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Master in Applied Mathematics with
concentration in Dynamical Systems
Major Code: 17031, SIMS Code: 776316


Program:

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.


Preparation:

Before entering the program, students must complete the following upper division courses, or equivalent. Students with inadequate undergraduate preparation may be accepted conditionally but will be required to complete courses for removal of the deficiency in the first year of study.

All of the following
  • Math 237 - Elementary Differential Equations (3 units)
  • Math 330 - Advanced Calculus (3 units)
  • Math 340 - Mathematical Programming (3 units)
  • Math 524 - Linear Algebra (3 units)

    • One of the following
  • Stat 350A - Statistical Methods (3 units)
  • Stat 551A - Probability and Mathematical Statistics (3 units)

    • Required Courses (31 units):

    The 31 units may include at most 12 units of approved 500-level mathematics courses and at most six units of independent research (Mathematics 797, 798, 799A, 799B). Elective courses from other departments may be approved by the adviser.

    All of the following
  • Math 538 - Discrete Dynamical Systems and Chaos (3 units)
  • Math 636 - Mathematical Modeling (3 units)
  • Math 780 - Seminar in Communicating Mathematical Research (1 unit) [maximum one RP allowed]
  • Math 797 - Research (3 units)
  • Math 799A - Thesis or Project (3 units)

    • One of the following
  • Math 531 - Partial Differential Equations (3 units)
  • Math 537 - Ordinary Differential Equations (3 units)
  • Math 638 - Continuous Dynamical Systems and Chaos (3 units)

    • One of the following
  • Math 630 - Applied Real Analysis (3 units)
  • Math 668 - Applied Fourier Analysis (3 units)

    • One of the following
  • Math 693A - Advanced Numerical Methods: Computational Optimization (3 units)
  • Math 693B - Advanced Numerical Methods: Computational Partial Differential Equations (3 units)

    • 9 units of electives, possibly selected from the following
  • Math 542 - Introduction to Computational Ordinary 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)

    • Other requirements:

    Program of study.
    The program of study,to include a plan for removal of any conditions on admission, must be approved by the graduate adviser and will include at least 22 units in mathematics.

    Thesis.
    Students must select Plan A and complete Math 799A (Thesis). Students are advised that a thesis normally takes a year to complete.

    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