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1. Course title

Suurenergiafysiikan laskentamenetelmiä
Beräkningsmetoder i högenergifysiken
Computing Methods in High Energy Physics

2. Course code


Aikaisemmat leikkaavat opintojaksot 530226 Suurenergiafysiikan laskentamenetelmiä, 5 op.

3. Course status: optional

-Which degree programme is responsible for the course?
Master’s Programme in Particle Physics and Astrophysical Sciences

-Which module does the course belong to?
PAP300 Advanced Studies in Particle Physics and Astrophysical Sciences (optional for Study Track in Particle Physics and Cosmology)

-Is the course available to students from other degree programmes?

4. Course level (first-, second-, third-cycle/EQF levels 6, 7 and 8)

Master’s level, degree programmes in medicine, dentistry and veterinary medicine = secondcycle
degree/EQF level 7
Doctoral level = third-cycle (doctoral) degree/EQF level 8

-Does the course belong to basic, intermediate or advanced studies (cf. Government Decree
on University Degrees)?
Advanced studies

5. Recommended time/stage of studies for completion

Third or fourth year, after having basic knowledge in particle physics and programming, or the same spring you are applying for a CERN internship.

6. Term/teaching period when the course will be offered

The course will be offered in the spring term, in III and IV periods.

7. Scope of the course in credits

5 cr

8. Teacher coordinating the course

Sami Lehti

9. Course learning outcomes


You will learn tools used in the data/physics analysis in a typical High Energy Physics experiment.

10. Course completion methods


Exercises and final project.

11. Prerequisites


Programming skills (any programming language).

Familiarity with the Linux programming environment and introduction to particle physics recommended.

12. Recommended optional studies


13. Course content


The course provides an introduction to learning to use software used in a typical High Energy Physics experiment. The CMS experiment is used as an example.


Topics covered include:


Short review of UNIX



Combining languages

Cross section and branching ratio calculations Event generators Detector simulations Reconstruction Fast simulation Grid computing

14. Recommended and required literature


Lecture notes

A book on C++ for reference

15. Activities and teaching methods in support of learning

Weekly lectures and exercises (individual work). Home exam.

16. Assessment practices and criteria, grading scale


Final grade is based on exercises (1/3) and home exam (2/3).

17. Teaching language


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