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BEGIN:VEVENT
DTSTART;TZID=Atlantic/Canary:20100610T000000
DTEND;TZID=Atlantic/Canary:20100610T010000
UID:iactalks-25
X-WR-CALNAME: IAC Talks: Open Astronomy Seminars
X-ORIGINAL-URL: /iactalks/Talks/view/25
CREATED:2010-06-10T00:00:00+01:00
X-WR-CALDESC: IAC Talks upcomming talks
SUMMARY:Automatic unsupervised classification of all Sloan Digital Sky Surv
 ey Data Release 7 galaxy spectra
DESCRIPTION:Automatic unsupervised classification of all Sloan Digital Sky 
 Survey Data Release 7 galaxy spectra\nDr. Jorge Sánchez Almeida\n\nUsing 
 the k-means cluster analysis algorithm, we carry out an unsupervised class
 ification of all galaxy spectra in the seventh and final Sloan Digital Sky
  Survey data release (SDSS/DR7). Except for the shift to rest-frame wavele
 ngths and the normalization to the g-band flux, no manipulation is applied
  to the original spectra. The algorithm guarantees that galaxies with simi
 lar spectra belong to the same class. We find that 99% of the galaxies can
  be assigned to only 17 major classes, with 11 additional minor classes in
 cluding the remaining 1%. The classification is not unique since many gala
 xies appear in between classes; however, our rendering of the algorithm ov
 ercomes this weakness with a tool to identify borderline galaxies. Each cl
 ass is characterized by a template spectrum, which is the average of all t
 he spectra of the galaxies in the class. These low-noise template spectra 
 vary smoothly and continuously along a sequence labeled from 0 to 27, from
  the reddest class to the bluest class. Our Automatic Spectroscopic K-mean
 s-based (ASK) classification separates galaxies in colors, with classes ch
 aracteristic of the red sequence, the blue cloud, as well as the green val
 ley. When red sequence galaxies and green valley galaxies present emission
  lines, they are characteristic of active galactic nucleus activity. Blue 
 galaxy classes have emission lines corresponding to star formation regions
 . We find the expected correlation between spectroscopic class and Hubble 
 type, but this relationship exhibits a high intrinsic scatter. Several pot
 ential uses of the ASK classification are identified and sketched, includi
 ng fast determination of physical properties by interpolation, classes as 
 templates in redshift determinations, and target selection in follow-up wo
 rks (we find classes of Seyfert galaxies, green valley galaxies, as well a
 s a significant number of outliers). The ASK classification is publicly ac
 cessible through various Web sites.
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