Abstract
Galaxy groups play a significant role in explaining the evolution of the universe. Given the amounts of available survey data, automated discovery of galaxy groups is of utmost interest. We introduce a novel methodology, based on probabilistic Hough transform, for finding galaxy groups embedded in a rich background. The model takes advantage of a typical signature pattern of galaxy groups known as “fingers-of-God”. It also allows us to include prior astrophysical knowledge as an inherent part of the method. The proposed method is first tested in large scale controlled experiments with 2-D patterns and then verified on 3-D realistic mock data (comparing with the well-known friends-of-friends method used in astrophysics). The experiments suggest that our methodology is a promising new candidate for galaxy group finders developed within a machine learning framework.
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Notes
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constructed based on a figure from [1].
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codes will be available from www.cs.bham.ac.uk/~pxt/my.publ.html.
References
Alpaslan, M., et al.: Galaxy and mass assembly (gama): the large scale structure of galaxies and comparison to mock universes. MNRAS 438(1), 177–194 (2014)
Astone, P., Colla, A., D’Antonio, S., Frasca, S., Palomba, C.: Method for all-sky searches of continuous gravitational wave signals using the frequency-hough transform. Phys. Rev. D 90, 042002 (2014)
Berlind, A.A., Frieman, J.A., Weinberg, D.H., Blanton, M.R., Warren, M.S., Abazajian, K., Scranton, R., Hogg, D.W., Scoccimarro, R., Bahcall, N.A., Brinkmann, J., Gott, J., Richard, I., Kleinman, S., Krzesinski, J., Lee, B.C., Miller, C.J., Nitta, A., Schneider, D.P., Tucker, D.L., Zehavi, I.: Percolation galaxy groups and clusters in the sdss redshift survey: identification, catalogs, and the multiplicity function. A.J.S 167, 1–25 (2006)
Duarte, M., Mamon, G.A.: Maggie: models and algorithms for galaxy groups, interlopers and environment (2014). arXiv:1412.3364
Eke, V.R., et al.: Galaxy groups in the 2dFGRS: the group - finding algorithm and the 2PIGG catalog. MNRAS 348, 866 (2004)
Hollitt, C., Johnston-Hollitt, M.: Feature detection in radio astronomy using the circle hough transform. PASA 29, 309–317 (2012)
Huchra, J.P., Geller, M.J.: Groups of galaxies. I - nearby groups. APJ 257, 423–437 (1982)
Liu, H.B., Hsieh, B., Ho, P.T., Lin, L., Yan, R.: A new galaxy group finding algorithm: probability friends-of-friends. APJ 681(2), 1046 (2008)
Llebaria, A., Lamy, P.: Time domain analysis of solar coronal structures through hough transform techniques. In: Mehringer, D., Plante, R., Roberts, D. (eds.) Astronomical Data Analysis Software and Systems VIII. Astronomical Society of the Pacific Conference Series, vol. 172, p. 46 (1999)
Mukhopadhyay, P., Chaudhuri, B.B.: A survey of hough transform. Pattern Recogn. 48(3), 993–1010 (2015)
Mushotzky, R.: Clusters of galaxies: an x-ray perspective. Clusters of Galaxies: Probes of Cosmological Structure and Galaxy Evolution, p. 123 (2004)
Navarro, J., Frenk, C.S., White, S.: The structure of cold dark matter halos. APJ 462, 563 (1996)
Pearson, R.J., Ponman, T.J., Norberg, P., Robotham, A.S.G., Farr, W.M.: On optical mass estimation methods for galaxy groups. MNRAS 449(3), 3082–3106 (2015)
Ramella, M., Geller, M.J., Huchra, J.P.: Groups of galaxies in the center for astrophysics redshift survey. APJ 344, 57–74 (1989)
Schechter, P.: An analytic expression for the luminosity function for galaxies. APJ 203, 297–306 (1976)
Storkey, A.J., Hambly, N.C., Williams, C.K.I., Mann, R.G.: Cleaning sky survey data bases using hough transform and renewal string approaches. MNRAS 347(1), 36–51 (2004)
Tino, P., Zhao, H., Yan, H.: Searching for coexpressed genes in three-color cdna microarray data using a probabilistic model-based hough transform. IEEE/ACM Trans. Comput. Biol. Bioinform. 8(4), 1093–1107 (2011)
Tyson, J.A., Valdes, F., Jarvis, J.F., Mills, A.P.: Galaxy mass-distribution from gravitational light deflection. APJ 281(2), L59–L62 (1984)
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Ibrahem, R.T., Tino, P., Pearson, R.J., Ponman, T.J., Babul, A. (2015). Automated Detection of Galaxy Groups Through Probabilistic Hough Transform. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_37
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