The Connection Between Galaxies and Their Dark Matter Halos
By Risa Wechsler, J. Tinker. Annual Review of Astronomy and Astrophysics, 2018
561 citations recorded by the source corpus.
In our modern understanding of galaxy formation, every galaxy forms within a dark matter halo. The formation and growth of galaxies over time is connected to the growth of the halos in which they form. The advent of large galaxy surveys as well as high-resolution cosmological simulations has provided a new window into the statistical relationship between galaxies and halos and its evolution. Here, we define this galaxy–halo connection as the multivariate distribution of galaxy and halo properties that can be derived from observations and simulations. This galaxy–halo connection provides a key test of physical galaxy-formation models; it also plays an essential role in constraints of cosmological models using galaxy surveys and in elucidating the properties of dark matter using galaxies. We review techniques for inferring the galaxy–halo connection and the insights that have arisen from these approaches. Some things we have learned are that galaxy-formation efficiency is a strong function of halo mass; at its peak in halos around a pivot halo mass of 1012M⊙, less than 20% of the available baryons have turned into stars by the present day; the intrinsic scatter in galaxy stellar mass is small, less than 0.2 dex at a given halo mass above this pivot mass; below this pivot mass galaxy stellar mass is a strong function of halo mass; the majority of stars over cosmic time were formed in a narrow region around this pivot mass. We also highlight key open questions about how galaxies and halos are connected, including understanding the correlations with secondary properties and the connection of these properties to galaxy clustering.
Subfields: Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics, Instrumentation
View Paper: https://www.semanticscholar.org/paper/e0d4fb12fc58909b9650b3fa152c019ca54cca8d
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In Astronomy and Astrophysics
- C. Conroy
- P. Hopkins
- R. Somerville
- L. Hernquist
- Christopher J. Conselice
- R. Dav'e
- A. Dekel
- P. V. van Dokkum
In Atomic and Molecular Physics, and Optics
In Instrumentation
- C. Conroy
- R. Somerville
- Christopher J. Conselice
- L. Hernquist
- P. Hopkins
- R. Dav'e
- A. Dekel
- Risa Wechsler
Citations in the corpus
- Milky Way Satellite Census. II. Galaxy–Halo Connection Constraints Including the Impact of the Large Magellanic Cloud (2019, background): “The scatter in luminosity at fixed Vpeak is constrained to σM 0.15 dex at 95% confidence, which may inform hydrodynamic feedback prescriptions that predict a steep increase in luminosity scatter at low masses (e.g., see Wechsler & Tinker 2018).”
- Mining for Dark Matter Substructure: Inferring Subhalo Population Properties from Strong Lenses with Machine Learning (2019, background): “…about the underlying dark matter properties, theoretical uncertainties in the connection between stellar and halo properties (Nadler et al. 2019; Wechsler & Tinker 2018) and the effect of baryons on the satellite galaxy population (Errani et al. 2017; Garrison-Kimmel et al. 2017; Brooks 2018;…”
- A Redshift-independent Efficiency Model: Star Formation and Stellar Masses in Dark Matter Halos at z ≳ 4 (2018, background): “An alternative approach is to connect halos to observed galaxies in a statistical way (see e.g. Wechsler & Tinker 2018, for a comprehensive review), thereby bypassing the explicit modeling of baryonic physics.”
- CEERS Key Paper. I. An Early Look into the First 500 Myr of Galaxy Formation with JWST (2022, background): “…also known as subhalo abundance matching or halo occupation distribution, which efficiently map the properties of a large ensemble of galaxies onto the properties of dark matter halos guided by a set of observed quantities and scaling relations (see Wechsler & Tinker 2018 for a detailed review).”
- UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10 (2018, background): “…Firmani & Avila-Reese 2010; Leitner 2012; Béthermin et al. 2013; Wang et al. 2013; Moster et al. 2013; Behroozi et al. 2013e,f; Mutch et al. 2013; Birrer et al. 2014; Marchesini et al. 2014; Lu et al. 2014a, 2015b; Papovich et al. 2015; Li et al. 2016; see Wechsler & Tinker 2018 for a review).”