Found 4 relevant results in 1.29s where lecturer="Mark Hannes Fischer"
This course provides an introduction to simulation methods for quantum systems. Starting from the one-body problem, a special emphasis is on quantum many-body problems, where we cover both approximate methods (Hartree-Fock, density functional theory) and exact methods (exact diagonalization, matrix product states, and quantum Monte Carlo methods).
This course is an introduction to the basic concepts of machine learning, including supervised and unsupervised learning with neural networks, reinforcement learning, and methods to make the learned results interpretable. The material is presented with scientific research applications in mind, where data has often very peculiar structure and quantitative accuracy is paramount.
Superconductivity: thermodynamics, London and Pippard theory; Ginzburg-Landau theory: spontaneous symmetry breaking, flux quantization, type I and II superconductors; microscopic BCS theory: electron-phonon mechanism, Cooper pairing, quasiparticle spectrum, thermodynamics and response to magnetic fields. Josephson effect: superconducting quantum interference devices (SQUID) and other applications.
This course offers an introduction to unconventional superconductivity along a microscopic and a phenomenological line, based on the generalized BCS and Ginzburg-Landau theory, respectively. Concepts of symmetry and topology are essential to characterize different superconducting phases together with their experimental signatures which will be discussed for specific exemplary material classes.