Schedule, syllabus and examination date

Choose semester

Course content

An introduction to numerical methods which are used in solving problems in physics and chemistry, including solutions of differential equations, matrix operations and eigenvalue problems, interpolation and numerical integration, modeling of data and Monte Carlo methods.

Learning outcome

The course gives an introduction to several of the most used algorithms from numerical analysis to solve problems in the Sciences. These algorithms cover topics such as advanced numerical integration using Gaussian quadrature, Monte Carlo methods with applications to random processes, Markov chains, integration of multidimensional integrals and applications to problems in statistical physics and quantum mechanics. Other methods which are presented are eigenvalue problems, from the
simple Jacobi method to iterative Krylov methods. Popular methods from linear algebra such as the LU-decomposition method and spline interpolation are also discussed. A large fraction of the course is also devoted to solving ordinary differential equations with or without boundary conditions and finally methods for solving partial differential equations. The student will thus develop a familiarity with some of the most used algorithms in Science. Several examples of problems in physics
and chemistry will be used in order to demonstrate various numerical methods. The examples span over several fields, from materials science to solid state physics, atomic physics, astrophysics, nuclear physics and eigenvalue problems in quantum chemistry. The course is project based and through the various projects, normally five, the participants will be exposed to fundamental research problems in these fields, where the aim of the last project is to reproduce state of the art scientific
results. The students will learn to develop and structure codes for studying these systems, develop a critical understanding of the capabilities and limits of the various numerical methods, get acquainted with supercomputing facilities and parallel computing and learn to handle scientific projects. The students will have to choose between C++, Python or Fortran2003 as computing languages. They will also learn how to interface python programs with C++ or Fortran programs.

A good scientific and ethical conduct is emphasized throughout the course.

Admission

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

Prerequisites

Formal prerequisite knowledge

In addition to fulfilling the Higher Education Entrance Qualification, applicants have to meet the following special admission requirements:

One of these:

  • Mathematics R1
  • Mathematics (S1+S2)

And and in addition one of these:

  • Mathematics (R1+R2)
  • Physics (1+2)
  • Chemistry (1+2)
  • Biology (1+2)
  • Information technology (1+2)
  • Geosciences (1+2)
  • Technology and theories of research (1+2)

The special admission requirements may also be covered by equivalent studies from Norwegian upper secondary school or by other equivalent studies. Read more about special admission requirements (in Norwegian).

Recommended previous knowledge

Knowledge corresponding to the following courses at the University of Oslo: INF1000 - Introduction to object-oriented programming (continued), FYS-MEK1110 - Mechanics, MOD100, MAT1100 - Calculus, MAT1110 - Calculus and linear algebra and MAT1120 - Linear algebra.

Overlapping courses

10 credits overlap with FYS4150 - Computational physics

10 credits overlap against FYS210.

Teaching

The course is offered for one semester and comprises 4 hours of lectures per week, in addition to laboratory exercises aided by the use of a computer. The course will also include five projects that students will receive feedback on.

Examination

Five projects, including three that will each count 1/3 of the grade. There will be no written or oral examination, only a portfolio assessment.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Explanations and appeals

Resit an examination

Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.

Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Evaluation

The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation.

Other

Course evaluation

Feedback from our students is an essential to us in our efforts to ensure and further improve the high quality of our programmes and courses. As a student at the University of Oslo you will therefore be asked to participate in various types of evaluation of our courses, facilities and services. All study programmes and courses are subject to continuous evaluation. At regular intervals we also ask students enrolled in a particular programme or course to participate in a more comprehensive, in-depth evaluation of their programme or course. The next evaluation of this course will be carried out during the autumn term of 2005.

Facts about this course

Credits

10

Level

Bachelor

Teaching

Every autumn

Examination

Every autumn

Teaching language

Norwegian (English on request)