Universal void density profiles from simulation and SDSS

We discuss the universality and self-similarity of void density profiles, for voids in realistic mock luminous red galaxy (LRG) catalogues from the Jubilee simulation, as well as in void catalogues constructed from the SDSS LRG and Main Galaxy samples. Voids are identified using a modified version of the ZOBOV watershed transform algorithm, with additional selection cuts. We find that voids in simulation are self-similar, meaning that their average rescaled profile does not depend on the void size, or -- within the range of the simulated catalogue -- on the redshift. Comparison of the profiles obtained from simulated and real voids shows an excellent match. The profiles of real voids also show a universal behaviour over a wide range of galaxy luminosities, number densities and redshifts. This points to a fundamental property of the voids found by the watershed algorithm, which can be exploited in future studies of voids.

The Good, the Bad and the Ugly: Statistical quality assessment of SZ detections

We examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence with which the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribution (SED). Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the considered range of frequencies. We first first consider likelihood analysis, which half way between supervised and unsupervised methods. Next, we investigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on Artificial Neural Networks. We illustrate the approach and results using catalogues from various surveys. i.e., X-Rays (MCXC), optical (SDSS) and millimetric (Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very good agreement with each others, although the supervised neural network-based classification shows better performances allowing the best separation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detected by the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the Planck SZ catalogue. Our method could easily be applied to catalogues from future large survey such as SRG/eROSITA and Euclid.

Self-similarity and universality of void density profiles in simulation and SDSS data

The stacked density profile of cosmic voids in the galaxy distribution provides an important tool for the use of voids for precision cosmology. We study the density profiles of voids identified using the ZOBOV watershed transform algorithm in realistic mock luminous red galaxy (LRG) catalogues from the Jubilee simulation, as well as in void catalogues constructed from the SDSS LRG and Main Galaxy samples. We compare different methods for reconstructing density profiles scaled by the void radius and show that the most commonly used method based on counts in shells and simple averaging is statistically flawed as it underestimates the density in void interiors. We provide two alternative methods that do not suffer from this effect; one based on Voronoi tessellations is also easily able to account from artefacts due to finite survey boundaries and so is more suitable when comparing simulation data to observation. Using this method we show that voids in simulation are exactly self-similar, meaning that their average rescaled profile does not depend on the void size. Within the range of our simulation we also find no redshift dependence of the profile. Comparison of the profiles obtained from simulated and real voids shows an excellent match. The profiles of real voids also show a universal behaviour over a wide range of galaxy luminosities, number densities and redshifts. This points to a fundamental property of the voids found by the watershed algorithm, which can be exploited in future studies of voids.

The Jubilee ISW Project I: simulated ISW and weak lensing maps and initial power spectra results

We present initial results from the Jubilee ISW project, which models the expected LambdaCDM Integrated Sachs-Wolfe (ISW) effect in the Jubilee simulation. The simulation volume is (6 Gpc/h)^3, allowing power on very large-scales to be incorporated into the calculation. Haloes are resolved down to a mass of 1.5x10^12 M_sun/h, which allows us to derive a catalogue of mock Luminous Red Galaxies (LRGs) for cross-correlation analysis with the ISW signal. We find the ISW effect observed on a projected sky to grow stronger at late times with the evolution of the ISW power spectrum matching expectations from linear theory. Maps of the gravitational lensing effect, including the convergence and deflection fields, are calculated using the same potential as for the ISW. We calculate the redshift dependence of the ISW-LRG cross-correlation signal for a full sky survey with no noise considerations. For l < 30, the signal is strongest for lower redshift bins (z ~ 0.2 to 0.5), whereas for l > 30 the signal is best observed with surveys covering z ~ 0.6-1.0.

A phenomenological model of galaxy clusters

We present a simple model to describe the dark matter density, the gas density, and the gas temperature profiles of galaxy clusters. Analytical expressions for these quantities are given in terms of only five free parameters with a clear physical meaning: the mass M of the dark matter halo (or the characteristic temperature T_0), the characteristic scale radius a, the cooling radius in units of a (0<alpha<1), the central temperature in units of T_0 (0<t<1), and the asymptotic baryon fraction in units of the cosmic value (f~1). It is shown that our model is able to reproduce the three-dimensional density and temperature profiles inferred from X-ray observations of real clusters within a 20 per cent accuracy over most of the radial range. Some possible applications are briefly discussed.