1 : Preliminaries   6 :   Dynamics I 11 : Star Formation  16 : Cosmology
2 : Morphology   7 :   Ellipticals 12 : Interactions 17 : Structure Growth  
3 : Surveys 8 :   Dynamics II 13 : Groups & Clusters  18 : Galaxy Formation 
4 : Lum. Functions  9 :   Gas & Dust   14 : Nuclei & BHs 19 : Reionization & IGM  
5 : Spirals 10 : Populations    15 : AGNs & Quasars 20 : Dark Matter





(1) Motivation & Aims

First step in new scientific area :   classify objects/phenomena
1850 - 1950 : discovery of galaxies   classify them

One approach to classification is to simply gather similar types into separate bins.
Wolf (1908) introduced a purely descriptive system of this type : [image]

A better approach is to choose categories which themselves form a coherent system
An ideal classification system of this type would have the following :


(2) Caveats with Standard System


(3) Brief History of Hubble Sequence

(a) Revisions by Sandage :

(b) Revisions by deVaucouleurs :


(4) Description and Illustration of Types

(a) Overview:

(b) Ellipticals : E

(c) Lenticulars : S0

(d) Spirals

(e) Very Late Spirals and Irregulars

(f) Peculiars

5%-10% galaxies are classified as "peculiar"
These don't fit easily into E, S0, S, I or dwarf categories
Nor are they mildly unusual, with postfix "pec", which is common (e.g. M87 is E0pec)
Catalogues : Vorontsov-Vel'yaminov (1956) and Arp (1963) [o-link].
Most are the result of interactions [images]   (see Topic 13)
Induced star formation (and associated dust) leads to a large spread in color.

Examples of Amorphous Irregular; Polar Ring; Interacting Pair; and Merger.


(5) Relative Frequency of Types

A detailed discussion requires analysis of catalogue selection effects: Here we simply take a cursory census of the RSA catalog.
Broken down by stage and bar, we have


(6) Other Classification Systems/Extensions

(a) DDO (van den Bergh 1960) "Luminosity Classes"

(b) Elmegreen & Elmegreen (1982, 1987) Arm Classes

(c) van den Bergh's "Trifork" Diagram

van den Bergh (1976) introduces disk gas/arm prominence as secondary parameter


(7) Automated Galaxy Classification

Modern CCD imaging surveys generate vast numbers of galaxy images
There is a need for fast, objective, robust classification.
Several approaches:

(a) Brute Force Approach

(b) Automated Approach

Often, surveys yield distant galaxy images that are too small for detailed classification
But it is still crucial to know basically what type of galaxy they are.
A number of simple parameters have been found to be very useful:


(8) Physical Morphology