Bayesian 3d velocity field reconstruction with VIRBIuS

I describe a new Bayesian based algorithm to infer the full three dimensional velocity field from observed distances and spectroscopic galaxy catalogues. In addition to the velocity field itself, the algorithm reconstructs true distances, some cosmological parameters and specific non-linearities in the velocity field. The algorithm takes care of selection effects, miscalibration issues and can be easily extended to handle direct fitting of, e.g., the inverse Tully-Fisher relation. I first describe the algorithm in details alongside its performances. This algorithm is implemented in the VIRBIuS (VelocIty Reconstruction using Bayesian Inference Software) software package. I then test it on different mock distance catalogues with a varying complexity of observational issues. The model proved to give robust measurement of velocities for mock catalogues of 3,000 galaxies. I expect the core of the algorithm to scale to tens of thousands galaxies. It holds the promises of giving a better handle on future large and deep distance surveys for which individual errors on distance would impede velocity field inference.Comment: 28 pages, 13 figures, accepted by MNRA

Reconstructing the gravitational field of the local universe

Tests of gravity at the galaxy scale are in their infancy. As a first step to systematically uncovering the gravitational significance of galaxies, we map three fundamental gravitational variables -- the Newtonian potential, acceleration and curvature -- over the galaxy environments of the local universe to a distance of approximately 200 Mpc. Our method combines the contributions from galaxies in an all-sky redshift survey, halos from an N-body simulation hosting low-luminosity objects, and linear and quasi-linear modes of the density field. We use the ranges of these variables to determine the extent to which galaxies expand the scope of generic tests of gravity and are capable of constraining specific classes of model for which they have special significance. Finally, we investigate the improvements afforded by upcoming galaxy surveys.Comment: 12 pages, 4 figures; revised to match MNRAS accepted versio

Precision constrained simulation of the Local Universe

We use the formalism of constrained Gaussian random field to compute a precise large scale simulation of the 60 Mpc/h volume of our Local Universe. We derive the constraints from the reconstructed peculiar velocities of the 2MASS Redshift Survey. We obtain a correlation of 0.97 between the log-density field of the dark matter distribution of the simulation and the log-density of observed galaxies of the Local Universe. We achieve a good comparison of the simulated velocity field to the observed velocity field obtained from the galaxy distances of the NBG-3k. At the end, we compare the two-point correlation function of both the 2MRS galaxies and of the dark matter particles of the simulation. We conclude that this method is a very promising technique of exploring the dynamics and the particularities the Universe in our neighbourhood.Comment: 8 pages, 5 figures, accepted by MNRA

Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data

We perform an analysis of the three-dimensional cosmic matter density field traced by galaxies of the SDSS-III/BOSS galaxy sample. The systematic-free nature of this analysis is confirmed by two elements: the successful cross-correlation with the gravitational lensing observations derived from Planck 2018 data and the absence of bias at scales $k \simeq 10^{-3}-10^{-2}h$ Mpc$^{-1}$ in the a posteriori power spectrum of recovered initial conditions. Our analysis builds upon our algorithm for Bayesian Origin Reconstruction from Galaxies (BORG) and uses a physical model of cosmic structure formation to infer physically meaningful cosmic structures and their corresponding dynamics from deep galaxy observations. Our approach accounts for redshift-space distortions and light-cone effects inherent to deep observations. We also apply detailed corrections to account for known and unknown foreground contaminations, selection effects and galaxy biases. We obtain maps of residual, so far unexplained, systematic effects in the spectroscopic data of SDSS-III/BOSS. Our results show that unbiased and physically plausible models of the cosmic large scale structure can be obtained from present and next-generation galaxy surveys

Lifting weak lensing degeneracies with a field-based likelihood

We present a field-based approach to the analysis of cosmic shear data to infer jointly cosmological parameters and the dark matter distribution. This forward modelling approach samples the cosmological parameters and the initial matter fluctuations, using a physical gravity model to link the primordial fluctuations to the non-linear matter distribution. Cosmological parameters are sampled and updated consistently through the forward model, varying (1) the initial matter power spectrum, (2) the geometry through the distance-redshift relationship, and (3) the growth of structure and light-cone effects. Our approach extracts more information from the data than methods based on two-point statistics. We find that this field-based approach lifts the strong degeneracy between the cosmological matter density, Ωm, and the fluctuation amplitude, σ8, providing tight constraints on these parameters from weak lensing data alone. In the simulated four-bin tomographic experiment we consider, the field-based likelihood yields marginal uncertainties on σ8 and Ωm that are, respectively, a factor of 3 and 5 smaller than those from a two-point power spectrum analysis applied to the same underlying data

How Sensitive is the CMB to a Single Lens?

We study the imprints of a single lens, that breaks statistical isotropy, on the CMB and calculate the signal to noise ratio (S/N) for its detection. We emphasize the role of non-Gaussianities induced by LCDM weak lensing in this calculation and show that typically the S/N is much smaller than expected. In particular we find that the hypothesis that a void (texture) is responsible for the WMAP cold spot can barely (cannot) be tested via weak lensing of the CMB.Comment: Accepted for publication in JCAP, 24 pages, 5 figure