Oliver Hahn

TL;DR: Enzo as discussed by the authors uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows, which can be run in one, two, and three dimensions, and supports a wide variety of physics, including hydrodynamics, ideal and non-ideal magnetohydrodynamic, N-body dynamics, primordial gas chemistry, optically thin radiative cooling of primordial and metal-enriched plasmas, and models for star formation and feedback in a cosmological context.

TL;DR: Enzo as mentioned in this paper uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows, which can be run in 1, 2, and 3 dimensions, and supports a wide variety of physics, including hydrodynamics, ideal and non-ideal magnetohydrodynamic, N-body dynamics, primordial gas chemistry, optically-thin radiative cooling of primordial and metal-enriched plasmas, and models for star formation and feedback.

TL;DR: In this paper, an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver is used to generate displacements and velocities following first- or second-order Lagrangian perturbation theory (2LPT).

TL;DR: In this article, the formation histories, shapes and angular momenta of dark-matter halos depend on the environment, and a classification scheme was proposed to distinguish haloes in clusters, filaments, sheets and voids in the large-scale distribution of matter.

TL;DR: In this paper, a series of high-resolution N-body simulations of the concordance cosmology is used to investigate the redshift evolution since z = 1 of the properties and alignment with the large-scale structure (LSS) of haloes in clusters, filaments, sheets and voids.