Novel Adaptive softening for collisionless N-body simulations: Eliminating spurious halos
Alexander Hobbs, Justin Read, Oscar Agertz, Francesca Iannuzzi, Chris, Power

TL;DR
This paper introduces NovA, an adaptive softening method for collisionless N-body simulations that reduces spurious halos and improves accuracy in modeling dark matter structures.
Contribution
NovA employs a new refinement criterion based on isotropy to minimize two-body effects while maintaining high force resolution, enhancing simulation fidelity.
Findings
NovA prevents numerical fragmentation in test simulations.
It converges faster than standard N-body methods in WDM simulations.
NovA reduces spurious small-scale halos, improving dark matter structure modeling.
Abstract
We describe a NOVel form of Adaptive softening (NovA) for collisionless -body simulations, implemented in the Ramses adaptive mesh refinement code. We introduce a refinement criterion that the particle distribution within each cell be sufficiently isotropic, as measured by its moment of inertia tensor. In this way, collapse is only refined if it occurs along all three axes, ensuring that the softening is always of order twice the largest inter-particle spacing in a cell. This more conservative force softening criterion is designed to minimise spurious two-body effects, while maintaining high force resolution in collapsed regions of the flow. We test NovA using an antisymmetric perturbed plane wave collapse (`Valinia' test) before applying it to warm dark matter (WDM) simulations. For the Valinia test, we show that -- unlike the standard -body method -- NovA produces no…
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