Quantum Information Processing
Jun.-Prof. Christoph Hirche
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General
Supervisor:
Appointments (every summer semester, including lecture and exercise classes: 5 CPs):
- Lecture: see
- Exercise: see
Exam:
- Oral exam
- Appointments: will be announced at the beginning of the summer semester
Lecture slides: see
Exercise materials: see
Content of the lecture
Students will understand the basic concepts of quantum information processing. In particular, they will have a broad overview of the tools needed to dive deeper into topics such as quantum computing, quantum information theory and quantum machine learning. The focus will be on theoretical considerations of what we can achieve with quantum computing hardware and understanding the differences to traditional information processing. To achieve this, students will also solidify and widen their knowledge in mathematical tools, in particular linear algebra. At the end of the course students will be able to understand and explain current research in the field and independently solve problems related to it.
Topics
- Quantum states, quantum channels, density matrix formalism, measurements, distance measures;
- no-cloning theorem;
- quantum circuits;
- quantum algorithms: quantum teleportation, super dense coding, Fourier transform, Shor's factoring algorithm; Grover's search algorithm;
- noisy quantum circuits, bounds from information theory;
- Entanglement and non-Locality, uncertainty relations;
- quantum error-correction;
- quantum machine learning.
Requirements
We recommend that you know the foundations of
- mathematical basics (especially linear algebra)
- (optional) Quantum mechanics
- (optional) information theory
in order to attend the course.
This course as well as the exercises will be in English only.
Literature
- Quantum Computing: Lecture Notes, Ronald de Wolf, https://arxiv.org/abs/1907.09415
- Quantum Information, Mark M. Wilde, https://arxiv.org/abs/1106.1445
- Quantum Computation (Lecture Notes), John Preskill, http://theory.caltech.edu/~preskill/ph229/
