Complete quantum-inspired framework for computational fluid dynamics

Raghavendra D. Peddinti, Stefano Pisoni, Alessandro Marini, Philippe Lott, Henrique Argentieri, Egor Tiunov, Leandro Aolita

Published 2023-08-02Version 1

Computational fluid dynamics is both an active research field and a key tool for industrial applications. The central challenge is to simulate turbulent flows in complex geometries, a compute-power intensive task due to the large vector dimensions required by discretized meshes. Here, we propose a full-stack solver for incompressible fluids with memory and runtime scaling polylogarithmically in the mesh size. Our framework is based on matrix-product states, a powerful compressed representation of quantum states. It is complete in that it solves for flows around immersed objects of diverse geometries, with non-trivial boundary conditions, and can retrieve the solution directly from the compressed encoding, i.e. without ever passing through the expensive dense-vector representation. These developments provide a toolbox with potential for radically more efficient simulations of real-life fluid problems.