CWI highly values education. CWI researchers not only supervise and inspire the CWI PhD students, but also aim at contributing to teaching Master's students at universities. See the overview of CWI's current involvement in teaching courses in the Netherlands below.
CWI is a research institute and does not have education as an institutional task. However, many of the senior researchers of CWI contribute to education via an affiliation or part-time appointment at one of the Dutch universities.
The courses they teach are listed below in chronological order, starting with the earliest upcoming course.
A major claim to fame of quantum computers is that they will be able to solve some problems significantly faster than believed to be possible on a classical computer. The design of further quantum algorithms is an exciting active field of research, and there is still much left to explore in understanding which problems can be sped up by quantum computers, and by how much.
In this course, students will learn about various advanced topics in quantum algorithms and algorithm design, as well as techniques for understanding for which problems it is possible to get a quantum speedup, and by how much.
In this course we build the theory of Schur-Weyl duality, highest-weight vectors, Clebsch-Gordan and Kronecker coefficients, moment polytopes, and symmetric polynomials, and then study various areas of applications including quantum information theory and quantum algorithms, optimization, and algebraic complexity theory.
Additive combinatorics is a relatively new area of mathematics that brings together topics such as combinatorial and analytic number theory, Ramsey theory, harmonic analysis, graph theory, extremal combinatorics, algebraic methods, ergodic theory and probability theory. The area has strong connections with theoretical computer science, including quantum computing. A centerpiece result is the Green-Tao theorem, which asserts that the prime numbers contain arbitrarily long arithmetic progressions. A general theme that drives much of the area has to do with relating quantitative notions of approximate algebraic structure.
Quantum Computing
This course offers a mathematical introduction to Quantum Information Theory. We will start with the fundamentals (such as quantum states, measurements, and channels) and then discuss some more advanced topics (such as compression of quantum information and entanglement theory).
In this course, we quickly review the basics of probability theory and introduce concepts such as (conditional) Shannon entropy, mutual information and entropy diagrams. Then, we prove Shannon's theorems about data compression and channel coding. An interesting connection with graph theory is made in the setting of zero-error information theory. We also cover some aspects of information-theoretic security such as perfectly secure encryption, and draw some connections to machine learning.
A major claim to fame of quantum computers is that they will be able to solve some problems significantly faster than believed to be possible on a classical computer. The design of further quantum algorithms is an exciting active field of research, and there is still much left to explore in understanding which problems can be sped up by quantum computers, and by how much.
In this course, students will learn about various advanced topics in quantum algorithms and algorithm design, as well as techniques for understanding for which problems it is possible to get a quantum speedup, and by how much.
