Computational Quantum Physics
Computergestützte Quantenphysik
6 CPWinterEN
Prerequisites
Recommended, as written
Knowledge of quantum mechanics on the level of a physics bachelor. Knowledge of C++ or python.
Contents
Numerical approaches:Lancos algorithm, Monte Carlo algorithm, Machine Learning, Numerov algorithm, Cranck-Nicolson Algorithm, Runge-Kutta algorithm, etc. Approximate solutions of the time-dependent Schrödinger equation. Calculations of the temporal evolution of a wave-function, electron density, spin state, spectra, taking into account decoherence.Programming languages: C++ or python.
Learning outcomes
After successfully completing the module, students will be able to solve complex physical problems by means of computer coding and simulations. Students are familiar with various numerical methods that are used in quantum mechanics, as well as in other fields. Students are extensively experienced in writing codes for solving problems numerically. Students have in-depth knowledge of quantum mechanics and can deal with quantum dynamical processes.
Assessment
Prerequisite: • Successful completion of of exercise assignments (50% must be reached) Final module examination: • Written examination, 90 min. (Solving tasks on the computer )
Literature (6)
- Philipp O.J. Scherer. Computational Physics. Simulation of Classical and Quantum Systems.
- Rubin H. Landau, Manuel Jose Paez, Cristian C. Bordeianu. Computational Physics. Problem Solving with Computers.
- Jos Thijssen. Computational Physics.
- Joshua Izaac and Jingbo Wang. Computational Quantum Mechanics.
- Tannor, David J. Introduction to Quantum Mechanics: A Time-Dependent Perspective.
- F. Grossmann. Theoretical Femtosecond Physics. Atoms and Molecules in Strong Laser Fields.
Remarks
• Study programme Physics M.Sc.: Compulsory elective module in the complexes „Physical Specialization with Theoretical Focus“, topic area „Theory, Simulation and further topics“
Source: BTU's module description · retrieved 29 Sep 2026Original