Estimating the distribution of Galaxy Morphologies on a continuous space. Issue Volume 10:Issue S306(2014) (1st July 2015)

• Record Type: Journal Article
• Authors: Vinci, Giuseppe; Freeman, Peter; Newman, Jeffrey; Wasserman, Larry; Genovese, Christopher
• Editors: Heavens, A. F.; Starck, J.-L.; Krone-Martins, A.
• Is Part Of: Proceedings of the International Astronomical Union. Volume 10:Issue S306(2014)
• Page Start: 68
• Page End: 71
• Publication Date: 2015-07-01
• Subjects: dictionary learning, -- manifold estimation, -- Radon transform, -- redshift, -- sparse coding, -- galaxies: statistics; Astronomy -- Congresses; Astronomy -- Periodicals; 520
• DOI: 10.1017/S1743921314013568
• Languages: English
• ISSNs: 1743-9213

Abstract

Abstract: The incredible variety of galaxy shapes cannot be summarized by human defined discrete classes of shapes without causing a possibly large loss of information. Dictionary learning and sparse coding allow us to reduce the high dimensional space of shapes into a manageable low dimensional continuous vector space. Statistical inference can be done in the reduced space via probability distribution estimation and manifold estimation.