Morphological classification of galaxies and its relation to physical properties

We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies approaches the problem separately through either morphological classification or, in more recent times, analysis of physical properties. A combined approach has significant potential in producing a consistent and accurate classification scheme as well as shedding light on the origin and evolution of galaxy morphology. Here, we present an analysis of a volume-limited sample of 31 703 galaxies from the fourth data release of the Sloan Digital Sky Survey. We use an image analysis method called Pixel-z to extract the underlying physical properties of the galaxies, which is then quantified using the concentration, asymmetry and clumpiness parameters. The galaxies also have their multiwavelength morphologies quantified using QMM, and these results are then related to the distributed physical properties through a regression analysis. We show that this method can be used to relate the spatial distribution of physical properties with the morphological properties of galaxies.

[1]  Kari Karhunen,et al.  Über lineare Methoden in der Wahrscheinlichkeitsrechnung , 1947 .

[2]  A. Sandage,et al.  The Las Campanas survey of bright southern galaxies. II - New classifications for 153 systems , 1979 .

[3]  Christopher J. Conselice,et al.  The Relationship between Stellar Light Distributions of Galaxies and Their Formation Histories , 2003 .

[4]  R. Lupton,et al.  Astrometric Calibration of the Sloan Digital Sky Survey , 2002, astro-ph/0211375.

[5]  Brandon C. Kelly,et al.  Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey , 2004 .

[6]  Ralf Bender,et al.  A Proposed Revision of the Hubble Sequence for Elliptical Galaxies , 1996 .

[7]  E. al.,et al.  The Sloan Digital Sky Survey: Technical summary , 2000, astro-ph/0006396.

[8]  Donald E. Osterbrock,et al.  On the Classification of the Forms and the Stellar Content of Galaxies , 1969 .

[9]  Jean-Luc Starck,et al.  Astronomical Data Analysis II , 2002 .

[10]  W. W. Morgan PRELIMINARY CLASSIFICATION OF THE FORMS OF GALAXIES ACCORDING TO THEIR STELLAR POPULATION. II , 1958 .

[11]  D. Bazell Feature relevance in morphological galaxy classification , 2000 .

[12]  N. Vogt,et al.  The DEEP Groth Strip Survey. II. Hubble Space Telescope Structural Parameters of Galaxies in the Groth Strip , 2002, astro-ph/0205025.

[13]  Mark SubbaRao,et al.  The Sloan Digital Sky Survey 1-Dimensional Spectroscopic Pipeline , 2002, SPIE Astronomical Telescopes + Instrumentation.

[14]  S. Okamura,et al.  Galaxy types in the Sloan Digital Sky survey using supervised artificial neural networks , 2003, astro-ph/0306390.

[15]  A. Réfrégier,et al.  Shape Reconstruction and Weak Lensing Measurement with Interferometers: A Shapelet Approach , 2001, astro-ph/0107085.

[16]  G. Vaucouleurs An expanding association of galaxies , 1959 .

[17]  J. Gunn,et al.  A Photometricity and Extinction Monitor at the Apache Point Observatory , 2001, astro-ph/0106511.

[18]  R. H. Berry,et al.  Modal decomposition of astronomical images with application to shapelets , 2004 .

[19]  David L. Block,et al.  Morphological differences between optical and infrared images of the spiral galaxy NGC309 , 1991, Nature.

[20]  The Star Formation History of Galaxies Measured from Individual Pixels. I. The Hubble Deep Field North , 2003, astro-ph/0307470.

[21]  A. Connolly,et al.  SPATIALLY RESOLVED GALAXY STAR FORMATION AND ITS ENVIRONMENTAL DEPENDENCE. II. EFFECT OF THE MORPHOLOGY–DENSITY RELATION , 2007, 0711.1171.

[22]  L. Ho,et al.  Detailed structural decomposition of galaxy images , 2002, astro-ph/0204182.

[23]  J. A. Smith,et al.  SDSS data management and photometric quality assessment , 2004 .

[24]  B. C. Kelly,et al.  MORPHOLOGICAL CLASSIFICATION OF GALAXIES BY SHAPELET DECOMPOSITION IN THE SLOAN DIGITAL SKY SURVEY. II. MULTIWAVELENGTH CLASSIFICATION , 2005 .

[25]  N. R. Tanvir,et al.  Galaxy morphology to I = 25 mag in the Hubble Deep Field , 1996 .

[26]  T. Jarrett Near‐Infrared Galaxy Morphology Atlas , 2000 .

[27]  A. Naim,et al.  Quantitative Morphology of Moderate-Redshift Galaxies: How Many Peculiar Galaxies Are There? , 1996, astro-ph/9609075.

[28]  P. Madau,et al.  A NEW NONPARAMETRIC APPROACH TO GALAXY MORPHOLOGICAL CLASSIFICATION , 2003, astro-ph/0311352.

[29]  Sidney van den Bergh,et al.  Galaxy Morphology And Classification , 1998 .

[30]  C. Stein Estimation of the Mean of a Multivariate Normal Distribution , 1981 .

[31]  A. Naim,et al.  Galaxy Morphology without Classification: Self-organizing Maps , 1997 .

[32]  Alexandre Refregier,et al.  Image simulation with shapelets , 2003, astro-ph/0301449.

[33]  S. C. Odewahn,et al.  Automated Galaxy Morphology: A Fourier Approach , 2002 .

[34]  A. Réfrégier Shapelets: I. a method for image analysis , 2001, astro-ph/0105178.

[35]  Joel R. Primack,et al.  The Rest-Frame Far-Ultraviolet Morphologies of Star-Forming Galaxies at z ~ 1.5 and 4 , 2006 .

[36]  G. Bruzual,et al.  Stellar population synthesis at the resolution of 2003 , 2003, astro-ph/0309134.

[37]  S. Bergh A new classification system for galaxies. , 1976 .

[38]  Siciy C. Pao On the Effect of Fluid Motion on the Initial Decay of a Magnetic Field in a Sphere. , 1956 .

[39]  B. Yanny,et al.  The Sloan Digital Sky Survey monitor telescope pipeline , 2006 .