Hans Maassen explores the nature of information in quantum-mechanical systems, such as atoms, light particles and crystal lattices. He approaches this information using an extended probability calculus in which random variables do not have to satisfy the commutative law XY = YX. Many concepts from probability theory can be transported to this new area, leading occasionally to surprising results. For example, Maassen was able to expand Heisenberg’s uncertainty principle, which is concerned with the variances of non-commuting random variables, to a relation between their Shannon information quantities, and he invented a stochastic analysis for particle scattering. In his lectures, Maassen will introduce Master’s students to this kind of probability theory.

At present, Maassen is working on the description of quantum-mechanical correlations (entanglement) in particle clusters and their symmetries, in which he is collaborating with other Amsterdam-based mathematicians. He also seeks collaboration with physicists at the UvA and computer scientists at the National Research Institute for Mathematics and Computer Science (CWI) in the quest for hardware for the quantum computers of the future, as well as the algorithms needed to programme them.

Maassen has been affiliated with Radboud University Nijmegen since 1986, where he has been associate professor of Probability and Statistics since 1999. In 1998 and 2000, Maassen was awarded research grants from the Netherlands Organisation for Scientific Research (NWO).

He is currently involved in a SERC research project at Nottingham University entitled ‘Large deviations and dynamical phase transitions in open quantum systems’. He is also co-authoring a series of books on quantum Markov chains in collaboration with Prof. Burkhard Kümmerer of the Technische Universität Darmstadt. Maassen has published extensively in various scientific journals, including Journal of Functional Analysis, Journal of Probability Theory and Related Fields, Physical Review Letters and Quantum Information Processing.