The aim of this graduate course is to introduce advanced numerical methods such as different techniques for differentiation, integration, and numerical methods for solving ODEs and PDEs as well as methods for solving the Schrodinger equation of quantum-many body systems. The course also covers topics that have application in condensed matter physics such as Monte Carlo, Exact Diagonalization, Tensor Network, and Deep Neural networks to Master and Ph.D. students.
To access the course materials and assignments, please visit the Moodle of the course.
The aim of this course is to introduce mathematical methods to undergraduate physics students to prepare them for future courses such as the theory of Electromagnetism and Quantum Mechanics.
To access the course materials and assignments, please visit the Moddle of the course: