Abstract
Variational quantum algorithms are particularly promising early applications of quantum computers
since they are comparatively noise tolerant and aim to achieve a quantum advantage with only a few
hundred qubits. They are applicable to a wide range of optimization problems arising throughout the
natural sciences and industry. To demonstrate the possibilities for the aeroscience community, I will
describe how variational quantum algorithms can be utilized in computational fluid dynamics in this talk.
I will discuss how classical fluid dynamics problems are translated into quantum variational algorithms by
using matrix product operators as a programming paradigm. The intricate multi-scale nature, describing the
coupling between different-sized eddies in space and time, allows us to design an efficient structure-resolving t
ensor network based description of turbulent flows and compute their dynamics. I will show how boundary conditions
can be incorporated and provide estimates for how the runtimes of the resulting quantum algorithms scale with
problem size. Importantly, I will demonstrate that only a logarithmically small number of qubits are required.
I will then then discuss several fundamental examples demonstrating the power of these quantum algorithms.
Finally, I will investigate the power of tensor network based classical algorithms for computational fluid dynamics
that arise as an intermediate step in the translation to fully quantum algorithms.
Bio
Professor Dieter Jaksch obtained his PhD in theoretical quantum optics and ultracold atom physics from the
University of Innsbruck, Austria in 1999. He moved to the University of Oxford (UK) as a Lecturer in 2003,
became a Reader in 2008 and a Professor in 2010. He moved to the University of Hamburg (Germany) in 2021
where he leads a research group on the theory of many-body quantum optical systems. He still holds a part-time
researcher position at Oxford.
Professor Jaksch works in the area of strongly correlated non-equilibrium quantum systems with a focus on utilizing
them in quantum computing and for generating functionalities in quantum matter. His early research helped initiating
the area of quantum simulation withy ultracold atoms in optical lattices. More recently, he has extended his
research interests to include the study of non-equilibrium dynamics in optically driven condensed matter and
the development of variational quantum computing algorithms for solving non-linear optimization problems.
Professor Jaksch authored about 200 scientific publications that have attracted over 25000 citations. He has been a
principal investigator on several national and international research programs like the ERC Synergy Grant QMAC or
the UK Quantum Hub NQIT. He currently leads the EU Quantum Flagship project QCFD on Quantum Computational Fluid Dynamics.
He was awarded the Thomas Young Medal and Prize by the Institute of Physics in 2018.
