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We present a conceptually clear introduction to quantum theory at a level suitable for exceptional high-school students. It is entirely self-contained and no university-level background knowledge is required. The lectures were given over four days, four hours each day, as part of the International Summer School for Young Physicists (ISSYP) at Perimeter Institute, Waterloo, Ontario, Canada. On the first day the students were given all the relevant mathematical background from linear algebra and probability theory. On the second day, we used the acquired mathematical tools to define the full quantum theory in the case of a finite Hilbert space and discuss some consequences such as entanglement, Bells theorem and the uncertainty principle. Finally, on days three and four we presented an overview of advanced topics related to infinite-dimensional Hilbert spaces, including canonical and path integral quantization, the quantum harmonic oscillator, quantum field theory, the Standard Model, and quantum gravity.
We give an elementary introduction to classical and quantum bosonic string theory.
These are lecture notes for the course Poisson geometry and deformation quantization given by the author during the fall semester 2020 at the University of Zurich. The first chapter is an introduction to differential geometry, where we cover manifold
Lecture notes for the course Batalin-Vilkovisky formalism and applications in topological quantum field theory given at the University of Notre Dame in the Fall 2016 for a mathematical audience. In these lectures we give a slow introduction to the pe
A relativistic density-functional theory based on a Fock-space effective quantum-electrodynamics (QED) Hamiltonian using the Coulomb or Coulomb-Breit two-particle interaction is developed. This effective QED theory properly includes the effects of va
These are lecture notes written at the University of Zurich during spring 2014 and spring 2015. The first part of the notes gives an introduction to probability theory. It explains the notion of random events and random variables, probability measure