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A multi-scale morphological analysis of the Sloan Digital Sky Survey (SDSS) Data Release 5 (DR5) was performed. We adapted the Metric Space Technique to perform a space-scale morphological analysis by filtering the galaxy point distributions with a smoothing Gaussian function, thus giving quantitative structural information on a range of scale sizes. The analysis was performed on 2-D (a dozen slices of a volume of space containing many newly measured galaxies from the SDSS DR5 survey) and 3-D data. Using the MST, observational data was compared to galaxy samples taken from N-body simulations…mehr

Produktbeschreibung
A multi-scale morphological analysis of the Sloan Digital Sky Survey (SDSS) Data Release 5 (DR5) was performed. We adapted the Metric Space Technique to perform a space-scale morphological analysis by filtering the galaxy point distributions with a smoothing Gaussian function, thus giving quantitative structural information on a range of scale sizes. The analysis was performed on 2-D (a dozen slices of a volume of space containing many newly measured galaxies from the SDSS DR5 survey) and 3-D data. Using the MST, observational data was compared to galaxy samples taken from N-body simulations with current best estimates of cosmological parameters and from random catalogs. By using the maximal ranking method among MST output functions we also developed a way to quantify the overall similarity of the observed samples with the simulated samples. MST does uncover some new multi-scale morphological properties and appears to be a good tool to measure those properties by clearly distinguishing the samples.
Autorenporträt
Yongfeng Wu received his B.S. (physics) from the Anhui Normal University (P.R.China) in 2001 and his Ph.D. (physics) from the University of Maine at orono (U.S.A) in 2010. He co-founded the Metric Space Technique and applied it into the astronomy research field. In 2010, He started his career in the field of ultrasonics in industry.