VIDE: The Void IDentification and Examination toolkit

Abstract

We present vide, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and N -body simulations, characterizing their properties, and providing a platform for more detailed analysis. At its core, vide uses a substantially enhanced version of zobov (Neyinck 2008) to calculate a Voronoi tessellation for estimating the density field and a performing a watershed transform to construct voids. Additionally, vide provides significant functionality for both pre-and post-processing: for example, vide can work with volume-or magnitude-limited galaxy samples with arbitrary survey geometries, or dark matter particles or halo catalogs in a variety of common formats. It can also randomly subsample inputs and includes a Halo Occupation Distribution model for constructing mock galaxy populations. vide uses the watershed levels to place voids in a hierarchical tree, outputs a summary of void properties in plain ASCII, and provides a Python API to perform many analysis tasks, such as loading and manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles. While centered around ZOBOV, the toolkit is designed to be as modular as possible and accommodate other void finders. vide has been in development for several years and has already been used to produce a wealth of results, which we summarize in this work to highlight the capabilities of the toolkit. vide is publicly available at http://bitbucket.org/cosmicvoids/vide public and http://www.cosmicvoids.net.

Imprint off(R)gravity on nonlinear structure formation

“…Several works have been focusing on measuring the void abundance and its deviation from the expectations of the standard ΛCDM model in the context of various non-standard cosmologies (e.g. [28,82,89,90,95]). In particular, for the case of f (R) gravity, some of these works [82,89,90] have shown that there is an excess of large voids compared to ΛCDM, and that the excess is larger for larger values of the f R0 parameter.…”

Testing the imprint of nonstandard cosmologies on void profiles using Monte Carlo random walks

“…In fact previous studies of f (R) imprints on void profiles have not investigated the effect of the void finder itself. As we already mentioned void finders such as [37,38] tend to identify voids without ridge for R v ≥ 17Mpc.h −1 (see [65]). Because the fifth force enhances the void ridge, it might be interesting to test the imprint of f (R) for different types of void profiles (for a fixed R v ).…”

“…This last constraint is not mandatory for certain void finders (e.g. [38]), particularly for large voids, and therefore we distinguish this additional condition as a +1 condition.…”

“…Void finders based on the watershed concept (e.g. [37,38]) also need to have an estimate of the density around each particle (e.g. Voronoi Tessellation) to define zones that have a density minimum and thus voids.…”

“…[30][31][32][33][34][35][36]). With cosmological observations, ZOBOV/VIDE [37,38] has also been quite successful in identifying density minima using Voronoi tessellation, leading to voids with interesting properties and that are not necessary spherical. In this case it is however more challenging to link the initial under-dense patches of matter to the identified void [14].…”