Exam Overview
- Exam Focus: Numerical Analysis
 - Exam Format: 4-Hour Written Exam
 - View Past Numerical Analysis Exams »
 
Syllabus Topics
This exam will cover the following topics:
- General Numerical Methods
 - Numerical Linear Algebra
 - Numerical Methods for Ordinary Differential Equations
 - Numerical Methods for Partial Differential Equations
 
General Numerical Methods
Principles of Numerical Mathematics
- Well-posedness and condition number of a problem
 - Stability and convergence of numerical methods
 - Machine representation of numbers
 
Rootfinding for Nonlinear Equations
- The bisection, the secant and Newton's methods
 - Fixed-point iterations
 - Solution of nonlinear systems of equations
 
Polynomial Interpolation
- Lagrange polynomials (and their Newton form)
 - Hermite interpolation
 - Approximation by splines
 
Numerical Differentiation and Integration
- Finite-difference approximations of derivatives
 - Midpoint, trapezoidal, Simpson, Newton-Cote quadratures
 - Richardson extrapolation
 
Orthogonal Polynomials in Approximation Theory
- Approximation of functions by Fourier series
 - Gaussian integration and interpolation
 - Fourier trigonometric polynomials
 
Numerical Linear Algebra
Fundamentals
- Orthogonal vectors and matrices
 - Vector and matrix norms
 - The singular value decomposition (SVD)
 - Conditioning and condition number
 
Least Squares Problem
- Normal equations
 - QR factorization
 
Solutions of Linear Systems of Equations
- Direct methods - LU factorization; Cholesky factorization
 - Iterative methods - Jacobi, Gauss-Seidel, SOR, Conjugate Gradient
 
Eigenvalue Problem
- Power method
 - QR method for symmetric matrices
 
Numerical Methods for Boundary Value Problems
- Boundary value problems for ODEs
 - Boundary value problems for elliptic PDEs
 
Numerical Methods for Ordinary Differential Equations
Numerical Methods for Initial Value Problems
- One-step methods
 - Linear multistep methods
 - Runge-Kutta methods
 - Consistency, stability and convergence
 
Numerical Methods for Partial Differential Equations
Finite-Difference Methods
- Accuracy and derivation of spatial discretizations
 - Explicit and implicit schemes for parabolic equations
 - Consistency, stability and convergence, Lax equivalence theorem
 - Von Neumann stability, amplification factor
 - CFL condition for hyperbolic equations
 - Upwind schemes for hyperbolic equations
 - Leapfrog, Lax-Friedrichs and Lax-Wendroff schemes
 - Crank-Nicolson scheme for the heat equation
 - Discrete approximation of boundary conditions
 
Finite Element Methods: Derivation and Basic Properties
Finite Volume Methods: Derivation and Basic Properties
Splitting Methods
- Dimensional splitting, ADI methods
 - Operator splitting methods for convection-diffusion equations
 
References
- Numerical Analysis, 6th edition, by Richard L. Burden and J. Douglas Faires
 - An Introduction to Numerical Analysis, 2nd edition, by Kendall E. Atkinson
 - Numerical Mathematics, by Alfio Quarteroni, Riccardo Sacco and Fausto Saleri
 - Numerical Linear Algebra, by Lloyd N. Trefhen and David Bau
 - Matrix Computations, by Gene H. Golub and Charles F. Van Loan
 - Finite Difference Schemes and Partial Differential Equations, by John C. Strikwerda
 - Finite Difference Methods for Ordinary and Partial Differential Equations, by Randall J. LeVeque
 - Numerical Methods for Evolutionary Differential Equations, by Uri M. Ascher