Toward Quantum-Accelerated CFD: From Algorithms to Applications
Abstract
Simulating fluid flows—known as computational fluid dynamics (CFD) — is central to many engineering applications, yet complex simulations remain demanding even for today’s high-performance computers. Quantum computing offers the prospect of accelerating some of these calculations by using quantum mechanical effects to encode and process information in new ways. Realizing this potential requires algorithms tailored to quantum computers, as well as a careful understanding of their capabilities and limitations.
In this talk, I will introduce the opportunities and challenges of quantum computing for CFD through our recent work on the quantum lattice Boltzmann method (QLBM). This approach models fluid flow through the evolution of particle distributions, using simplified transport and collision steps that provide a promising starting point for quantum algorithms. I will explain its main computational building blocks and discuss a central challenge: how to represent the nonlinear behavior of fluid flows using the linear operations underlying quantum circuits. Finally, I will present an end-to-end workflow for quantum-accelerated design optimization, in which our QLBM solver is embedded within a quantum search procedure to explore candidate designs. The talk will emphasize the ideas behind the approach and the challenges ahead, assuming no prior knowledge of quantum computing.