A robust determination of halo environment in the cosmic field
Abstract
A number of methods for studying the largescale cosmic matter distribution exist in the literature. One particularly common method employed to define the cosmic web is to examine the density, velocity or potential field. Such methods are advantageous since a Hessian matrix can be constructed whose eigenvectors (and eigenvalues) indicate the principal directions (and strength) of local collapse or expansion. Technically this is achieved by diagonalizing the Hessian matrix using a fixed finite grid. The resultant largescale structure quantification is thus inherently limited by the grid's finite resolution. Here, we overcome the obstacle of finite grid resolution by introducing a new method to determine halo environment using an adaptive interpolation which is more robust to resolution than the typical "Nearest Grid Point" (NGP) method. Essentially instead of computing and diagonalizing the Hessian matrix once for the entire grid, we suggest doing so once for each halo or galaxy in question. We examine how the eigenvalues and eigenvector direction's computed using our algorithm and the NGP method converge for different grid resolutions, finding that our new method is convergent faster. Namely changes of resolution have a much smaller effect than in the NGP method. We therefore suggest this method for future use by the community.
 Publication:

New Astronomy
 Pub Date:
 October 2020
 DOI:
 10.1016/j.newast.2020.101405
 arXiv:
 arXiv:2007.08344
 Bibcode:
 2020NewA...8001405W
 Keywords:

 largescale structure of Universe;
 cosmic web;
 dark matter halo;
 simulation;
 Astrophysics  Cosmology and Nongalactic Astrophysics
 EPrint:
 Published in New Astronomy, https://doi.org/10.1016/j.newast.2020.101405