English

Large-scale dark matter simulations

Cosmology and Nongalactic Astrophysics 2022-02-14 v1 Astrophysics of Galaxies

Abstract

We review the field of collisionless numerical simulations for the large-scale structure of the Universe. We start by providing the main set of equations solved by these simulations and their connection with General Relativity. We then recap the relevant numerical approaches: discretization of the phase-space distribution (focusing on N-body but including alternatives, e.g., Lagrangian submanifold and Schr\"odinger-Poisson) and the respective techniques for their time evolution and force calculation (Direct summation, mesh techniques, and hierarchical tree methods). We pay attention to the creation of initial conditions and the connection with Lagrangian Perturbation Theory. We then discuss the possible alternatives in terms of the micro-physical properties of dark matter (e.g., neutralinos, warm dark matter, QCD axions, Bose-Einstein condensates, and primordial black holes), and extensions to account for multiple fluids (baryons and neutrinos), primordial non-Gaussianity and modified gravity. We continue by discussing challenges involved in achieving highly accurate predictions. A key aspect of cosmological simulations is the connection to cosmological observables, we discuss various techniques in this regard: structure finding, galaxy formation and baryonic modelling, the creation of emulators and light-cones, and the role of machine learning. We finalise with a recount of state-of-the-art large-scale simulations and conclude with an outlook for the next decade.

Keywords

Cite

@article{arxiv.2112.05165,
  title  = {Large-scale dark matter simulations},
  author = {Raul E. Angulo and Oliver Hahn},
  journal= {arXiv preprint arXiv:2112.05165},
  year   = {2022}
}

Comments

171 pages, 30 figures, 1018 references. Review article (in press) for 'Living Reviews in Computational Astrophysics'. The article will be updated regularly, thus, comments and suggestions will be very welcome

R2 v1 2026-06-24T08:11:23.734Z