Computational Physics

Objective

This is one of the options that students enrolled in the course PRODEF039 — Engineering Physics of Data and Computation can choose. It involves studying topics in Computational Physics adapted to the research that each student is conducting within their Ph. D. dissertation. Thus, it is expected that the students develop skills on simulation of the physical systems related to their research.

Program

1. Numerical solution of differential equations using the Python programming language and the Maxima Computer Algebra System.
2. Computing eigenvalues and eigenfunctions of the Schrödinger equation.
3. Monte Carlo methods.
4. Solving partial differential equations by the method of finite differences.

Bibliography

• Linge S. & Langtangen H. P. (2020). Programming for Computations – Python, 2nd edition, Springer, ISBN: 978-3-030-16876-6.
• Langtangen H. P. (2016). A Primer on Scientific Programming with Python, 5th edition, Springer, ISBN: 978-3-662-49886-6.
• Landau, R. H., Páez, M. J. & Bordeianu, C. (2024). Computational Physics: Problem Solving with Python, 4th edition, Wiley, ISBN: 978-3-527-41425-3.
• Kiusalaas, J. (2005). Numerical methods in engineering with Python. Cambridge University Press, ISBN: 978-0-521-85287-6.

Aditional Material

• Métodos Numéricos com Maxima (in Portuguese).
• Simulações com VPython (in Portuguese).