Abstract: Computational fluid dynamics simulations use about 20% of all public HPC resources (conservatively). These simulations are expensive, both in node hours and dollars. They are also inefficient: A staggering quantity of the marshaled computational resources are required to represent the effects of microscopically small features that accumulate to have macroscopic effects. Computational models help elide this cascade of scales, though fully‐resolved simulations are still required for engineering health, defense, and energy applications. These concerns triggered a call‐to‐arms for computational scientists, who are investigating ever novel architectures for this purpose. This talk comes to you via a part domain‐expert, part computational‐scientist, and epsilon quantum expert. In this context, a first‐take on tackling CFD problem via quantum computing is discussed. A quantum analog to the lattice Boltzmann algorithm is presented as a step towards meaningful quantum computation for fluid dynamics.

Bio: Spencer Bryngelson joined the School of Computational Science and Engineering at Georgia Tech in 2021. He has been a senior postdoc at Caltech, a visiting researcher at MIT, and a postdoc at the Center for Exascale Simulation of Plasma‐Coupled Combustion. He received his Ph.D. in 2017 from UIUC and his B.S. in 2013 from the University of Michigan. Spencerʹs research group, Computational Physics @ GT, develops models, fast numerics, and scalable software for problems in health and defense.