maps used to obtain the peculiar velocity for redshift correction were for $z\leq 0.06$, which is not a sufficiently large scale to detect the presence of inhomogeneities extending up to $z=0.07$. The inhomogeneity does not affect the high redshift luminosity distance because the volume averaged density contrast tends to zero asymptotically, making the value of $H_0^{CMB}$ obtained from CMB observations insensitive to any local structure. The inversion method can provide a unique tool to reconstruct the density field at high redshift where only SN data is available, and in particular to normalize correctly the density field respect to the average large scale density of the Universe.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Antonio Enea Romano. 2018-05-12. Hubble trouble or Hubble bubble?. https://doi.org/10.1142/s021827181850102x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Constraints on the Thomson optical depth to the CMB from the Lyman-$α$ forest

We present the first constraints on the electron optical depth to reionization, $τ_{\mathrm{e}}$, from the Lyman-$α$ forest alone for physically motivated reionization models that match the reionization's end-point, $z_{\rm{end}}$, required by the same astrophysical probe, and for symmetric reionization models with fixed duration, $Δz$, commonly adopted in CMB reionization analyses. Compared to traditional estimates from the latter, the Lyman-$α$ forest traces the ionization state of the IGM through its coupling with the thermal state. We find an explicit mapping between the two solving the chemistry and temperature evolution equations for hydrogen and helium. Our results yield $τ_{\mathrm{e}}$=$0.040^{+0.042}_{-0.018}$ (95\% C.L) and $τ_{\mathrm{e}}$=$0.041^{+0.028}_{-0.017}$ for reionization models with $z_{\rm{end}}$ and $Δz$-fixed, respectively. With mock Lyman-$α$ forest data that mimics the precision of future larger quasar sample datasets, we would potentially obtain tighter $τ_{\mathrm{e}}$ constraints, paving the way for CMB-independent constraints on the epoch of reionization from a large-scale structure probe.

astro-ph.CO

Non-minimally Coupled Running Curvaton for DESI-motivated Dynamical Dark Energy

Recent DESI BAO data combined with CMB and supernova measurements suggest a dynamical dark energy that can cross the phantom divide. We show that introducing a non-minimal coupling $ξχ^2R$ to the running-curvaton framework allows a single field to drive early-universe curvature perturbations and late-time phantom-crossing cosmic acceleration without ghost instabilities. Using MCMC background likelihoods with DESI DR2 BAO, Pantheon+ SNe, and a reduced CMB prior, we constrain the cosmological parameters: $H_0 = 67.88^{+0.53}_{-0.61}\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $Ω_m = 0.3072^{+0.0059}_{-0.0054}$, $w_0 = -0.922^{+0.055}_{-0.063}$, and $w_a = -0.205^{+0.173}_{-0.182}$. Parameter degeneracies leave the coupling constants weakly constrained, highlighting the need for full perturbation-level analysis using CMB spectra and lensing.

astro-ph.CO

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

We develop a field-level posterior for cosmological data by marginalizing over initial conditions and noise in a general forward model. While our focus is on large-scale structure data, the results generalize to any weakly non-Gaussian observable. Moreover, the construction is non-perturbative with respect to the forward model and applies equally well to perturbative calculations, simulation-based predictions, and more general effective descriptions. Expanding the FLP around its Gaussian limit, we derive a general expression for the Fisher matrix and reorganize the field-level information into contributions associated with the connected correlators of the evolved field. This makes explicit which terms are captured by likelihood analyses based on the power spectrum, the bispectrum, or finite sets of summary statistics, and which are lost under compression. We recover the standard Gaussian-covariance result for the power spectrum, show that the Gaussian bispectrum likelihood reproduces the corresponding field-level contribution, and show how cross-covariances among summaries progressively reconstruct more of the full field-level information. As an application to the BAO scale, we show how the field contains all the information required for its optimal reconstruction in the presence of noise, and identify the contributions in the FLP needed to attain this limit. We also show that the reconstruction of the initial field arises naturally as a byproduct of our approach, yielding the optimal estimate of the initial conditions given the data and the noise. Our results provide a unified framework to compare field-level and correlator-based inference, to quantify the information loss induced by compression, and to explore the role of stochasticity.

astro-ph.CO