Quantum Brain
← Back to papers

Computational Fluid Dynamics on Quantum Computers

M. Syamlal, Carter Copen, M. Takahashi, Benjamin Hall QubitSolve Inc., Infleqtion·June 26, 2024·DOI: 10.2514/6.2024-3534
Physics

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

QubitSolve is working on a quantum solution for computational fluid dynamics (CFD). We have created a variational quantum CFD (VQCFD) algorithm and a 2D Software Prototype based on it. By testing the Software Prototype on a quantum simulator, we demonstrate that the partial differential equations that underlie CFD can be solved using quantum computers. We aim to determine whether a quantum advantage can be achieved with VQCFD. To do this, we compare the performance of VQCFD with classical CFD using performance models. The quantum performance model uses data from VQCFD circuits run on quantum computers. We define a key performance parameter Q_{5E7}, the ratio of quantum to classical simulation time for a size relevant to industrial simulations. Given the current state of the Software Prototype and the limited computing resources available, we can only estimate an upper bound for Q_{5E7}. While the estimated Q_{5E7} shows that the algorithm's implementation must improve significantly, we have identified several innovative techniques that could reduce it sufficiently to achieve a quantum advantage. In the next phase of development, we will develop a 3D minimum-viable product and implement those techniques.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.