The Master of Science Degree in Applied and computational mathematics is offered under both thesis and non-thesis plans. In both cases, the first year of study typically includes a theoretical core in linear and abstract algebra, real analysis, and probability and statistics. Students entering with sufficiently strong backgrounds may replace these with more advanced courses. Students also choose an area of concentration from among scientific computation, probability and statistics, applied analysis, continuous modeling and discrete mathematics/abstract algebra. An overview of modern computational issues is presented in a graduate level seminar.

During the second year, a student typically enrolls in graduate-level courses both in and out of the Department. Those studetns not writing a thesis take a heavier course load and participate in a research project. Degree requirements include a written examination on basic coursework and oral presentations of thesis or project work.

A more detailed description of degree requirements can be obtained by contacting the Director of Graduate Studies at the Department of Mathematics and Statistics.

 



A Basin of Attraction

Upper-level and graduate courses offered on a regular basis include the theoretical core courses in linear algebra, probability, abstract algebra, and real analysis, as well as courses on:
  • numerical analysis
  • numerical partial differential equations
  • scientific computation
  • linear programming
  • operational methods
  • dynamical systems
  • finite elements
  • ordinary differential equations
  • continuous mathematical modeling
  • measure theory
  • complex variables
  • analysis of variance
  • regression analysis
  • linear models
  • multivariate analysis
  • experimental design
  • statistic inference
  • stochastic processes
  • graph theory
  • algebraic coding theory
  • combinatorics
  • number theory
Computing plays an integral role in many upper-level mathematics and statistics courses offered by the department.

 

 At right: A visual representation of memory access for a banked memory vector Supercomputer, based on a simulation model designed and encoded by Mark Cotter (1995). The model allows for an examination of the contention for common memory on Cray-like vector supercomputers. Selecting the number of banks, bank delays, typical vector lengths, and the number of competing processors allows one to examine the difference between "peak" performance and "actual" performance. The graphics were done with the aid of geomview on a Silicon Graphics Indigo2.

 

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