Graduate Courses

AST 5012: The Interstellar Medium

4 credits — Lecture

Prerequisites: AST 2001, PHYS 2601 or instructor consent

Typically Offered: Periodic Fall 

Survey of physical processes in the interstellar medium. Dynamic processes, excitation processes, emission and absorption by gas and dust. Hot bubbles, HII regions, molecular clouds.

AST 5022: Relativity, Cosmology, and the Universe

4 credits — Lecture

Prerequisites: AST 2001, PHYS 2601 or instructor consent

Typically Offered: Periodic Fall & Spring

Large-scale structure/history of universe. Introduction to Newtonian/relativistic world models. Physics of early universe, cosmological tests, formation of galaxies.

AST 5031: Interpretation and Analysis of Astrophysical Data

4 credits — Lecture

Prerequisite: graduate student in physics or astronomy

Typically Offered: Every Spring

Introduction to analysis techniques with applications to modern astrophysics. Methods to interpret/analyze large data sets from experiments. Principles/methods of analysis, with applications to current research.

AST 5201: Methods of Experimental Astrophysics

4 credits — Lab and lecture

Prerequisite: upper division CSE, graduate student, or instructor consent

Typically Offered: Spring even year

Contemporary astronomical techniques and instrumentation. Emphasizes data reduction and analysis, including image processing. Students make astronomical observations at O’Brien Observatory and use department’s computing facilities for data analysis. Image processing packages include IRAF, AIPS, IDL, MIRA.

AST 5731: Methods of Bayesian Astrostatistics

4 credits — Lab and lecture

Prerequisite: multivariable calculus and linear algebra, or instructor consent. Suggested: statistical methods at the level of AST 4031, AST 5031, STAT 3021, or STAT 5021; or familiarity with astrophysics topics such as star formation and evolution, galaxies and clusters, composition and expansion of the universe, gravitational wave sources and waveforms, and high-energy astrophysics.

Typically Offered: Every Fall 

This course will introduce Bayesian methods for interpreting and analyzing large data sets from astrophysical experiments. These methods will be demonstrated using astrophysics real-world data sets, and a focus on modern statistical softwares such as R and python. The course will assume familiarity with basic concepts in astrophysics, but it will include brief reviews as needed to demonstrate the use of modern data analysis techniques.

AST 8333: FTE: Master’s

1 credits — No Grade Associated

Prerequisites: master’s student, consent from adviser and Director of Graduate Studies

AST 8444: FTE: Doctoral

1 credits — No Grade Associated

Prerequisites: doctoral student, consent from adviser and Director of Graduate Studies

AST 8666: Doctoral Pre-Thesis Credits

1–6 credits — No Grade Associated

Prerequisites: doctoral student who has not passed oral preliminary exam; no required consent for first and second registrations, up to 12 combined credits; Department consent for third and fourth registrations, up to 24 combined credits; doctoral student admitted before Summer 2007 may register up to four times, up to 60 combined credits

TODO: Need to ask about the prerequisite on this one

AST 8777: Thesis Credits: Master’s

1–18 credits — No Grade Associated

Prerequisites: maximum 18 credits per semester or summer, 10 credits total required [Plan A only]

Typically Offered: Every Fall, Spring & Summer

AST 8888: Thesis Credit: Doctoral

1–24 credits — No Grade Associated

Prerequisites: doctoral student who has passed preliminary oral exam; maximum 18 credits per semester or summer, 24 credits required

Typically Offered: Every Fall, Spring & Summer

AST 8990: Research in Astronomy and Astrophysics

1–4 credits — Independent Study

Prerequisite: instructor consent

Typically Offered: Every Fall & Spring 

Research under supervision of a graduate faculty member.