Variational Quantum Solutions to the Advection-Diffusion Equation for Applications in Fluid Dynamics

TL;DR

This paper introduces a hybrid quantum-classical method for solving fluid dynamics equations, demonstrating its effectiveness on IBM quantum computers for small systems, with potential applications in weather prediction.

Contribution

It presents a scalable hybrid quantum-classical algorithm for fluid dynamics, specifically solving the advection-diffusion equation using current noisy quantum hardware.

Findings

Reliable solutions achieved on noisy quantum computers.

Method scales logarithmically with system dimension.

Potential to replace traditional weather prediction methods.

Abstract

Constraints in power consumption and computational power limit the skill of operational numerical weather prediction by classical computing methods. Quantum computing could potentially address both of these challenges. Herein, we present one method to perform fluid dynamics calculations that takes advantage of quantum computing. This hybrid quantum-classical method, which combines several algorithms, scales logarithmically with the dimension of the vector space and quadratically with the number of nonzero terms in the linear combination of unitary operators that specifies the linear operator describing the system of interest. As a demonstration, we apply our method to solve the advection-diffusion equation for a small system using IBM quantum computers. We find that reliable solutions of the equation can be obtained on even the noisy quantum computers available today. This and other methods that exploit quantum computers could replace some of our traditional methods in numerical weather prediction as quantum hardware continues to improve.