In this paper, we propose a new dynamical classification of the cosmic web. Each point in space is classified in one of four possible web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor (i.e. the Hessian of the gravitational potential) on a grid. The classification is based on counting the number of eigenvalues above a certain threshold, λth, at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, sheet, filament or a knot grid point. The collection of neighbouring grid points, friends of friends, of the same web type constitutes voids, sheets, filaments and knots as extended web objects. A simple dynamical consideration of the emergence of the web suggests that the threshold should not be null, as in previous implementations of the algorithm. A detailed dynamical analysis would have found different threshold values for the collapse of sheets, filaments and knots. Short of such an analysis a phenomenological approach has been opted for, looking for a single threshold to be determined by analysing numerical simulations. Our cosmic web classification has been applied and tested against a suite of large (dark matter only) cosmological N‐body simulations. In particular, the dependence of the volume and mass filling fractions on λth and on the resolution has been calculated for the four web types. We also study the percolation properties of voids and filaments. Our main findings are as follows. (i) Already at λth= 0.1 the resulting web classification reproduces the visual impression of the cosmic web. (ii) Between 0.2 ≲λth≲ 0.4, a system of percolated voids coexists with a net of interconnected filaments. This suggests a reasonable choice for λth as the parameter that defines the cosmic web. (iii) The dynamical nature of the suggested classification provides a robust framework for incorporating environmental information into galaxy formation models, and in particular to semi‐analytical models.

The cosmic web is one of the most striking features of the distribution of galaxies and dark matter on the largest scales in the Universe. It is composed of dense regions packed full of galaxies, long filamentary bridges, flattened sheets and vast low density voids. The study of the cosmic web has focused primarily on the identification of such features, and on understanding the environmental effects on galaxy formation and halo assembly. As such, a variety of different methods have been devised to classify the cosmic web -depending on the data at hand, be it numerical simulations, large sky surveys or other. In this paper we bring twelve of these methods together and apply them to the same data set in order to understand how they compare. In general these cosmic web classifiers have been designed with different cosmological goals in mind, and to study different questions. Therefore one would not a priori expect agreement between different techniques however, many of these methods do converge on the identification of specific features. In this paper we study the agreements and disparities of the different methods. For example, each method finds that knots inhabit higher density regions than filaments, etc. and that voids have the lowest densities. For a given web environment, we find substantial overlap in the density range assigned by each web classification scheme. We also compare classifications on a halo-by-halo basis; for example, we find that 9 of 12 methods classify around a third of group-mass haloes (i.e. M halo ∼ 10 13.5 h −1 M ⊙ ) as being in filaments. Lastly, so that any future cosmic web classification scheme can be compared to the 12 methods used here, we have made all the data used in this paper public.

A new approach for the classification of the cosmic web is presented. In extension of the previous work of Hahn et al. (2007) and Forero-Romero et al. (2009) the new algorithm is based on the analysis of the velocity shear tensor rather than the gravitational tidal tensor. The procedure consists of the construction of the the shear tensor at each (grid) point in space and the evaluation of its three eigenvectors. A given point is classified to be either a void, sheet, filament or a knot according to the number of eigenvalues above a certain threshold, 0, 1, 2, or 3 respectively. The threshold is treated as a free parameter that defines the web. The algorithm has been applied to a dark matter only, high resolution simulation of a box of side-length 64$h^{-1}$Mpc and N = $1024^3$ particles with the framework of the WMAP5/LCDM model. The resulting velocity based cosmic web resolves structures down to <0.1$h^{-1}$Mpc scales, as opposed to the ~1$h^{-1}$Mpc scale of the tidal based web. The under-dense regions are made of extended voids bisected by planar sheets, whose density is also below the mean. The over-dense regions are vastly dominated by the linear filaments and knots. The resolution achieved by the velocity based cosmic web provides a platform for studying the formation of halos and galaxies within the framework of the cosmic web.Comment: 8 pages, 4 Figures, MNRAS Accepted 2012 June 19. Received 2012 May 10; in original form 2011 August 2

We present the online MultiDark Database -a Virtual Observatory-oriented, relational database for hosting various cosmological simulations. The data is accessible via an SQL (Structured Query Language) query interface, which also allows users to directly pose scientific questions, as shown in a number of examples in this paper. Further examples for the usage of the database are given in its extensive online documentation. The database is based on the same technology as the Millennium Database, a fact that will greatly facilitate the usage of both suites of cosmological simulations. The first release of the MultiDark Database hosts two 8.6 billion particle cosmological N-body simulations: the Bolshoi (250 h −1 Mpc simulation box, 1 h −1 kpc resolution) and MultiDark Run1 simulation (MDR1, or BigBolshoi, 1000 h −1 Mpc simulation box, 7 h −1 kpc resolution). The extraction methods for halos/subhalos from the raw simulation data, and how this data is structured in the database are explained in this paper. With the first data release, users get full access to halo/subhalo catalogs, various profiles of the halos at redshifts z = 0-15, and raw dark matter data for one time-step of the Bolshoi and four time-steps of the MultiDark simulation. Later releases will also include galaxy mock catalogs and additional merger trees for both simulations as well as new large volume simulations with high resolution. This project is further proof of the viability to store and present complex data using relational database technology. We encourage other simulators to publish their results in a similar manner.