Universal Density Profile for Cosmic Voids

We present a simple empirical function for the average density profile of cosmic voids, identified via the watershed technique in $\Lambda$CDM N-body simulations. This function is universal across void size and redshift, accurately describing a large radial range of scales around void centers with only two free parameters. In analogy to halo density profiles, these parameters describe the scale radius and the central density of voids. While we initially start with a more general four-parameter model, we find two of its parameters to be redundant, as they follow linear trends with the scale radius in two distinct regimes of the void sample, separated by its compensation scale. Assuming linear theory, we derive an analytic formula for the velocity profile of voids and find an excellent agreement with the numerical data as well. In our companion paper [Sutter et al., Mon. Not. R. Astron. Soc. 442, 462 (2014)] the presented density profile is shown to be universal even across tracer type, properly describing voids defined in halo and galaxy distributions of varying sparsity, allowing us to relate various void populations by simple rescalings. This provides a powerful framework to match theory and simulations with observational data, opening up promising perspectives to constrain competing models of cosmology and gravity.Comment: 5 pages, 3 figures. Matches PRL published version after minor correction

Using hybrid GPU/CPU kernel splitting to accelerate spherical convolutions

We present a general method for accelerating by more than an order of magnitude the convolution of pixelated functions on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space component and a compact spherical harmonic space component. These components can then be convolved in parallel using an inexpensive commodity GPU and a CPU. We provide models for the computational cost of both real-space and Fourier space convolutions and an estimate for the approximation error. Using these models we can determine the optimum split that minimizes the wall clock time for the convolution while satisfying the desired error bounds. We apply this technique to the problem of simulating a cosmic microwave background (CMB) anisotropy sky map at the resolution typical of the high resolution maps produced by the Planck mission. For the main Planck CMB science channels we achieve a speedup of over a factor of ten, assuming an acceptable fractional rms error of order 1.e-5 in the power spectrum of the output map.Comment: 9 pages, 11 figures, 1 table, accepted by Astronomy & Computing w/ minor revisions. arXiv admin note: substantial text overlap with arXiv:1211.355

Modeling cosmic void statistics

Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void two-point statistics in redshift space, by examining voids identified via the watershed transform in state-of-the-art $\Lambda$CDM n-body simulations and mock galaxy catalogs. The simple and universal characteristics that emerge from these statistics indicate the self-similarity of large-scale structure and suggest cosmic voids to be among the most pristine objects to consider for future studies on the nature of dark energy, dark matter and modified gravity.Comment: to appear as proceedings of the IAU Symposium 308 "The Zeldovich Universe: Genesis and Growth of the Cosmic Web", 23-28 June 2014, Tallinn, Estoni

On the observability of coupled dark energy with cosmic voids

Taking N-body simulations with volumes and particle densities tuned to match the SDSS DR7 spectroscopic main sample, we assess the ability of current void catalogs (e.g., Sutter et al. 2012b) to distinguish a model of coupled dark matter-dark energy from {\Lambda}CDM cosmology using properties of cosmic voids. Identifying voids with the VIDE toolkit, we find no statistically significant differences in the ellipticities, but find that coupling produces a population of significantly larger voids, possibly explaining the recent result of Tavasoli et al. (2013). In addition, we use the universal density profile of Hamaus et al. (2014) to quantify the relationship between coupling and density profile shape, finding that the coupling produces broader, shallower, undercompensated profiles for large voids by thinning the walls between adjacent medium-scale voids. We find that these differences are potentially measurable with existing void catalogs once effects from survey geometries and peculiar velocities are taken into account.Comment: 5 pages, 4 figures, moderate revision and extended discussion from referee comments, MNRAS letters accepte

A response to arXiv:1310.2791: A self-consistent public catalogue of voids and superclusters in the SDSS Data Release 7 galaxy surveys

Recently, Nadathur & Hotchkiss (2013) submitted a paper discussing a new cosmic void catalog. This paper includes claims about the void catalog described in Sutter et al. (2012). In this note, we respond to those claims, clarify some discrepancies between the text of Sutter et al. (2012) and the most recent version of the catalog, and provide some comments on the differences between our catalog and that of Nadathur & Hotchkiss (2013). All updates and documentation for our catalog are available at http://www.cosmicvoids.net.Comment: 3 pages, 1 figure, public catalog available at http://www.cosmicvoids.ne

Dark matter voids in the SDSS galaxy survey

What do we know about voids in the dark matter distribution given the Sloan Digital Sky Survey (SDSS) and assuming the $\Lambda\mathrm{CDM}$ model? Recent application of the Bayesian inference algorithm BORG to the SDSS Data Release 7 main galaxy sample has generated detailed Eulerian and Lagrangian representations of the large-scale structure as well as the possibility to accurately quantify corresponding uncertainties. Building upon these results, we present constrained catalogs of voids in the Sloan volume, aiming at a physical representation of dark matter underdensities and at the alleviation of the problems due to sparsity and biasing on galaxy void catalogs. To do so, we generate data-constrained reconstructions of the presently observed large-scale structure using a fully non-linear gravitational model. We then find and analyze void candidates using the VIDE toolkit. Our methodology therefore predicts the properties of voids based on fusing prior information from simulations and data constraints. For usual void statistics (number function, ellipticity distribution and radial density profile), all the results obtained are in agreement with dark matter simulations. Our dark matter void candidates probe a deeper void hierarchy than voids directly based on the observed galaxies alone. The use of our catalogs therefore opens the way to high-precision void cosmology at the level of the dark matter field. We will make the void catalogs used in this work available at http://www.cosmicvoids.net.Comment: 15 pages, 6 figures, matches JCAP published version, void catalogs publicly available at http://www.cosmicvoids.ne

First measurement of gravitational lensing by cosmic voids in SDSS

We report the first measurement of the diminutive lensing signal arising from matter underdensities associated with cosmic voids. While undetectable individually, by stacking the weak gravitational shear estimates around 901 voids detected in SDSS DR7 by Sutter et al. (2012a), we find substantial evidence for a depression of the lensing signal compared to the cosmic mean. This depression is most pronounced at the void radius, in agreement with analytical models of void matter profiles. Even with the largest void sample and imaging survey available today, we cannot put useful constraints on the radial dark-matter void profile. We invite independent investigations of our findings by releasing data and analysis code to the public at https://github.com/pmelchior/void-lensingComment: 6 pages, 5 figures, as accepted by MNRA