Computational methods are widely applied in all areas of astrophysical research, including data analysis, instrumentation, and theory. This course covers advanced computing skills that optimize the scientific return from using increasingly complex code bases and sophisticated code development tools. Using Python, we introduce widely applicable numerical methods while training the students in the use of commonly used code development concepts.

Independent study of a topic of special interest to the student under individual supervision by a faculty member. May be repeated once for credit. Prerequisite: Instructor permission.

May be repeated once for credit. Prerequisite: Instructor permission.

Surveys modern techniques of radiation measurement, data analysis, and image processing, and their application to astrophysical problems, especially the physical properties of stars and galaxies. Relevant laboratory experiments and observations with the department's telescopes are included. Students are expected to develop a familiarity with programming and other basic computer skills if they do not already possess them. Prerequisite: ASTR 2110-2120; PHYS 3420, 3430 or instructor permission.

Graduate students will be exposed to a research methods-intensive set of projects, with emphasis on current active areas of astrophysics research. The goal is to prepare students for research in astrophysics. Topics will include databases and database manipulation, astronomical surveys, statistics, space observatories and observation planning, intro to numerical simulations, and proposal writing.

This interdisciplinary course will introduce advanced undergraduates and graduates to molecules and their chemistry in different sources throughout the universe. Topics include gas-phase and grain-surface reactions, astronomical spectroscopy, laboratory experiments, and astrochemical modeling.Prerequisite: There are no formal prerequisites, but some knowledge of chemical kinetics, spectroscopy, and/or the interstellar medium will be helpful.

Studies the physics of the interstellar gas and grains, the distribution and dynamics of gas, and cosmic radiation and interstellar magnetic fields. Prerequisite: Instructor permission.

Studies observed properties and physics of stars including radiative transfer; stellar thermodynamics; convection; formation of spectra in atmospheres; equations of stellar structure; nuclear reactions; stellar evolution; and nucleosynthesis. Includes applicable numerical techniques. Prerequisite: Instructor permission.

The compact stars - white dwarfs, neutron stars, and black holes - are the end state of stellar evolution. The conditions in and around these objects are extreme as compared to terrestrial standards, and they are responsible for some of the most powerful and dynamic phenomena in the universe. This course introduces the physics of strong gravity and dense matter required to understand compact stars and their observational manifestations.

Computational methods are widely applied in all areas of astrophysical research, including data analysis, instrumentation, and theory. This course covers advanced computing skills that optimize the scientific return from using increasingly complex code bases and sophisticated code development tools. Using Python, we introduce widely applicable numerical methods while training the students in the use of commonly used code development concepts.