Multivariate Evolutionary Analyses in Astrophysics

Didier Fraix-Burnet (1)

1 IPAG - Institut de Planétologie et d'Astrophysique de Grenoble

The large amount of data on galaxies, up to higher and higher redshifts, asks for sophisticated statistical approaches to build adequate classifications. Multivariate cluster analyses, that compare objects for their global similarities, are still confidential in astrophysics, probably because their results are somewhat difficult to interpret. We believe that the missing key is the unavoidable characteristics in our Universe: evolution. Our approach, known as Astrocladistics, is based on the evolutionary nature of both galaxies and their properties. It gathers objects according to their "histories" and establishes an evolutionary scenario among groups of objects. In this presentation, I show two recent results on globular clusters and earlytype galaxies to illustrate how the evolutionary concepts of Astrocladistics can also be useful for multivariate analyses such as K-means Cluster Analysis.

Keywords: multivariate analysis; evolution; cladistics; galaxies; globular clusters

Domains: Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]; Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]; Applications [stat.AP]

Didier Fraix-Burnet. Multivariate Evolutionary Analyses in Astrophysics. Astronomical Data Analysis, 6th conference, May 2010, Monastir, Tunisia. ⟨hal-00601508⟩