Detalles de publicación
PP 010017
Automatic unsupervised classification of all SDSS/DR7 galaxy spectra
(1) Instituto de Astrofisica de Canarias, E-38205 La Laguna, Tenerife, Spain
(2) Departamento de Astrofisica, Universidad de La Laguna, E-38071 La Laguna,
Tenerife, Spain
Using the 'k-means' cluster analysis algorithm, we carry out an unsupervised
classification of all galaxy spectra in the seventh and final Sloan Digital
Sky Survey data release (SDSS/DR7). Except for the shift to restframe
wavelengths, and the normalization to the g-band flux, no manipulation is
applied to the original spectra. The algorithm guarantees that galaxies
with similar 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
including the remaining 1%. The classification is not unique since many galaxies
appear in between classes, however, our rendering of the algorithm overcomes
this weakness with a tool to identify borderline galaxies. Each class is
characterized by a template spectrum, which is the average of all the
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-means-based (ASK) classification separates galaxies in colors, with classes
characteristic of the red sequence, the blue cloud, as well as the green
valley. When red sequence galaxies and green valley galaxies present emission
lines, they are characteristic of AGN 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 potential uses of
the ASK classification are identified and sketched, including fast
determination of physical properties by interpolation, classes as
templates in redshift determinations, and target selection
in follow-up works (we find classes of Seyfert galaxies, green valley galaxies,
as well as a significant number of outliers). The ASK classification is publicly
accessible through various websites.
Classification @ ftp://ask:galaxy@ftp.iac.es/
classification of all galaxy spectra in the seventh and final Sloan Digital
Sky Survey data release (SDSS/DR7). Except for the shift to restframe
wavelengths, and the normalization to the g-band flux, no manipulation is
applied to the original spectra. The algorithm guarantees that galaxies
with similar 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
including the remaining 1%. The classification is not unique since many galaxies
appear in between classes, however, our rendering of the algorithm overcomes
this weakness with a tool to identify borderline galaxies. Each class is
characterized by a template spectrum, which is the average of all the
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-means-based (ASK) classification separates galaxies in colors, with classes
characteristic of the red sequence, the blue cloud, as well as the green
valley. When red sequence galaxies and green valley galaxies present emission
lines, they are characteristic of AGN 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 potential uses of
the ASK classification are identified and sketched, including fast
determination of physical properties by interpolation, classes as
templates in redshift determinations, and target selection
in follow-up works (we find classes of Seyfert galaxies, green valley galaxies,
as well as a significant number of outliers). The ASK classification is publicly
accessible through various websites.
Classification @ ftp://ask:galaxy@ftp.iac.es/