Gravitational instability with a dark matter background: Exploring the different scenarios

TL;DR

This paper investigates how a dark matter background influences gravitational instability in a two-species medium, using a hybrid quantum-classical fluid model, and compares theoretical predictions with astrophysical observations.

Contribution

It introduces a hybrid quantum-classical approach to study dark matter's impact on Jeans instability, considering nonlinear effects and comparing results with observational data.

Findings

Dark matter background affects Jeans mass based on density and velocity ratios.

Model aligns with Bok globule stability observations using dark matter parameters.

Quantum effects in dark matter can influence gravitational collapse scenarios.

Abstract

We study the Jeans-type gravitational instability for a self-gravitating medium composed of two species, baryonic (bright) and dark matter particles, using a hybrid quantum-classical fluid approach. Baryonic matter is treated classically, which is appropriate for most astrophysical environments, e.g., Bok globules, while dark matter is treated through a quantum hydrodynamic approach allowing for possible nonlinearities. These nonlinearities may arise in bosonic dark matter due to attractive or repulsive short-range self-interaction (attractive interaction being more relevant for axions) or from the Pauli exclusion principle for fermionic dark matter, e.g., massive neutrinos. This allows us to explore, in a very broad context, the impact of a dark matter background on the Jeans process for different scenarios discussed in the literature. In the simplest case, it is shown that the effect of a dark matter background on the Jeans mass depends only on the ratio of densities and velocity dispersions of baryonic and dark matter particles. Taking advantage of that, we confront the established stability criterion with Bok globule stability observations and show that the model adequately accounts for the data with dark matter parameters close to those predicted independently from numerical simulations.