Lagrangian methods of cosmic web classification

Abstract

This research report uses cosmological N-body simulations to examine the the large scale mass distribution of the Universe, known as the cosmic web. The cosmic web can be classi ed into nodes, laments, sheets and voids - each with its own characteristic density and velocity elds. In this work, the author proposes a new Lagrangian cosmic web classi- cation algorithm, based on smoothed particle hydrodynamics. This scheme o ers adaptive resolution, resolves smaller substructure and obeys similar statistical properties with existing Eulerian methods. Using the new classi cation scheme, halo clustering dependence on cosmic web type is examined. The author nds halo clustering is signi cantly correlated with web type. Consequently, the mass dependence of halo clustering may be explained by the fractions of web types found for a particular halo mass. Finally, an analysis of dark matter halo spin, shape and fractional anisotropy is presented per web type to suggest avenues for future work.