EDGE: two routes to dark matter core formation in ultra-faint dwarfs

Matthew D. A. Orkney, Justin I. Read, Martin P. Rey, Imran Nasim, Andrew Pontzen, Oscar Agertz, Stacy Y. Kim, Maxime Delorme, Walter Dehnen

Research output: Contribution to journalArticlepeer-review

38 Citations (SciVal)

Abstract

In the standard Lambda cold dark matter paradigm, pure dark matter simulations predict dwarf galaxies should inhabit dark matter haloes with a centrally diverging density 'cusp'. This is in conflict with observations that typically favour a constant density 'core'. We investigate this 'cusp-core problem' in 'ultra-faint' dwarf galaxies simulated as part of the 'Engineering Dwarfs at Galaxy formation's Edge' project. We find, similarly to previous work, that gravitational potential fluctuations within the central region of the simulated dwarfs kinematically heat the dark matter particles, lowering the dwarfs' central dark matter density. However, these fluctuations are not exclusively caused by gas inflow/outflow, but also by impulsive heating from minor mergers. We use the genetic modification approach on one of our dwarf's initial conditions to show how a delayed assembly history leads to more late minor mergers and, correspondingly, more dark matter heating. This provides a mechanism by which even ultra-faint dwarfs (M* < 105 M), in which star formation was fully quenched at high redshift, can have their central dark matter density lowered over time. In contrast, we find that late major mergers can regenerate a central dark matter cusp, if the merging galaxy had sufficiently little star formation. The combination of these effects leads us to predict significant stochasticity in the central dark matter density slopes of the smallest dwarfs, driven by their unique star formation and mass assembly histories....
Original languageEnglish
Pages (from-to)3509–3522
Number of pages14
JournalMonthly Notices of the Royal Astronomical Society
Volume504
Issue number3
Early online date21 Apr 2021
DOIs
Publication statusPublished - 31 Jul 2021

Data Availability Statement

Data available upon request.

Funding

The author acknowledges the UK Research and Innovation (UKRI) Science and Technology Facilities Council (STFC) for support (grant ST/R505134/1). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 818085 GMGalaxies. AP was further supported by the Royal Society. OA and MPR acknowledge support from the Knut and Alice Wallenberg Foundation and the Swedish Research Council (grants 2014-5791 and 2019-04659). MD acknowledges support by ERC-Syg 810218 WHOLE SUN. This work was performed using the Distributed Research utilising Advanced Computing (DiRAC) Data Intensive service at Leicester, operated by the University of Leicester IT Services, which forms part of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The equipment was funded by Business, Energy & Industrial Strategy (BEIS) capital funding via STFC capital grants ST/K000373/1 and ST/R002363/1 and STFC DiRAC Operations grant ST/R001014/1. DiRAC is part of the National e-Infrastructure. We thank the anonymous referee for their review and comments.

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