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Cited by 294

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Fossil Signatures of Ancient Accretion Events in the Halo

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Johnston, Kathryn V., Hernquist, Lars, Bolte, Michael·1996·The Astrophysical Journal

Abstract

The role that minor mergers have played in the formation and structure of the Milky Way is still an open question, about which there is much debate. We use numerical simulations to explore the evolution of debris from a tidally disrupted satellite, with the aim of developing a method that can be used to identify and quantify signatures of accretion in a survey of halo stars. For a Milky Way with a spherical halo, we find that debris from minor mergers can remain aligned along great circles throughout the lifetime of the Galaxy. We exploit this result to develop the method of great circle cell counts (GC3), which we test by applying it to artificially constructed halo distributions. Our results suggest that if as few as 1 % of the stars in a halo survey are accreted from the disruption of a single subsystem smaller than the Large Magellanic Cloud, GC3 can recover the great circle associated with this debris. The dispersion in GC3 can also be used to detect the presence of structure characteristic of accretion in distributions containing a much smaller percentage of material accreted from any single satellite.

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Metadata

Authors
Johnston, K. V., Hernquist, L., & Bolte, M.
Venue
The Astrophysical Journal
Published
1996-07
Volume
465
Pages
278
ISSN
  • 0004-637X (ISSN-L)
  • 1538-4357
OpenAlex
W1974309328
Cited by
294
References
0
FWCI
6.53
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Fossil Signatures of Ancient Accretion Events in the Halo. https://app.cochat.ai/papers/10.1086/177418
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Johnston, K. V., Hernquist, L., & Bolte, M. (1996). Fossil Signatures of Ancient Accretion Events in the Halo. The Astrophysical Journal. https://doi.org/10.1086/177418

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.