The MIP Ensemble Simulation: Local Ensemble Statistics in the Cosmic Web

Abstract

We present a new technique that allows us to compute ensemble statistics on a local basis, directly relating halo properties to their local environment. This is achieved by the use of a correlated ensemble in which the Large Scale Structure is common to all realizations while having each an independent halo population. The correlated ensemble can be stacked, effectively increasing the halo number density by an arbitrary factor, thus breaking the fundamental limit in the halo number density given by the haloe mass function. This technique allows us to compute \textit{local ensemble statistics} of the matter/haloe distribution at any position in the simulation box, while removing the intrinsic stochasticity in the halo formation process and directly relating halo properties to their environment. We introduce the \textit{Multum In Parvo} (MIP) correlated ensemble simulation consisting of 220 realizations on a 32 h${}^{-1}$ Mpc box with $256^3$ particles each. This is equivalent in terms of effective volume and number of particles to a box of $\sim 193$ h${}^{-1}$ Mpc of side with $\sim 1540^3$ particles containing $\sim 5\times 10^6$ haloes with a minimum mass of $3.25\times 10^9$ h${}^{-1}$ M${}_{\odot }$. The potential of the technique presented here is illustrated by computing the local ensemble statistics of the halo ellipticity and halo shape-LSS alignment. We show that, while there are general trends in the ellipticity and alignment of haloes with their LSS, there are also significant spatial variations which has important implications for observational studies of galaxy shape and alignment.

Published in MNRAS

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Cited by in corpus (11)

• The Hierarchical Nature of the Spin Alignment of Dark Matter Haloes in Filaments
• Inverted initial conditions: exploring the growth of cosmic structure and voids
• The Void Galaxy Survey: Photometry, structure and identity of void galaxies
• Halo abundances within the cosmic web
• The SIBELIUS Project: E Pluribus Unum
• Predicted future fate of COSMOS galaxy protoclusters over 11 Gyr with constrained simulations
• Kinematic Morphology of Large-scale Structure: Evolution from Potential to Rotational Flow
• Intergalactic filaments spin
• Setting the Stage: Structures from Gaussian Random Fields
• A Machine Learning Approach to Galaxy-LSS Classification I: Imprints on Halo Merger Trees
• On the Statistical Evolution of the Large-scale Structure and the Effective Dynamics