On the equilibrium morphology of systems drawn from spherical collapse experiments

TL;DR

This theoretical study investigates how resolution affects the shape and density profiles of self-gravitating systems formed by dissipationless collapse, revealing the conditions for convergence and the influence of initial mass distributions.

Contribution

It provides new insights into the equilibrium morphology and density profiles of collapsing systems, emphasizing the role of resolution and initial conditions.

Findings

Higher resolution leads to more oblate equilibria.

Convergence in aspect ratios requires N >= 100000 particles.

Density profiles depend on initial mass distribution slope g.

Abstract

We present a purely theoretical study of the morphological evolution of self-gravitating systems formed through the dissipationless collapse of N-point sources. We explore the effects of resolution in mass and length on the growth of triaxial structures formed by an instability triggered by an excess of radial orbits. We point out that as resolution increases, the equilibria shift, from mildly prolate, to oblate. A number of particles N ~= 100000 or larger is required for convergence of axial aspect ratios. An upper bound for the softening, e ~ 1/256, is also identified. We then study the properties of a set of equilibria formed from scale-free cold initial mass distributions, ro ~ r^-g with 0 <= g <= 2. Oblateness is enhanced for initially more peaked structures (larger values of g). We map the run of density in space and find no evidence for a power-law inner structure when g <= 3/2 down to a mass fraction <~0.1 per cent of the total. However, when 3/2 < g <= 2, the mass profile in equilibrium is well matched by a power law of index ~g out to a mass fraction ~ 10 per cent. We interpret this in terms of less-effective violent relaxation for more peaked profiles when more phase mixing takes place at the centre. We map out the velocity field of the equilibria and note that at small radii the velocity coarse-grained distribution function (DF) is Maxwellian to a very good approximation.