The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
FAINT TIDAL FEATURES IN GALAXIES WITHIN THE CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY WIDE FIELDS
Open accessAbstract
We present an analysis of the detectability of faint tidal features in galaxies from the wide-field component of the Canada–France–Hawaii Telescope Legacy Survey. Our sample consists of 1781 luminous ( mag) galaxies in the magnitude range 15.5 mag < r ' < 17 mag and in the redshift range 0.04 < z < 0.2. Although we have classified tidal features according to their morphology (e.g., streams, shells, and tails), we do not attempt to interpret them in terms of their physical origin (e.g., major versus minor merger debris). Instead, we provide a catalog that is intended to provide raw material for future investigations which will probe the nature of low surface brightness substructure around galaxies. We find that around 12% of the galaxies in our sample show clear tidal features at the highest confidence level. This fraction rises to about 18% if we include systems with convincing, albeit weaker tidal features, and to 26% if we include systems with more marginal features that may or may not be tidal in origin. These proportions are a strong function of rest-frame color and of stellar mass. Linear features, shells, and fans are much more likely to occur in massive galaxies with stellar masses >10 10.5 M ☉ , and red galaxies are twice as likely to show tidal features than are blue galaxies.
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“Current tidal feature detection and classification is primarily achieved through visual identification (e.g. Tal et al. 2009; Sheen et al. 2012; Atkinson et al. 2013; Hood et al. 2018; Bílek et al. 2020; Martin et al. 2022)”
From Detecting galaxy tidal features using self-supervised representation learning (2024) · cites this paper as Atkinson et al. 2013
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“They used a sample of 305 galaxies with tidal features and 1316 galaxies without tidal features, assembled by Atkinson et al. (2013), to train a CNN, using augmentations such as image flipping, rotation, and translation to expand their dataset.”
From Detecting galaxy tidal features using self-supervised representation learning (2024) · cites this paper as Atkinson et al. (2013)
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Metadata
- Authors
- Atkinson, A. M., Abraham, R. G., & Ferguson, A. M. N.
- Affiliations
- University of Toronto (CA)
- University of Edinburgh (GB)
- Venue
- The Astrophysical Journal
- Publisher
- American Astronomical Society
- Published
- 2013-02-13
- Volume
- 765
- Issue
- 1
- Pages
- 28
- ISSN
- 0004-637X (ISSN-L)
- 1538-4357
- OpenAlex
- W2046466474
- Cited by
- 122
- References
- 45
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 8 · 2023: 6 · 2022: 13 · 2021: 6 · 2020: 15 · 2019: 11 · 2018: 8 · 2017: 8 · 2016: 8 · 2015: 10 · 2014: 11 · 2013: 3
- FWCI
- 5.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The Astrophysical Journal (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Science and Technology Facilities Council (ST/J001422/1)
- Topics
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Stellar, planetary, and galactic studies
- Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Astrophysical Phenomena and Observations
- Keywords
- tidal features, galaxy morphology, galaxy tails, galaxy mergers, stellar mass, rest-frame colors, galaxy catalog
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