MONTECARLO METHODS IN EXPERIMENTAL PHYSICS
Academic year2016/17
CoursePHYSICS
Code185BB
Credits6
PeriodSemester 2
LanguageItalian
| Modules | Area | Type | Hours | Teacher(s) |
| METODI MONTECARLO NELLA FISICA SPERIMENTALE | FIS/01 | LEZIONI | 36 | |
Programma non disponibile nella lingua selezionata
Knowledge
Students are expected to acquire:
The mathematical basis of statistical sampling as a tool for computational problem.
Skillness in applying pseudo-random number techiniques for simulation in physics.
Skill in the realization of algorithms based on pseudo-random number
Assessment criteria of knowledge
During the oral exam the student must demonstrate the ability to approach a circumscribed research problem, and organise an effective exposition of the results.
Methods:
- Final oral exam
- Written report
Further information:
During the exame student must be able to demonstrate to Know the mathematical basis of the statistical sampling method (50 % weight) and must be able to present and discuss with property of expression a specific problem (50% weight) assigned by the teacher taking into account the interests of the student.
Teaching methods
Delivery: face to face
Learning activities:
- attending lectures
- participation in seminar
- preparation of oral/written report
- individual study
- group work
Attendance: Advised
Teaching methods:
- Lectures
- Seminar
- project work
Syllabus
Statistical sampling, Von Neumann optimization Algorithm, Numerical integration,
Application in High Energy Physics and Medical Physics: A study of cerenkov counter,
simulation of a spectrometer, Bragg Peak simulation, positron range in water, delta rays simulation, simulation of limiting resolution effect in the case of PET (positron emission tomography).
Since Montecarlo Methods play role in a wide range of application, students are invited to attend seminars illustrating how the methods is used in other Physics fields (Astro-physics, Astro-particle physics, bio-physics)
Bibliography
A. Rotondi et al. , "Probabilita`, Statistica e Simulazione " Ed. Springer.
and various Articles taken form the Scientific literature.
Updated: 14/11/2016 17:27
