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Note: This is a guide to the
courses we expect to teach each year. We cannot guarantee that these
courses will be taught.
Graduate Math Courses Offered Every Year
- Primarily for first-year students:
- Fall semester
- Math 216: Applied Stochastic Processes
- Math 224: Scientific Computing I
- Math 231: Ordinary Differential Equations
- Math 241: Real Analysis I
- Math 251: Groups, Rings and Fields
- Spring semester
- Math 219: Introduction to Stochastic Calculus
or Math 287: Probability Theory
- Math 225: Scientific Computing II
- Math 232: Partial Differential Equations I
- Math 245: Complex Analysis
- Math 252: Commutative Algebra
- Math 261: Algebraic Topology I
- Math 267: Differential Geometry
- Primarily for second-year students:
- Fall semester
- Math 226: Numerical Partial Differential Equations I
- Math 233: Asymptotic and Perturbation Methods
- Math 242: Real Analysis II (Functional Analysis)
- Math 253: Representation Theory
- Math 262: Algebraic Topology II
- Math 272: Riemann Surfaces
- Math 282: Elliptic Partial Differential Equations
- Math 288: Topics in Probability
- Spring semester
- Math 228: Mathematical Fluid Dynamics
- Math 229: Mathematical Modeling
- Math 236: General Relativity
- Math 268: Topics in Differential Geometry
- Math 273: Algebraic Geometry or Math 274: Number Theory
- Math 281: Hyperbolic Partial Differential Equations
Course descriptions
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MATH 216 - APPLIED STOCHASTIC PROCESSES
An introduction to stochastic processes without measure theory. Topics
selected from: Markov chains in discrete and continuous time, queuing theory,
branching processes, martingales, Brownian motion, stochastic calculus.
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MATH 219 - INTRODUCTION TO STOCHASTIC CALCULUS
An introduction to the theory of stochastic differential equations
with an eye towards those topics useful in applications.
Brownian motion, stochastic integrals, and diffusions as solutions of
stochastic differential equations. Functionals of diffusions and their
connection with partial differential equations. Ito's formula,
Girsanov's theorem, Feynman-Kac formula, Martingale representation
theorem. Additional topics have included one dimensional boundary
behavior, stochastic averaging, stochastic numerical methods.
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MATH 224 - SCIENTIFIC COMPUTING I
Structured scientific programming in C/C++ and FORTRAN. Floating point
arithmetic and interactive graphics for data visualization. Numerical linear
algebra, direct and iterative methods for solving linear systems, matrix
factorizations, least squares problems and eigenvalue problems. Iterative
methods for nonlinear equations and nonlinear systems, Newton's method.
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MATH 225 - SCIENTIFIC COMPUTING II
Approximation theory: Fourier series, orthogonal polynomials, interpolating
polynomials and splines. Numerical differentiation and integration. Numerical
methods for ordinary differential equations: finite difference methods for
initial and boundary value problems, and stability analysis. Introduction to
finite element methods.
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MATH 226 - NUMERICAL PARTIAL DIFF EQUATIONS I
Numerical solution of hyperbolic conservation laws. Conservative difference
schemes, modified equation analysis and Fourier analysis, Lax-Wendroff
process. Gas dynamics and Riemann problems. Upwind schemes for hyperbolic
systems. Nonlinear stability, monotonicity and entropy; TVD, MUSCL, and ENO
schemes for scalar laws. Approximate Riemann solvers and schemes for
hyperbolic systems. Multidimensional schemes. Adaptive mesh
refinement.
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MATH 227 - NUMERICAL PARTIAL DIFFERENTIAL EQUATIONS II
Numerical solution of parabolic and elliptic equations. Diffusion equations
and stiffness, finite difference methods and operator splitting (ADI).
Convection-diffusion equations. Finite element methods for elliptic equations.
Conforming elements, nodal basis functions, finite element matrix assembly and
numerical quadrature. Iterative linear algebra; conjugate gradients,
Gauss-Seidel, incomplete factorizations and multigrid. Mixed and hybrid
methods. Mortar elements. Reaction-diffusion problems, localized phenomena,
and adaptive mesh refinement.
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MATH 228 - MATHEMATICAL FLUID DYNAMICS
Properties and solutions of the Euler and Navier-Stokes equations, including
particle trajectories, vorticity, conserved quantities, shear, deformation and
rotation in two and three dimensions, the Biot-Savart law, and singular
integrals. Additional topics determined by the instructor.
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MATH 229 - MATHEMATICAL MODELING
Formulation and analysis of mathematical models in science and engineering.
Emphasis on case studies; may include individual or team research
projects.
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MATH 231 - ORDINARY DIFFERENTIAL EQUATIONS
Existence and uniqueness theorems for nonlinear systems, well-posedness,
two-point boundary value problems, phase plane diagrams, stability, dynamical
systems, and strange attractors.
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MATH 232 - INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS
Fundamental solutions of linear partial differential equations, hyperbolic
equations, characteristics, Cauchy-Kowalevski theorem, propagation of
singularities.
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MATH 233 - ASYMPTOTICS AND PERTURBATION METHODS
Asymptotic solution of linear and nonlinear ordinary and partial differential
equations. Asymptotic evaluation of integrals. Singular perturbation. Boundary
layer theory. Multiple scale analysis.
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MATH 241 - REAL ANALYSIS
Measures; Lebesgue integral; L^p spaces; Daniell integral, differentiation
theory, product measures.
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MATH 242 - FUNCTIONAL ANALYSIS
Metric spaces, fixed point theorems, Baire category theorem, Banach spaces,
fundamental theorems of functional analysis, Fourier transform.
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MATH 245 - COMPLEX ANALYSIS
Complex calculus, conformal mapping, Riemann mapping theorem, Riemann
surfaces.
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MATH 251 - GROUPS RINGS & FIELDS
Groups including nilpotent and solvable groups, p-groups and Sylow theorems;
rings and modules including classification of modules over a PID and
applications to linear algebra; fields including extensions and Galois theory.
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MATH 252 - COMMUTATIVE ALGEBRA
Extension and contraction of ideals, modules of fractions, primary
decomposition, integral dependence, chain conditions, affine algebraic
varieties, Dedekind domains, completions.
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MATH 253 - REPRESENTATION THEORY
Representation theory of finite groups, Lie algebras and Lie groups, roots,
weights, Dynkin diagrams, classification of semisimple Lie algebras and their
representations, exceptional groups, examples and applications to geometry and
mathematical physics.
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MATH 261 - ALGEBRAIC TOPOLOGY I
Fundamental group and covering spaces, singular and cellular homology,
Eilenberg-Steenrod axioms of homology, Euler characteristic, classification of
surfaces, singular and cellular cohomology.
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MATH 262 - ALGEBRAIC TOPOLOGY II
Universal coefficient theorems, Kunneth theorem, cup and cap products,
Poincare
duality, plus topics selected from: higher homotopy groups, obstruction
theory, Hurewicz and Whitehead theorems, and characteristic classes.
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MATH 267 - DIFFERENTIAL GEOMETRY
Differentiable manifolds, fiber bundles, connections, curvature,
characteristic classes, Riemannian geometry including submanifolds and
variations of length integral, complex manifolds, homogeneous spaces.
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MATH 272 - RIEMANN SURFACES
Compact Riemann Surfaces, maps to projective space, Riemann-Roch Theorem,
Serre duality, Hurwitz formula, Hodge theory in dimension one, Jacobians, the
Abel-Jacobi map, sheaves, Cech cohomology.
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MATH 273 - ALGEBRAIC GEOMETRY
Affine varieties, projective varieties, Riemann surfaces, algebraic curves,
algebraic groups, sheaf cohomology, singularities, Hodge theory, or
computational algebraic geometry.
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MATH 281 - HYPERBOLIC PDE
Linear wave motion, dispersion, stationary phase, foundations of continuum
mechanics, characteristics, linear hyperbolic systems, and nonlinear
conservation laws.
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MATH 282 - ELLIPTIC PDE
Fourier transforms, distributions, elliptic equations, singular
integrals, layer potentials, Sobolev spaces, regularity of elliptic
boundary value problems.
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MATH 283 - TOPICS IN PARTIAL DIFFERENTIAL EQUATIONS
Hyperbolic conservation laws, pseudo-differential operators, variational
inequalities, theoretical continuum mechanics.
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MATH 287 - PROBABILITY THEORY
Measure theoretic probability. Triangular arrays, weak laws of large
numbers, variants of the Central Limit Theorem, rates of convergence
of limit theorems, local limit theorems, stable laws, infinitely
divisible distributions, general state space Markov chains, Ergodic
theorems, Large deviations, Martingales, Brownian Motion and Donsker's
Theorem.
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MATH 288 - TOPICS IN PROBABILITY
Probability tools and theory, geared towards topics of current
research interest. See synopsis for current description.
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Math Graduate Program *
Mathematics Department *
Duke University
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Mathematics
Department
Duke University, Box 90320
Durham, NC 27708-0320
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