Quantum Computers for Weather and Climate Prediction: The Good, the Bad and the Noisy

Abstract

Over the past few years, quantum computers and quantum algorithms have attracted considerable interest and attention from numerous scientific disciplines. In this article, we aim to provide a non-technical, yet informative introduction to key aspects of quantum computing. We discuss whether quantum computers one day might become useful tools for numerical weather and climate prediction. Using a recently developed quantum algorithm for solving non-linear differential equations, we integrate a simple non-linear model. In addition to considering the advantages that quantum computers have to offer, we shall also discuss the challenges one faces when trying to use quantum computers for real-world problems involving ''big data'', such as weather prediction.

References in corpus (4)

• Quantum algorithm for solving linear systems of equations
• Noisy intermediate-scale quantum (NISQ) algorithms
• A quantum algorithm to solve nonlinear differential equations
• Quantum algorithm for nonlinear differential equations

Cited by in corpus (9)

• Opportunities and challenges of quantum computing for climate modelling
• Quantum Dynamics Simulation of the Advection-Diffusion Equation
• Quantum computing for simulation of fluid dynamics
• Parallelizing quantum simulation with decision diagrams
• Integrating Quantum Algorithms Into Classical Frameworks: A Predictor-corrector Approach Using HHL
• An Efficient Decomposition of the Carleman Linearized Burgers' Equation
• A time-marching quantum algorithm for simulation of the nonlinear Lorenz dynamics
• Performance evaluation of variational quantum eigensolver and quantum dynamics algorithms on the advection-diffusion equation
• Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines