Numerical Analysis: Numerical Methods for Differential Equations

Education facts

Code: NUMN32

<p>The course provides a basic introduction to numerical analysis for differential equations. This includes design, analysis, implementation and application of numerical methods for initial value problems, boundary value problems and various types of partial differential equations.</p><p>The course treats:</p> <ul> <li>Methods for time integration: Euler’s method, the trapezoidal rule. Multistep methods: Adams' methods, backward differentiation formulae.</li> <li>Explicit and implicit Runge-Kutta methods.</li> <li>Error analysis, stability and convergence.</li> <li>Stiff problems and A-stability. Error control and adaptivity.</li> <li>The Poisson equation: finite differences and the finite element method.</li> <li>Elliptic, parabolic and hyperbolic problems.</li> <li>Time dependent partial differential equations: numerical schemes for the diffusion equation.</li> <li>Introduction to difference methods for conservation laws.</li> </ul>

Entry requirements

Admission to the course requires English 6/b and at least 90 credits of which at least 45 credits should be in mathematics and/or numerical analysis, including the courses NUMA01 Computational Programming with Python, 7.5 credits, MATB22 Linear Algebra 2, 7.5 credits, and MATB21 Analysis in Several Variables 1, 7,5 credits, or equivalent. In addition to these 45 credits, also one of the courses MATC12 Ordinary Differential Equations I, 7.5 credits, NUMA41 Numerical Analysis, Basic Course, 7.5 credits, and FYSB21 Physics: Mathematical Methods for Vibrations, Waves and Diffusion, 7.5 credits, or equivalent, is required.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Numerical Analysis: Numerical Methods for Differential Equations

  Lund University

  Start date: 2 November 2026

  End date: 17 January 2027

  Pace of study: 50 %