Selected Tools of Theoretical Physics IA (first half)
Instructor
- Pok Man Lo
- 428 Institute of Theoretical Physics, University of Wroclaw
- email me
- course website
Time and Place
- Every Tuesday 0845-1200 @ IFT Rm 422
Course Description
This first half of the course introduces essential numerical approaches to physics problems. We begin with the fundamentals of solving differential equations, progress to Monte Carlo methods, and explore foundational topics in quantum many-body systems.
We employ a problem-based approach: lectures and exercises are woven together, and we learn by working on concrete problems. Selected applications include the logistic equation, the Lorenz model, the Schroedinger equation, the Ising model, and percolation theory.
Helps needed
Feel free to comment and connect.
Grading Scheme
TBA
Textbooks
computational physics
- J.F. Boudreau and E.S. Swanson, Applied Computational Physics (Oxford University Press, 2017)
- Rubin H. Landau, Manuel J. Páez Cristian and C. Bordeianu, Computational Physics
Supplementary texts
- D. Kincaid and W. Cheney, Numerical Analysis: Mathematics of Scientific Computing
- N.J. Giordano and H. Nakanishi, Computational Physics
- W.R. Gibbs, Computation in Modern Physics
- Heinz J Rothe, Lattice Gauge Theories
Topics
Primary topics to be discussed are
- Basic Python / Julia programming
- Applied computational physics
- Solution to the Schroedinger Equation
- Monte Carlo method
- Percolation, Ising model, and Beyond: QMs and QFTs and Many-body problems
Preparation and Help
This course is not about hard-core programming, nor about solving large scale computing problems. Mostly we will be writing little scripts for toy numerical experiments to gain understanding of some quantum mechanical problems. (The Julia language is easy to learn even for beginners in programming. Helps will be provided during tutorial sessions. Also, you are free to choose any language you like as long as you can explain and communicate your work effectively.)
The presentation of physics topics aims to be self-contained, but it is best to come prepared. This means remembering your undergraduate classical and quantum physics.
For documentation of codes and works, use of latex and markdown is recommended.