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Published March 2019 | Published
Journal Article Open

The suppression of star formation on the smallest scales: what role does environment play?

Abstract

The predominantly ancient stellar populations observed in the lowest mass galaxies (i.e. ultra-faint dwarfs) suggest that their star formation was suppressed by reionization. Most of the well-studied ultra-faint dwarfs, however, are within the central half of the Milky Way dark matter halo, such that they are consistent with a population that was accreted at early times and thus potentially quenched via environmental processes. To study the potential role of environment in suppressing star formation on the smallest scales, we utilize the Exploring the Local Volume in Simulations suite of N-body simulations to constrain the distribution of infall times for low-mass subhaloes likely to host the ultra-faint population. For the ultra-faint satellites of the Milky Way with star formation histories inferred from Hubble Space Telescopeimaging, we find that environment is highly unlikely to play a dominant role in quenching their star formation. Even when including the potential effects of pre-processing, there is a ≲0.1 per cent probability that environmental processes quenched all of the known ultra-faint dwarfs early enough to explain their observed star formation histories. Instead, we argue for a mass floor in the effectiveness of satellite quenching at roughly M⋆∼10^5M⊙, below which star formation in surviving galaxies is globally suppressed by reionization. We predict a large population of quenched ultra-faint dwarfs in the Local Field (1 < R/R_(vir) < 2), with as many as ∼250 to be discovered by future wide-field imaging surveys.

Additional Information

© 2018 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2018 December 5. Received 2018 December 4; in original form 2018 June 19. Published: 11 December 2018. We thank Tyler Kelley, Dan Weisz, Josh Simon, Alex Riley, and Mary Jenkins for helpful discussions regarding this project. This work was supported in part by NSF grants AST-1518257, AST-1518291, AST-1517226, and AST-1815475. MBK also acknowledges support from NSF CAREER grant AST-1752913 and NASA grant NNX17AG29G. Additional support for this work was provided by NASA through grants GO-12914, AR-13888, AR-13896, GO-14191, AR-14282, AR-14289, AR-14554, and AR-15006 from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. MKRW acknowledges support from the National Science Foundation Graduate Research Fellowship. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1321846. This research made use of ASTROPY, a community-developed core PYTHON package for Astronomy (Astropy Collaboration et al. 2013). Additionally, the PYTHON packages NUMPY (Walt, Colbert & Varoquaux 2011), IPYTHON (Pérez & Granger 2007), SCIPY (Jones et al. 2001), and MATPLOTLIB (Hunter 2007) were utilized for the majority of our data analysis and presentation.

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Created:
August 19, 2023
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October 20, 2023