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Peer-reviewedCC BY 4.0The Astrophysical Journal

Bayesian Galaxy Asymmetry

  • Mathieu Perron-Cormier1
  • Kristine Spekkens1
  • Nathan Deg1
  • Lawrence M. Widrow1
  • Marcin Glowacki2,3
  1. 1Queen’s University
  2. 2University of Edinburgh
  3. 3Inter-University Institute for Data Intensive Astronomy
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Abstract

Galaxy asymmetry is an efficient way to characterize galaxy morphology in atomic hydrogen 21 cm emission detections. We propose a novel Bayesian approach to calculate the probability of an underlying squared differences asymmetry in a noisy detection. This approach has a number of advantages, including the recovery of low asymmetry values where prior noise corrections failed. More importantly, our approach provides robust uncertainties on the asymmetry, enabling a wide variety of statistical studies of galaxy populations. This method is generalized for convolved noise measures. We validate our method using a convergence test. Finally, we show how, when applied to the untargeted H I survey WALLABY, our method nearly triples the number of reliable measurements relatively to the previous state-of-the-art technique. This Bayesian approach to measure asymmetry will therefore further unlock the statistical power of widefield galaxy surveys.

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Cite

BibTeXRIS
BibTeX
@article{perroncormier2026bayesian,
  title = {{Bayesian Galaxy Asymmetry}},
  author = {Mathieu Perron-Cormier and Kristine Spekkens and Nathan Deg and Lawrence M. Widrow and Marcin Glowacki},
  journal = {The Astrophysical Journal},
  year = {2026},
  month = oct,
  doi = {10.3847/1538-4357/aea97a},
  url = {https://iopscience.iop.org/article/10.3847/1538-4357/aea97a},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Bayesian Galaxy Asymmetry
AU  - Mathieu Perron-Cormier
AU  - Kristine Spekkens
AU  - Nathan Deg
AU  - Lawrence M. Widrow
AU  - Marcin Glowacki
PY  - 2026
DA  - 2026/10/12
JO  - The Astrophysical Journal
DO  - 10.3847/1538-4357/aea97a
UR  - https://iopscience.iop.org/article/10.3847/1538-4357/aea97a
AB  - Galaxy asymmetry is an efficient way to characterize galaxy morphology in atomic hydrogen 21 cm emission detections. We propose a novel Bayesian approach to calculate the probability of an underlying squared differences asymmetry in a noisy detection. This approach has a number of advantages, including the recovery of low asymmetry values where prior noise corrections failed. More importantly, our approach provides robust uncertainties on the asymmetry, enabling a wide variety of statistical studies of galaxy populations. This method is generalized for convolved noise measures. We validate our method using a convergence test. Finally, we show how, when applied to the untargeted H I survey WALLABY, our method nearly triples the number of reliable measurements relatively to the previous state-of-the-art technique. This Bayesian approach to measure asymmetry will therefore further unlock the statistical power of widefield galaxy surveys.
SN  - 0004-637X
SN  - 1538-4357
ER  -