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Mathematics 16:643:574 Numerical Analysis II


The course is normally offered during the Spring semester.
  • Class meeting dates: Please visit the University's academic calendar.
  • Schedule and Instructor: Please visit the University's schedule of classes for the instructor, time, and room.
  • Instructor and Teaching Assistant Office Hours: Please visit the Mathematical Finance program's office hour schedule.

Course Abstract

This course is the second part, independent of 16:643:573 Numerical Analysis I, of a general survey of the basic topics in numerical analysis. We shall study and analyze a number of numerical algorithms for approximating the solution of a variety of generic problems which occur in applications. The course will begin with the description of the solution methods for the linear system of equations. Starting from the direct methods based on the Gaussian elimination, various classical iterative methods such as Gauss-Seidel, Jacobi and SOR will be discussed. Further, we study more advanced iterative methods, multigrid methods in this course. Large portion of the course will be devoted to numerical techniques for optimization, matrix eigenvalues and eigenvectors and numerical solutions to nonlinear equations. As a separate but important technique, finite difference and finite element discretization methods for simple partial differential equations such as Poisson's equations and Heat equations will be studied at the end of the course. Particular emphasis in this course is to interconnect the theorectical results and computer implementation. Students will study not only the solid theoretical backgrounds in developing and understanding the algorithms but also a hands-on experience to implement the methods.

Pre-requisites and Co-requisites

Advanced Calculus, Linear Algebra, and familiarity with differential equations. Numerical Analysis I (16:643:573) is desirable but not required.

Primary Textbooks

A. Quarteroni, R. Sacco, and F. Saleri, Numerical Mathematics, 2nd ed., Springer, 2004.
K. Atkinson, An Introduction to Numerical Analysis, 2nd ed., Wiley, 1989.


Please contact the instructor.

Class Policies

Please see the MSMF common class policies.


Homework assignments in the course consist of both theoretical and computational work. For the computational component, the students should use a language/environment that possesses high level data types so that the students spend more time working with algorithms and not worrying about the details of writing computer code. MATLAB is a good choice. Fortran 77/90/95 and C++ with appropriate class libraries can also be used.

Previous Instructor Course Websites

2010 Richard Falk
2009 Young-Ju Lee
2008 Michael Vogelius
2007 Richard Falk

Weekly Lecturing Agenda and Readings

The lecture schedule below is a sample; actual content may vary depending on the instructor.

1 General course outline and Background for Programming projects.
  Numerical Solution of Systems of Linear Equations.
2 Gaussian Elimination
3 Choleski decomposition and pivoting
4 Perturbation theory for linear systems of equations
5 Matrix iterative method, Gauss-Seidel, Jacobi and SOR
6 Steepest descent and Conjugate Gradient Methods
  Matrix Eigenvalues and Eigenvectors
7 Calculation of Eigenvalues and Eigenvectors
8 Numerical Methods for Eigenvalues and Eigenvectors
9 QR algorithm I
10 QR algorithm II
  Solution of Nonliear Equations
11 Bisection and False Position
12 Secant, Newton's method and Fixed point iterations
13 Local Convergence Results and Order of Convergence
  Solution of Nonliear Systems of Equations
14 Newton and Broyden's method and their convergence
  Minimization Problems
15 Newton, quasi-Newton, Steepest descent and Levenberg-Marguardt method
16 Review
17 Midterm
  Finite Difference Methods
18 Shooting method and Finite Difference methods
19 Analysis of Finite Difference Methods
20 Finite Difference Methods for Elliptic Equations in two dimensions
21 Finite Difference Methods for Heat Equations
  Finite Element Methods
22 ntroduction to Finite Element Methods
23 Finite Element Method I
24 Finite Element Method II
25 Finite Element Method for Parabolic Equations
  Multigrid Methods
26 Brief Review on Iterative Methods, Gauss-Seidel and Jacobi
27 Introduction of Multigrid Methods for Eliptic Equations
28 Implementation of Multigrid Methods for Eliptic Equations
29 Convergence of Multigrid Methods
30 Review

Library Reserves

All textbooks referenced on this page should be on reserve in the Hill Center Mathematical Sciences Library (1st floor). Please contact the instructor if reserve copies are insufficient or unavailable.

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Mathematical Finance Master's Program

Department of Mathematics, Hill 348
Hill Center for Mathematical Sciences
Rutgers, The State University of New Jersey
110 Frelinghuysen Road
Piscataway, NJ 08854-8019

Email: finmath (at)
Phone: +1.848.445.3920
Fax: +1.732.445.5530