Morphology of dark matter haloes beyond triaxiality

TL;DR

This paper uses Minkowski Functionals to analyze dark matter halo morphology, revealing sensitivity to internal substructures and offering a promising statistical tool for improving spatial modeling in cosmology.

Contribution

It introduces Minkowski Functionals as a novel way to characterize halo morphology beyond simple shapes, accounting for substructures and internal features.

Findings

MFs differentiate between smooth and substructured haloes

Sensitivity of MFs to inner and outer density slopes

Potential of MFs to enhance dark matter spatial modeling

Abstract

The morphology of haloes inform about both cosmological and galaxy formation models. We use the Minkowski Functionals (MFs) to characterize the actual morphology of haloes, only partially captured by smooth density profile, going beyond the spherical or ellipsoidal symmetry. We employ semi-analytical haloes with NFW and $\alpha\beta\gamma$-profile and spherical or ellipsoidal shape to obtain a clear interpretation of MFs as function of inner and outer slope, concentration and sphericity parameters. We use the same models to mimic the density profile of $N$-body haloes, showing that their MFs clearly differ as sensitive to internal substructures. This highlights the benefit of MFs at the halo scales as promising statistics to improve the spatial modeling of dark matter, crucial for future lensing, Sunyaev-Zel'dovich, and X-ray mass maps as well as dark matter detection based on high-accuracy data.