Identification and Analysis of Galactic Bars in DESI Legacy Imaging Surveys

Abstract We present a comprehensive study of bar structures in the local universe using data from the DESI Legacy Imaging Surveys. Through isophotal analysis of 232,142 galaxies, we identify bars and classify them into strong and weak categories based on normalized bar length, using a threshold of 0.4. We find a total bar fraction of 42.9%, rising to 62.0% in disk galaxies, with strong barred galaxies accounting for 30.0%. For barred galaxies in our sample, deprojected bar lengths are measured both in absolute terms and normalized by galaxy size. Most bars are found to have absolute lengths of 3–7 kpc, and normalized bar lengths concentrated around a median value of 0.4. Bar ellipticity mainly ranges from 0.2 to 0.6, with a median value of 0.3. Our analysis reveals a bimodal distribution of bar fractions with respect to galaxy color, with weak bars in our classification being more prevalent in intermediate-color systems. With respect to stellar mass, strong bars also present a bimodal distribution, while weak bars are distributed uniformly. Normalized bar length remains relatively stable across stellar masses, while absolute bar length positively correlates with stellar mass. Cross-validation with visual classifications from Galaxy Zoo DESI catalog confirms a bar identification accuracy of 93%. These results validate our automated method for bar identification and measurement, demonstrating its reliability. Our findings underscore the importance of bars in galaxy evolution and highlight the potential of upcoming wide-field surveys to deepen our understanding of barred galaxies.

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Publication Details

Journal
The Astrophysical Journal
Published
2025-03-25
DOI
https://doi.org/10.3847/1538-4357/adbcac
Citations
3
Primary Topic
Gamma-ray bursts and supernovae
Type
article
Field-Weighted Citation Impact
3.46
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article

Identification and Analysis of Galactic Bars in DESI Legacy Imaging Surveys

Zhimin Zhou, Wenwen Wang
3 citations
The Astrophysical Journal
Gamma-ray bursts and supernovae
3.46
article

Identification and Analysis of Galactic Bars in DESI Legacy Imaging Surveys

Zhimin Zhou, Wenwen Wang
article en
3 citations

Abstract

Abstract We present a comprehensive study of bar structures in the local universe using data from the DESI Legacy Imaging Surveys. Through isophotal analysis of 232,142 galaxies, we identify bars and classify them into strong and weak categories based on normalized bar length, using a threshold of 0.4. We find a total bar fraction of 42.9%, rising to 62.0% in disk galaxies, with strong barred galaxies accounting for 30.0%. For barred galaxies in our sample, deprojected bar lengths are measured both in absolute terms and normalized by galaxy size. Most bars are found to have absolute lengths of 3–7 kpc, and normalized bar lengths concentrated around a median value of 0.4. Bar ellipticity mainly ranges from 0.2 to 0.6, with a median value of 0.3. Our analysis reveals a bimodal distribution of bar fractions with respect to galaxy color, with weak bars in our classification being more prevalent in intermediate-color systems. With respect to stellar mass, strong bars also present a bimodal distribution, while weak bars are distributed uniformly. Normalized bar length remains relatively stable across stellar masses, while absolute bar length positively correlates with stellar mass. Cross-validation with visual classifications from Galaxy Zoo DESI catalog confirms a bar identification accuracy of 93%. These results validate our automated method for bar identification and measurement, demonstrating its reliability. Our findings underscore the importance of bars in galaxy evolution and highlight the potential of upcoming wide-field surveys to deepen our understanding of barred galaxies.

The Astrophysical JournalVol. 982(2)
Openalex Percentile: Top 8%
Gamma-ray bursts and supernovae
3.46
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Identification and Analysis of Galactic Bars in DESI Legacy Imaging Surveys — Zhimin Zhou, Wenwen Wang · The Astrophysical Journal (2025) | TGRS Research Map | TGRS