Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey Page: 2 of 362
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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 = -20
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Hoversten, Erik A. & U., /Johns Hopkins. Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey, thesis or dissertation, October 1, 2007; Batavia, Illinois. (digital.library.unt.edu/ark:/67531/metadc893104/m1/2/: accessed January 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.