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Lund University
Numerical Analysis: Numerical Methods for Partial Differential Equations
<p>The course is an optional course for second-cycle studies for a Master's degree in mathematics with a specialisation in numerical analysis, as well as for a master's degree in computational science. The purpose of the course is for the students to acquire in-depth knowledge of numerical methods for partial differ…
- Higher education
- Information unavailable
- 18 January 2027
- Lund
- Information unavailable
- 50 %
Overview
<p>The course is an optional course for second-cycle studies for a Master's degree in mathematics with a specialisation in numerical analysis, as well as for a master's degree in computational science. The purpose of the course is for the students to acquire in-depth knowledge of numerical methods for partial differential equations and get the opportunity to work with relevant computational problems and software in connection with partial differential equations.</p><p>The course gives an introduction to error estimates, convergence and stability, as well as existence and regularity of solutions to elliptic differential equations (PDEs). This is followed by an introduction to DUNE-FEM which discusses how elliptic PDEs can be discretized using the Finite Element Method (FEM).</p> <p>The course treats:</p> <ul> <li>Weak theory for elliptic PDEs: existence and error estimates</li> <li>Construction of Finite Elements, e.g. discretization grids, reference elements, degree-of-freedom (DOF) mappings</li> <li>Unified Form Language (UFL) for description of weak forms of partial differential equations</li> <li>Parallelization of Finite Element methods using domain decomposition</li> <li>Adaptive Finite Element</li> </ul>
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Entry requirements
Admission to the course requires English 6/b and at least 90 credits in natural sciences or engineering, of which at least 45 credits should be in mathematics and/or numerical analysis, including knowledge corresponding to the courses NUMA01 Computational Programming with Python, 7.5 credits, and NUMN32 Numerical Methods for Differential Equations, 7.5 credits.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2027-01-18
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.lu.numn33.52572.20271
- Last checked
- 2026-09-23T10:38:33.477975+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.numn33.52572.20271
- Offering identity in the source
- e.uoh.lu.numn33.52572.20271
- Education-form source code
- HS
- Education code in the source
- NUMN33
- Change time according to the source
- 2026-07-06T16:50:09
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.