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Published October 2017 | Published
Journal Article Open

Not so lumpy after all: modelling the depletion of dark matter subhaloes by Milky Way-like galaxies

Abstract

Among the most important goals in cosmology is detecting and quantifying small (M_(halo)≃10^(6−9) M⊙) dark matter (DM) subhaloes. Current probes around the Milky Way (MW) are most sensitive to such substructure within ∼20 kpc of the halo centre, where the galaxy contributes significantly to the potential. We explore the effects of baryons on subhalo populations in ΛCDM using cosmological zoom-in baryonic simulations of MW-mass haloes from the Latte simulation suite, part of the Feedback In Realistic Environments (FIRE) project. Specifically, we compare simulations of the same two haloes run using (1) DM-only (DMO), (2) full baryonic physics and (3) DM with an embedded disc potential grown to match the FIRE simulation. Relative to baryonic simulations, DMO simulations contain ∼2 × as many subhaloes within 100 kpc of the halo centre; this excess is ≳5 × within 25 kpc. At z = 0, the baryonic simulations are completely devoid of subhaloes down to 3×10^6M⊙ within 15 kpc of the MW-mass galaxy, and fewer than 20 surviving subhaloes have orbital pericentres <20 kpc. Despite the complexities of baryonic physics, the simple addition of an embedded central disc potential to DMO simulations reproduces this subhalo depletion, including trends with radius, remarkably well. Thus, the additional tidal field from the central galaxy is the primary cause of subhalo depletion. Subhaloes on radial orbits that pass close to the central galaxy are preferentially destroyed, causing the surviving population to have tangentially biased orbits compared to DMO predictions. Our method of embedding a potential in DMO simulations provides a fast and accurate alternative to full baryonic simulations, thus enabling suites of cosmological simulations that can provide accurate and statistical predictions of substructure populations.

Additional Information

© 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2017 July 5. Received 2017 July 5; in original form 2017 January 17. Published: 08 July 2017. Support for SGK was provided by NASA through Einstein Postdoctoral Fellowship grant number PF5-160136 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. AW was supported by a Caltech-Carnegie Fellowship, in part through the Moore Center for Theoretical Cosmology and Physics at Caltech, and by NASA through grant HST-GO-14734 from STScI. JSB and TK were supported by NSF grant AST-1518291 and by NASA through HST theory grants (programs AR-13921, AR-13888, and AR-14282.001) awarded by the Space Telescope Science Institute (STScI), which is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under NASA contract NAS5-26555. Support for PFH was provided by an Alfred P. Sloan Research Fellowship, NASA ATP Grant NNX14AH35G, and NSF Collaborative Research Grant #1411920 and CAREER grant #1455342. MBK acknowledges support from the National Science Foundation (grant AST-1517226) and from NASA through HST theory grants (programs AR-12836, AR-13888, AR-13896 and AR-14282) awarded by STScI. CAFG was supported by NSF through grants AST-1412836 and AST-1517491, and by NASA through grant NNX15AB22G. DK acknowledges support from NSF grant AST-1412153 and the Cottrell Scholar Award from the Research Corporation for Science Advancement. EQ was supported by NASA ATP grant 12-APT12-0183, a Simons Investigator award from the Simons Foundation, and the David and Lucile Packard Foundation. Support for ASG was provided by NSF grant AST-1009973. Numerical calculations were run on the Caltech compute cluster 'Zwicky' (NSF MRI award #PHY-0960291) and allocation TG-AST130039 granted by the Extreme Science and Engineering Discovery Environment (XSEDE) supported by the NSF. Resources supporting this work were also provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. This work also made use of ASTROPY, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013), MATPLOTLIB (Hunter 2007), NUMPY (van der Walt, Colbert & Varoquaux 2011), SCIPY (Jones et al. 2001), IPYTHON (Perez & Granger 2007), MAYAVI (Ramachandran & Varoquaux 2011), and NASA's Astrophysics Data System.

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Created:
August 19, 2023
Modified:
October 17, 2023