TANA22 · 8 credits · Basic level (G1F) · Matematik, Tillämpad matematik
Scientific Computing
Active · next start HT 2026
83%
passed the latest ordinary exam
TEN1 · 31 Oct 2025 · 6 students
93%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 29 students
Part of 1 programme
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
93% passed · 29 students
- 83%6
- 83%6
- 100%5
- 100%5
- 100%7
Re-exams
No sittings with at least 5 students.
- Get 4 or 5: 79% (29 students)
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
UPG1 Project work
- G
Main rounds
100% passed · 20 students
- 100%7
- 100%6
- 100%7
Later rounds
No sittings with at least 5 students.
Show small sittings (5)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%4
- 100%1
- 100%1
- 100%3
Hand-in or lab
LAB1 Laboratory work
- G
Main rounds
100% passed · 19 students
- 100%7
- 100%6
- 100%6
Later rounds
No sittings with at least 5 students.
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%4
- 100%1
- 100%1
- 100%3
- 100%1
About the course
Aim
Computational mathematics is the art of developing and analysing numerical algorithms for solving mathematical problems in for example natural science and technology. After finishing the course the student should be able to
- explain and separate fundamental terms and concepts in computational mathematics
- use a selection of numerical algorithms for solving given mathematical problems
- estimate the accuracy of calculated results
- use mathematical software
Content
- Error analysis: Round off, truncation, error propagation and cancellation.
- Floting point numbers: Floating point systems, machine epsilon and round off.
- Linear systems of equations: LU decomposition, pivoting, backward and forward substitution, condition and arithmetic complexity.
- Interpolation and approximation: Newton's and Lagrange's methods, splines, Horner's scheme, least squares and overdetermined systems, Runges fenomenon,Chebyshevpolynom.
- Differentiation and integration: Difference approximation, order of accuracy, the trapezoidal rule and Simpon's rule, Gauss quadrature.
- Ordinary differential equations: Runge Kutta methods, local and global truncation error, stability and convergence. Finite difference method.
- Non-linear equations: The bisection method, Newton-Raphson's method, fixed point iteration, condition and order of convergence.
- Examiner
- Andrew Winters
- Scheduled hours
- 58 h
- Main field of study
- Matematik, Tillämpad matematik