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

Quantifying the Rarity of the Local Super-Volume

We investigate the extent to which the number of clusters of mass exceeding 1015M⊙h−1 within the local super-volume (⁠<135Mpch−1⁠) is compatible with the standard ΛCDM cosmological model. Depending on the mass estimator used, we find that the observed number N of such massive structures can vary between 0 and 5. Adopting N = 5 yields ΛCDM likelihoods as low as 2.4 × 10−3 (with σ8 = 0.81) or 3.8 × 10−5 (with σ8 = 0.74). However, at the other extreme (N = 0), the likelihood is of order unity. Thus, while potentially very powerful, this method is currently limited by systematic uncertainties in cluster mass estimates. This motivates efforts to reduce these systematics with additional observations and improved modelling

Quantifying the Rarity of the Local Super-Volume

We investigate the extent to which the number of clusters of mass exceeding 1015M⊙h−1 within the local super-volume (⁠<135Mpch−1⁠) is compatible with the standard ΛCDM cosmological model. Depending on the mass estimator used, we find that the observed number N of such massive structures can vary between 0 and 5. Adopting N = 5 yields ΛCDM likelihoods as low as 2.4 × 10−3 (with σ8 = 0.81) or 3.8 × 10−5 (with σ8 = 0.74). However, at the other extreme (N = 0), the likelihood is of order unity. Thus, while potentially very powerful, this method is currently limited by systematic uncertainties in cluster mass estimates. This motivates efforts to reduce these systematics with additional observations and improved modelling

Robust, data-driven inference in non-linear cosmostatistics

We discuss two projects in non-linear cosmostatistics applicable to very large surveys of galaxies. The first is a Bayesian reconstruction of galaxy redshifts and their number density distribution from approximate, photometric redshift data. The second focuses on cosmic voids and uses them to construct cosmic spheres that allow reconstructing the expansion history of the Universe using the Alcock-Paczynski test. In both cases we find that non-linearities enable the methods or enhance the results: non-linear gravitational evolution creates voids and our photo-z reconstruction works best in the highest density (and hence most non-linear) portions of our simulations.Comment: 14 pages, 10 figures. Talk given at "Statistical Challenges in Modern Astronomy V," held at Penn Stat

Halo based reconstruction of the cosmic mass density field

We present the implementation of a halo based method for the reconstruction of the cosmic mass density field. The method employs the mass density distribution of dark matter haloes and its environments computed from cosmological N-body simulations and convolves it with a halo catalog to reconstruct the dark matter density field determined by the distribution of haloes. We applied the method to the group catalog of Yang etal (2007) built from the SDSS Data Release 4. As result we obtain reconstructions of the cosmic mass density field that are independent on any explicit assumption of bias. We describe in detail the implementation of the method, present a detailed characterization of the reconstructed density field (mean mass density distribution, correlation function and counts in cells) and the results of the classification of large scale environments (filaments, voids, peaks and sheets) in our reconstruction. Applications of the method include morphological studies of the galaxy population on large scales and the realization of constrained simulations.Comment: Accepted for publication in MNRA

Bayesian analysis of cosmic structures

We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales below ~ 10 h^{-1} Mpc for which higher order correlations would be required to describe the matter statistics. However, we confirm as it was recently shown in the context of Ly-alpha forest tomography that the Poisson-lognormal model provides the correct two-point statistics (or power-spectrum).Comment: 11 pages, 1 figure, report for the Astrostatistics and Data Mining workshop, La Palma, Spain, 30 May - 3 June 2011, to appear in Springer Series on Astrostatistic

Reconstructing the Cosmic Velocity and Tidal Fields with Galaxy Groups Selected from the Sloan Digital Sky Survey

[abridge]Cosmic velocity and tidal fields are important for the understanding of the cosmic web and the environments of galaxies, and can also be used to constrain cosmology. In this paper, we reconstruct these two fields in SDSS volume from dark matter halos represented by galaxy groups. Detailed mock catalogues are used to test the reliability of our method against uncertainties arising from redshift distortions, survey boundaries, and false identifications of groups by our group finder. We find that both the velocity and tidal fields, smoothed on a scale of ~2Mpc/h, can be reliably reconstructed in the inner region (~66%) of the survey volume. The reconstructed tidal field is used to split the cosmic web into clusters, filaments, sheets, and voids, depending on the sign of the eigenvalues of tidal tensor. The reconstructed velocity field nicely shows how the flows are diverging from the centers of voids, and converging onto clusters, while sheets and filaments have flows that are convergent along one and two directions, respectively. We use the reconstructed velocity field and the Zel'dovich approximation to predict the mass density field in the SDSS volume as function of redshift, and find that the mass distribution closely follows the galaxy distribution even on small scales. We find a large-scale bulk flow of about 117km/s in a very large volume, equivalent to a sphere with a radius of ~170Mpc/h, which seems to be produced by the massive structures associated with the SDSS Great Wall. Finally, we discuss potential applications of our reconstruction to study the environmental effects of galaxy formation, to generate initial conditions for simulations of the local Universe, and to constrain cosmological models. The velocity, tidal and density fields in the SDSS volume, specified on a Cartesian grid with a spatial resolution of ~700kpc/h, are available from the authors upon request.Comment: 35 pages, 13 figures, accepted for publication in MNRA

The large-scale environment of thermonuclear and core-collapse supernovae

The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution of ∼3.8 Mpc, constrained by the 2M+ + galaxy survey. We limit our analysis to redshift z < 0.036, using samples of 498 thermonuclear and 782 core-collapse SNe from the Zwicky Transient Facility’s Bright Transient Survey and Census of the Local Universe catalogues. We detect clustering of SNe with high significance; the observed clustering of the two SNe populations is consistent with each other. Further, the clustering of SN hosts is consistent with that of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey DR12 spectroscopic galaxy sample in the same redshift range. Using a tidal shear classifier, we classify the LSS into voids, sheets, filaments, and knots. We find that both SNe and SDSS galaxies are predominantly found in sheets and filaments. SNe are significantly under-represented in voids and over-represented in knots compared to the volume fraction in these structures. This work opens the potential for using forthcoming wide-field deep SN surveys as a complementary LSS probe

Precise cosmological parameter estimation using CosmoRec

We use the new cosmological recombination code, CosmoRec, for parameter estimation in the context of (future) precise measurements of the CMB temperature and polarization anisotropies. We address the question of how previously neglected physical processes in the recombination model of Recfast affect the determination of key cosmological parameters, for the first time performing a model-by-model computation of the recombination problem. In particular we ask how the biases depend on different combinations of parameters, e.g. when varying the helium abundance or the effective number of neutrino species in addition to the standard six parameters. We also forecast how important the recombination corrections are for a combined Planck, ACTPol and SPTpol data analysis. Furthermore, we ask which recombination corrections are really crucial for CMB parameter estimation, and whether an approach based on a redshift-dependent correction function to Recfast is sufficient in this context.Comment: 12 pages, 7 figures, submitted to MNRA

The Milky Way's plane of satellites is consistent with LambdaCDM

Large scale structure and cosmolog