Investigating the environment of magnesium II absorption line systems with the Sloan Digital Sky Survey.

Format:

Book

Thesis/Dissertation

Author/Creator:

Caler, Michelle A.

Contributor:

University of Pennsylvania.

Language:

English

Subjects (All):

Astrophysics.

0596.

Local Subjects:

0596.

Physical Description:

238 pages

Contained In:

Dissertation Abstracts International 71-04B.

System Details:

Mode of access: World Wide Web.

text file

Summary:

We study the properties of 1880 Mg II absorption line systems using only the photometric data cataloged by the Sloan Digital Sky Survey. To compensate for the lack of redshift information, we develop several background subtraction techniques to isolate galaxies physically associated with the absorption systems. These methods were tested on a set of mock catalogs to ensure that they yield correct results when applied to a set of data.

Upon measuring the absolute magnitude distribution and luminosity function of neighbours of these absorbers, we find a distribution whose shape matches a fiducial model based on a luminosity function at a similar redshift. On scales 0.02--0.5 Mpc/h, we find that strong systems have more neighbours than weak ones; when the scale is increased to 0.02--1 Mpc/h, weak systems have more neighbours.

Our measured Mg II absorber-neighbouring galaxy projected cross-correlation function demonstrates evidence of a break at ∼ 100 kpc/h (co-moving), but is consistent with a single power law over the range 40 kpc/h ≤ rp ≤ 880 kpc/h. The cross-correlation functions of the weak and strong sub-samples have similar slopes, but the amplitude of the weak one is higher than that of the strong one.

We use the galaxies closest in angular separation to absorbers to constrain the properties of candidate hosts. The mean absorber-galaxy centre separation is ∼ 30 kpc/h; we also find that strong systems lie closer to the centre of their host galaxies than weak systems.

Notes:

Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2440.

Adviser: Ravi K. Sheth.

Thesis (Ph.D.)--University of Pennsylvania, 2009.

Local Notes:

School code: 0175.

ISBN:

9781109709438

Access Restriction:

Restricted for use by site license.