Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

© 2019 IOP Publishing Ltd and Sissa Medialab. We explore the implications of a rapid appearance of dark energy between the redshifts (z) of one and two on the expansion rate and growth of perturbations. Using both Gaussian process regression and a parametric model, we show that this is the preferred solution to the current set of low-redshift (z<3) distance measurements if H0=73 km s-1 Mpc-1 to within 1% and the high-redshift expansion history is unchanged from the ΛCDM inference by the Planck satellite. Dark energy was effectively non-existent around z=2, but its density is close to the ΛCDM model value today, with an equation of state greater than-1 at z<0.5. If sources of clustering other than matter are negligible, we show that this expansion history leads to slower growth of perturbations at z<1, compared to ΛCDM, that is measurable by upcoming surveys and can alleviate the σ8 tension between the Planck CMB temperature and low-redshift probes of the large-scale structure.

Abstract:

The disconnected part of the power spectrum covariance matrix (also known as the "Gaussian" covariance) is the dominant contribution on large scales for galaxy clustering and weak lensing datasets. The presence of a complicated sky mask causes non-trivial correlations between different Fourier/harmonic modes, which must be accurately characterized in order to obtain reliable cosmological constraints. This is particularly relevant for galaxy survey data. Unfortunately, an exact calculation of these correlations involves O(ℓmax6) operations that become computationally impractical very quickly. We present an implementation of approximate methods to estimate the Gaussian covariance matrix of power spectra involving spin-0 and spin-2 flat- and curved-sky fields, expanding on existing algorithms {developed in the context of CMB analyses}. These methods achieve an O(ℓmax3) scaling, which makes the computation of the covariance matrix as fast as the computation of the power spectrum itself. We quantify the accuracy of these methods on large-scale structure and weak lensing data, making use of a large number of Gaussian but otherwise realistic simulations. We show that, using the approximate covariance matrix, we are able to recover the true posterior distribution of cosmological parameters to high accuracy. We also quantify the shortcomings of these methods, which become unreliable on the very largest scales, as well as for covariance matrix elements involving cosmic shear B modes. The algorithms presented here are implemented in the public code NaMaster https://github.com/LSSTDESC/NaMaster.

Abstract:

We investigate the impact of the number of filaments connected to the nodes of the cosmic web on the physical properties of their galaxies using the Sloan Digital Sky Survey. We compare these measurements to the cosmological hydrodynamical simulations Horizon-(no)AGN and Simba. We find that more massive galaxies are more connected, in qualitative agreement with theoretical predictions and measurements in dark matter only simulation. The star formation activity and morphology of observed galaxies both display some dependence on the connectivity of the cosmic web at fixed stellar mass: less star forming and less rotation supported galaxies also tend to have higher connectivity. These results qualitatively hold both for observed and virtual galaxies, and can be understood given that the cosmic web is the main source of fuel for galaxy growth. The simulations show the same trends at fixed halo mass, suggesting that the geometry of filamentary infall impacts galaxy properties beyond the depth of the local potential well. Based on simulations, it is also found that AGN feedback is key in reversing the relationship between stellar mass and connectivity at fixed halo mass. Technically, connectivity is a practical observational proxy for past and present accretion (minor mergers or diffuse infall).