CosmicGrowth Simulations---Cosmological simulations for structure growth studies

TL;DR

The paper introduces a comprehensive set of high-resolution cosmological simulations based on ${ m f ext{Λ}}$CDM and alternative models, providing a valuable resource for studying structure formation and evolution in the universe.

Contribution

It presents a large, diverse suite of high-resolution simulations with various cosmological parameters, including ${ m f ext{Λ}}$CDM, scale-free, and XCDM models, for detailed structure growth analysis.

Findings

Simulations include up to 29 billion particles for high resolution.

Generated data supports studies of nonlinear clustering and structure evolution.

Provides a database for comparing different cosmological models with observations.

Abstract

I present a large set of high resolution simulations, called CosmicGrowth Simulations, which were generated with either 8.6 billion or 29 billion particles. As the nominal cosmological model that can match nearly all observations on cosmological scales, I have adopted a flat Cold Dark Matter (CDM) model with a cosmological constant $\Lambda$ (${\Lambda}$CDM). The model parameters have been taken either from the latest result of the WMAP satellite (WMAP ${\Lambda}$CDM) or from the first year's result of the Planck satellite (Planck ${\Lambda}$CDM). Six simulations are produced in the ${\Lambda}$CDM models with two in the Planck model and the others in the WMAP model. In order for studying the nonlinear evolution of the clustering, four simulations were also produced with $8.6$ billion particles for the scale-free models of an initial power spectrum $P(k)\propto k^n$ with $n=0$,$-1$,$-1.5$ or $-2.0$. Furthermore, two radical CDM models (XCDM) are simulated with 8.6 billion particles each. Since the XCDM have some of the model parameters distinct from those of the ${\Lambda}$CDM models, they must be unable to match the observations, but are very useful for studying how the clustering properties depend on the model parameters. The Friends-of-Friends (FoF) halos were identified for each snapshot and subhalos were produced by the Hierarchical Branch Tracing (HBT) algorithm. These simulations form a powerful database to study the growth and evolution of the cosmic structures both in theories and in observations.