PHYSICS LABORATORY (UNIT 2)
Learning outcomes of the course unit
The course will provide an overview of computational tools useful for making predictions from the theoretical modeling (formalization) of physical problems. A particular attention will be dedicated to simulation methods.
Course contents summary
The course will show how to derive physical prediction (numerical values) from a mathematical model and, consequently, as how to estimate parameters of a mathematical model from measurements.
The main topics of the course are:
1) General issues of numerical calculation and implementation of algorithms.
2) software tools to implement numerical algorithms (matlab/python/C/C++).
3) Methods of solution of ordinary differential equations and the partial derivatives.
4) Statistical methods for data processing.
5) The problems resulting from the extraction of the parameters of a mathematical model from the experimental data.
Notes provided by the lecturer.
Formal presentation of the topics will be followed by group sessions in which students will experiment (by implementing the numerical code) benefit and problems of the presented simulation algorithms.
Assessment methods and criteria
Evaluation will be based on tests during the course. At the end of the course to every student will be assigned a problem to be solved via numerical simulations. Students will present their solution, together with a report, in front of their collegues.