Using dust to constrain dark matter models

Adam J. Ussing, Robert Adriel Mostoghiu Paun, Darren Croton, Celine Boehm, Alan Duffy, Chris Power

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we use hydrodynamic zoom-in simulations of Milky Way-type haloes to explore using dust as an observational tracer to discriminate between cold and warm dark matter (WDM) universes. Comparing a cold and 3.5 keV WDM particle model, we tune the efficiency of galaxy formation in our simulations using a variable supernova rate to create Milky Way systems with similar satellite galaxy populations while keeping all other simulation parameters the same. Cold dark matter (CDM), having more substructure, requires a higher supernova efficiency than WDM to achieve the same satellite galaxy number. These different supernova efficiencies create different dust distributions around their host galaxies, which we generate by post-processing the simulation output with the POWDERDAY codebase. Analysing the resulting dust in each simulation, we find ∼4.5 times more dust in our CDM Milky Way haloes compared with WDM. The distribution of dust out to R200c is then explored, revealing that the WDM simulations are noticeably less concentrated than their CDM counterparts, although differences in substructure complicate the comparison. Our results indicate that dust is a possible unique probe to test theories of dark matter.

Original languageEnglish
Pages (from-to)2622-2632
Number of pages11
JournalMonthly Notices of the Royal Astronomical Society
Volume534
Issue number3
Early online date14 Oct 2024
DOIs
Publication statusPublished - Nov 2024

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