Informing dark matter direct detection limits with the ARTEMIS simulations

Poole-McKenzie, Robert; Font, Andreea S.; Boxer, B.; McCarthy, Ian G.; Burdin, S.; Stafford, Sam G.; Brown, S F

doi:10.1088/1475-7516/2020/11/016

Cited by 12 publications

(9 citation statements)

References 99 publications

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“…We have also shown that including baryons (with or without DM self-interactions) in the simulations has a major effect on the local DM distribution. This agrees with the results of previous work, which compared the local DM distributions in CDM (including baryons) and DM-only halos in various high resolution cosmological simulations [37][38][39][40][41][42].…”

Section: Discussionsupporting

confidence: 92%

“…The local DM density in the SHM is assumed to be 0.3 or 0.4 GeV/cm 3 and the local velocity distribution is assumed to be a Maxwellian distribution in the Galactic rest frame, with a peak speed equal to the local circular speed, v c , usually set equal to 230 km/s, and truncated at an escape speed of 544 km/s from the Galaxy. Recent cosmological simulations of ΛCDM including baryons have provided realistic predictions for the local DM distribution and its implications for DM direct detection [37][38][39][40][41][42]. These studies find that a Maxwell-Boltzmann distribution provides a good fit to the local DM velocity distribution of MW-like halos in ΛCDM simulations.…”

Section: Introductionmentioning

confidence: 85%

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The local dark matter distribution in self-interacting dark matter halos

Rahimi

Vienneau²,

Bozorgnia³

et al. 2023

J. Cosmol. Astropart. Phys.

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We study the effects of dark matter self-interactions on the local dark matter distribution in selected Milky Way-like galaxies in the EAGLE hydrodynamical simulations. The simulations were run with two different self-interacting dark matter models, a constant and velocity-dependent self-interaction cross-section. We find that the local dark matter velocity distribution of the Milky Way-like halos in the simulations with dark matter self-interactions and baryons are generally similar to those extracted from cold collisionless dark matter simulations with baryons. In both cases, the local dark matter speed distributions agree well with their best fit Maxwellian distributions. Including baryons in the simulations with or without dark matter self-interactions increases the local dark matter density and shifts the dark matter speed distributions to higher speeds. To study the implications for direct detection, we compute the dark matter halo integrals obtained directly from the simulations and compare them to those obtained from the best fit Maxwellian velocity distribution. We find that a Maxwellian distribution provides a good fit to the halo integrals of most halos, without any significant difference between the results of different dark matter self-interaction models.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 85%

The local dark matter distribution in self-interacting dark matter halos

Rahimi

Vienneau²,

Bozorgnia³

et al. 2023

J. Cosmol. Astropart. Phys.

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“…Appendix A Figure 1 References Apart from Symphony, Figure 1 shows the following cosmological zoom-in simulations: NIHAO (Wang et al 2015;Dutton et al 2016), ELVIS (Garrison-Kimmel et al 2014, 2019, Artemis (Poole-McKenzie et al 2020), Caterpillar (Griffen et al 2016), Via Lactea (Diemand et al 2008), Aquarius (Springel et al 2008), Latte (Wetzel et al 2016;Samuel et al 2020), APOSTLE (Sawala et al 2016), Ponos (Fiacconi et al 2016(Fiacconi et al , 2017, Phoenix (Gao et al 2012), the Three Hundred Project (Cui et al 2018), C-EAGLE (Barnes et al 2017), and simulations from Despali et al (2019) and Richings et al (2020). This collection is not comprehensive, and does not include: resimulation suites (e.g., PhatELVIS; Kelley et al 2019), zoom-ins of cosmological volumes that do not target specific hosts (e.g., Copernicus Complexio; Hellwing et al 2016), hydrodynamic simulations of lower-mass galaxies (e.g., from FIRE; Hopkins et al 2014), or simulations only presented in a hydrodynamic context (e.g., ERIS; Guedes et al 2011).…”

Section: Appendix B Convergence Testsmentioning

confidence: 99%

“…First, the majority of cosmological zoom-in simulations focus on host halos with masses similar to the Milky Way (e.g., Diemand et al 2008;Springel et al 2008;Garrison-Kimmel et al 2014;Mao et al 2015;Griffen et al 2016;Sawala et al 2016;Wetzel et al 2016;Samuel et al 2020;Poole-McKenzie et al 2020) or galaxy clusters (e.g., Gao et al 2012; Barnes et al 2017;Cui et al 2018). Although many exceptions exist (e.g., Wang et al 2015;Dutton et al 2016;Fiacconi et al 2016Fiacconi et al , 2017Despali et al 2019;Richings et al 2021), zoom-in suites at other mass scales typically include only a few distinct hosts, precluding analyses of their subhalo populations that capture host-tohost scatter (see Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Symphony: Cosmological Zoom-in Simulation Suites over Four Decades of Host Halo Mass

Nadler

Mansfield

Wang

et al. 2023

ApJ

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We present Symphony, a compilation of 262 cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from 1011–1015 M ⊙. This compilation includes three existing simulation suites at the cluster and Milky Way–mass scales, and two new suites: 39 Large Magellanic Cloud-mass (1011 M ⊙) and 49 strong-lens-analog (1013 M ⊙) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of ≈3 × 10−7 times the host virial mass and a Plummer-equivalent gravitational softening length of ≈9 × 10−4 times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are ≈50% higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts’ underlying dark matter distributions. We compare our results to the semianalytic model Galacticus, which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use UniverseMachine to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony.

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“…The suite comprises 45 such systems and their retinue of dwarf galaxies. The simulations have previously been shown to match a range of global properties of Milky Way-mass galaxies, such as galaxy sizes, star formation rates, stellar metallicities, and various observed properties of Milky Way-mass stellar haloes (Font et al 2020) and of the solar neighborhood (Poole-McKenzie et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Can cosmological simulations capture the diverse satellite populations of observed Milky Way analogues?

Font

McCarthy

Belokurov

2021

Monthly Notices of the Royal Astronomical Society

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The recent advent of deep observational surveys of local Milky Way ‘analogues’ and their satellite populations allows us to place the Milky Way in a broader cosmological context and to test models of galaxy formation on small scales. In the present study, we use the ΛCDM-based ARTEMIS suite of cosmological hydrodynamical simulations containing 45 Milky Way analogue host haloes to make comparisons to the observed satellite luminosity functions, radial distribution functions, and abundance scaling relations from the recent Local Volume and SAGA observational surveys, in addition to the Milky Way and M31. We find that, contrary to some previous claims, ΛCDM-based simulations can successfully and simultaneously capture the mean trends and the diversity in both the observed luminosity and radial distribution functions of Milky Way analogues once important observational selection criteria are factored in. Furthermore, we show that, at fixed halo mass, the concentration of the simulated satellite radial distribution is partly set by that of the underlying smooth dark matter halo, although stochasticity due to the finite number of satellites is the dominant driver of scatter in the radial distribution of satellites at fixed halo mass.

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Informing dark matter direct detection limits with the ARTEMIS simulations

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Cited by 12 publications

References 99 publications

The local dark matter distribution in self-interacting dark matter halos

The local dark matter distribution in self-interacting dark matter halos

Symphony: Cosmological Zoom-in Simulation Suites over Four Decades of Host Halo Mass

Can cosmological simulations capture the diverse satellite populations of observed Milky Way analogues?

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