On the statistical theory of self-gravitating collisionless dark matter flow
Zhijie Xu

TL;DR
This paper develops a statistical theory for collisionless, self-gravitating dark matter flow, deriving analytical models for velocity, density, and potential correlations across different scales, and compares them with N-body simulations.
Contribution
It introduces a comprehensive statistical framework for dark matter flow, incorporating scale-dependent behaviors and kinematic relations, which advances understanding beyond previous models.
Findings
Velocity correlation approaches 1/2 at small scales
Transverse velocity correlation decays exponentially with scale
Small-scale longitudinal structure function follows a 1/4 power law
Abstract
Dark matter, if exists, accounts for five times as much as the ordinary baryonic matter. Compared to hydrodynamic turbulence, the flow of dark matter might possess the widest presence in our universe. This paper presents a statistical theory for the flow of dark matter that is compared with N-body simulations. By contrast to hydrodynamics of normal fluids, dark matter flow is self-gravitating, long-range, and collisionless with a scale dependent flow behavior. The peculiar velocity field is of constant divergence nature on small scale and irrotational on large scale. The statistical measures, i.e. correlation, structure, dispersion, and spectrum functions are modeled on both small and large scales, respectively. Kinematic relations between statistical measures are fully developed for incompressible, constant divergence, and irrotational flow. Incompressible and constant divergence flow…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCosmology and Gravitation Theories · Galaxies: Formation, Evolution, Phenomena · Statistical Mechanics and Entropy
