The request to create MATH 7180/8180 and add as an elective course

Date: March 11, 2016
To: College of Liberal Arts & Sciences
From: Office of Academic Affairs
Approved On: February 2, 2016
Approved by: Graduate Council
Implementation Date: Summer 2016

Note: Deletions are strikethroughs. Insertions are underlined.

Catalog Copy

MATH 7180. Advanced Numerical Methods in Scientific Computing (3). Cross-listed as MATH 8180. Prerequisites: MATH 5172 and MATH 5176, or permission of the department. This course introduces advanced numerical methods in scientific computing. Topics include Particle-Mesh Ewald and the Fast multipole methods, boundary element methods, absorbing and perfectly matched layered boundary conditions, Yee’s finite difference and discontinuous Galerkin methods, surface integral equation methods, Nedelec edge elements for Maxwell equations, Bloch theory and periodic structures and photonics, Boltzmann and Wigner kinetic methods, high resolution Godunov methods and WENO methods for hydrodynamic equations, particle-in-cell and constrained transport methods for magnetohydrodynamics. (On demand)

MATH 8180. Advanced Numerical Methods in Scientific Computing (3). Cross-listed as MATH 7180. Prerequisites: MATH 5172 and MATH 5176, or permission of the department. This course introduces advanced numerical methods in scientific computing. Topics include Particle-Mesh Ewald and the Fast multipole methods, boundary element methods, absorbing and perfectly matched layered boundary conditions, Yee’s finite difference and discontinuous Galerkin methods, surface integral equation methods, Nedelec edge elements for Maxwell equations, Bloch theory and periodic structures and photonics, Boltzmann and Wigner kinetic methods, high resolution Godunov methods and WENO methods for hydrodynamic equations, particle-in-cell and constrained transport methods for magnetohydrodynamics. (On demand)

Concentration In General Mathematics

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Group I Applied Mathematics

Concentration in Applied Mathematics

The Master of Science degree concentration in Applied Mathematics is designed to develop critical thinking, intuition, and advanced experience in the techniques of mathematical analysis and their application to the problems of industry and technology. Skills are developed to deal with technical problems encountered in industry, business, and government and to hold leadership positions therein; to teach Applied Mathematics at the undergraduate or community college level; and to potentially study Applied Mathematics leading to the Ph.D. degree.

Concentration Requirements

A candidate for the Master of Science degree concentration in Applied Mathematics must complete at least 30 credit hours of graduate work approved by the department Graduate Committee to include:

Core Courses (21 credit hours)
Numerical Analysis Courses

Select one of the following:

Advanced Analysis Courses

Select one of the following:

Advanced Applied Mathematics Courses

Select two of the following:

Elective Courses (6 credit hours)
Advanced Elective Courses

Select one of the following: