Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey Page: 2 of 362
This thesis or dissertation is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided to UNT Digital Library by the UNT Libraries Government Documents Department.
Extracted Text
The following text was automatically extracted from the image on this page using optical character recognition software:
Abstract
This thesis centers on the use of spectral modeling techniques on data from
the Sloan Digital Sky Survey (SDSS) to gain new insights into current questions in
galaxy evolution. The SDSS provides a large, uniform, high quality data set which
can be exploited in a number of ways. One avenue pursued here is to use the large
sample size to measure precisely the mean properties of galaxies of increasingly narrow
parameter ranges. The other route taken is to look for rare objects which open up
for exploration new areas in galaxy parameter space.
The crux of this thesis is revisiting the classical Kennicutt method for in-
ferring the stellar initial mass function (IMF) from the integrated light properties of
galaxies. A large data set (- 105 galaxies) from the SDSS DR4 is combined with
more in-depth modeling and quantitative statistical analysis to search for systematic
IMF variations as a function of galaxy luminosity. Galaxy Hc equivalent widths are
compared to a broadband color index to constrain the IMF. It is found that for the
sample as a whole the best fitting IMF power law slope above 0.5 ME is I = 1.5 0.1
with the error dominated by systematics. Galaxies brighter than around M,.,O.I = -20ii
Upcoming Pages
Here’s what’s next.
Search Inside
This document can be searched. Note: Results may vary based on the legibility of text within the document.
Tools / Downloads
Get a copy of this page or view the extracted text.
Citing and Sharing
Basic information for referencing this web page. We also provide extended guidance on usage rights, references, copying or embedding.
Reference the current page of this Thesis Or Dissertation.
Hoversten, Erik A. Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey, thesis or dissertation, October 1, 2007; Batavia, Illinois. (https://digital.library.unt.edu/ark:/67531/metadc893104/m1/2/?rotate=270: accessed April 24, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.