Catalog description:
[Online Catalog]
Applied Mathematics, Dynamical Systems Concentration, M.S.
(Major Code: 17031) (SIMS Code: 776316).
This concentration focuses on interdisciplinary applications of dynamical systems and nonlinear modeling in biology, chemistry, engineering, and physics. Students with interests in modeling and analyzing real life problems through mathematics will benefit from this concentration. To enter the program, students must possess a bachelor's degree with a strong mathematical background; furthermore, the admission requirements for the Master of Science degree in applied mathematics also apply with the exception that only one semester of mathematical analysis/advanced calculus (MATH 330) is required.
Advancement to Candidacy:
All students must satisfy the general requirements for advancement to candidacy as described in Requirements for Master’s Degrees. In addition, the student must have passed a qualifying examination in some programs.
Core Courses
In addition to satisfying the requirements of the Master of Science Degree in Applied Mathematics, students pursuing this concentration must complete:
* MATH 531 - Partial Differential Equations (3 units)
or
* MATH 537 - Ordinary Differential Equations (3 units)
or
* MATH 638 - Continuous Dynamical Systems and Chaos (3 units)
* MATH 538 - Discrete Dynamical Systems and Chaos (3 units)
* MATH 630 - Applied Real Analysis (3 units)
or
* MATH 668 - Applied Fourier Analysis (3 units)
* MATH 636 - Mathematical Modeling (3 units)
* MATH 693A - Advanced Numerical Methods: Computational Optimization (3 units)
or
* MATH 693B - Advanced Numerical Methods: Computational Partial Differential Equations (3 units)
* MATH 780 - Seminar in Communicating Mathematical Research (1 unit)
* MATH 797 - Research Units (3 units)
and
* MATH 799A - Thesis or Project (3 units)
500- or 600-Level Courses:
The remaining units must consist of 500- or 600-level courses in mathematics or in a related area, selected with the approval of the program adviser.
Possible elective courses include:
*MATH 542 - Introduction to Computational Ordinary of Differential Equations (3 units)
*MATH 543 - Numerical Matrix Analysis (3 units)
*MATH 635 - Pattern Formation (3 units)
*MATH 639 - Nonlinear Waves (3 units)
*MATH 693A - Advanced Numerical Methods: Computational Optimization (3 units)
*MATH 693B - Advanced Numerical Methods: Computational Partial Differential Equations (3 units)
*COMP 605/CS 605 - Scientific Computing (3 units)
Note:
Students must select Plan A (Thesis) and give a public oral defense of the thesis. A thesis normally takes one year to complete and is done under the direction of a thesis adviser.
The thesis is written under the direction of a faculty
member who works closely with the student in both the
research and the writing of the thesis. The student
can choose any faculty member in the program to be the
thesis adviser. The student and the adviser will determine
the topic of the thesis, generally on a topic of interest to both.
Admission Requirements:
To be admitted to the program, the student should
have training equivalent to that required for an undergraduate
degree in mathematics, applied mathematics, physics
or electrical engineering. In addition, all students
must satisfy the general requirements for admission
to the university with classified graduate standing.
Please refer to the
Graduate Bulletin [Mathematics] for more details.
The Department maintains a web page with further information
on admission
requirements, deadlines, and further instructions.
Financial support:
Graduate Teaching Assistantships (GTAs) are available.
For further information go to our
Graduate
admissions webpage.
Exceptional candidates may be granted a tuition waver
to cover the difference between out-of-state fees and
in-state fees.
Maintained by
Ricardo Carretero
Ricardo Carretero Gonzalez
Antonio Palacios Peter Blomgren Joe Mahaffy Diana Verzi Chris Curtis San Diego
San Diego State University SDSU California West coast MS master
masters PhD doctorate doctoral graduate undergraduate concentration
emphasis applied mathematics chaos chaotic fractal fractals dynamics
dynamical systems nonlinear nonlinear dynamical systems nonlinear
dynamics NLDS model modeling modelling publication publications
research preprints analysis adaptivity aggregation bifurcation
bifurcations bioloby blowup blow up blow-up bose bose-einstein
breather breathers CML CMLs condensates coupled map lattices delay
differential determinism deterministic differential einstein embedding
equation equations fluidization fluidized GPE heteroclinic homoclinic
ILM ILMs image restoration intrinsic localized modes lattices
manifold map maps math mathematical bioloby metastability moving
mesh NLS nonlinear waves numerics numerical ODE ODEs orbit orbits
pattern patterns PDE PDEs POD prediction proper orthogonal decomposition
reconstruction soliton solitons spatio temporal stable stochastic
studies study systems tangle temporal time series unstable