MS1: Quantum Computing for CFD Applications
Matthias Möller, Julia Kowalski, Norbert Hosters, Rakesh Sarma, and Jaka Vodeb
Abstract
Computational Fluid Dynamics (CFD) has been among the first disciplines to explore emerging compute technologies like vector processors in the 1990s and early 2000s and multi-core CPUs and GPUs since the mid-2000s to push the capabilities of simulation- based fluid flow analysis to their limits. Every new compute paradigm required a modernization of CFD codes and has brought a plethora of advanced methodologies to date ranging from classical grid-based approaches to particle and hybrid methods.
An emerging compute technology that promises to become a game-changer in the quest for ultimate compute power is quantum computing. In contrast to vector processors and multi- core CPUs and GPUs, quantum computing requires more than the adaption of established codes. The potential power of quantum computers will come from the strict exploitation of quantum mechanical effects such as superposition, entanglement, and quantum parallelism. This requires us to rethink the usefulness of established approaches such as grid-based Navier-Stokes solvers as a methodological base for future quantum-CFD applications.
The aim of this mini-symposium is to bring together pioneers and interested stakeholders in quantum-CFD to discuss recent advances in this young discipline. In particular, we welcome contributions in the fields of quantum Navier-Stokes methods, quantum Lattice Boltzmann methods, hybrid quantum-classical approaches, and quantum Machine Learning such as Quantum Gaussian Process emulation and hybrid workflows for Hyperparameter Optimization. Due to the early stage of the field, contributions can range from theoretical complexity analysis results to practical implementations of algorithms on quantum computers or their simulators. We also encourage newcomers in the field to pitch their ideas to stimulate open discussions and thereby contribute towards nurturing a stable quantum- CFD community.
Matthias Möller - Delft University of Technology, Department of Applied Mathematics
Matthias Möller is Associate Professor of Numerical Analysis at Delft University of Technology, The Netherlands. He holds a PhD degree in Mathematics from TU Dortmund University and joined TU Delft in 2013. He is currently leading the quantum-CFD lab which is a joined research initiative between TU Delft and Fujitsu Limited, Japan. Matthias’ research focusses on the development of numerical methods for fluid flow applications both on conventional and emerging compute technologies. His particular interest is in finite element and isogeometric analysis as well as lattice Boltzmann methods. He has (co-)authored more than 70 research articles and book chapters and is member of the advisory council of the DLR Quantum Computing Initiative.
Julia Kowalski - RWTH Aachen University, Faculty of Mechanical Engineering
Julia Kowalski is Professor at RWTH Aachen University’s Faculty of Mechanical Engineering, where she leads the Chair of Methods for Model- based Development in Computational Engineering (MBD). She holds a PhD from the Seminar of Applied Mathematics at ETH Zurich and joined RWTH in 2021. Julia’s research concerns computational methods for goal-oriented prediction and decision support based on data-integrated multi-physics simulations. She is member of the board of directors of the Center for Simulation and Data Science at the Jülich Aachen Research Alliance, and serves the Steering Committee of the Helmholtz Graduate School for data science in Life, Earth and Energy.
Norbert Hosters - RWTH Aachen University, Faculty of Mechanical Engineering
Norbert Hosters is Senior Scientist at the Chair for Computational Analysis of Technical Systems (CATS) at RWTH Aachen University. In 2018, he defended his PhD thesis on spline-based methods for fluid-structure interaction at the same institute. While continuing this research, he is now also working on discontinuous and continuous space-time finite elements, physical-informed neural networks and quantum computational science in engineering. Furthermore, Norbert is secretary general of the German Association for Computational Mechanics.
Rakesh Sarma - Forschungszentrum Jülich GmbH Jülich Supercomputing Center, Institute for Advanced Simulation
Rakesh Sarma is a post-doctoral researcher at the Forschungszentrum Jülich, working on the development of parallel and scalable AI methods and workflows for HPC applications. He obtained his PhD from Delft University of Technology, Netherlands, in 2018. His doctoral thesis was on the development of Bayesian inference and reduced order modelling methods for prediction of instabilities in aeroelastic structures. Thereafter, he worked at the Dutch National Center for Mathematics and Computer Science in Amsterdam in the domain of ML/AI in space weather and stratified turbulence applications.
Jaka Vodeb - Forschungszentrum Jülich GmbH Jülich Supercomputing Center, Institute for Advanced Simulation
Jaka Vodeb is a post-doctoral researcher at the Forschungszentrum Jülich, working on applications of quantum computers, particularly in the fields of quantum simulation and optimization. He obtained his PhD from the University of Ljubljana, Slovenia, in 2021, for the development of a theoretical description and successful quantum simulation of a two- dimensional quantum material.
