Quantum circuit implementation of multi-dimensional nonlinear lattice models

Steijl, R. (2023) Quantum circuit implementation of multi-dimensional nonlinear lattice models. Applied Sciences, 13(1), 529. (doi: 10.3390/app13010529)

[img] Text
288718.pdf - Published Version
Available under License Creative Commons Attribution.



The application of Quantum Computing (QC) to fluid dynamics simulation has developed into a dynamic research topic in recent years. With many flow problems of scientific and engineering interest requiring large computational resources, the potential of QC to speed-up simulations and facilitate more detailed modeling forms the main motivation for this growing research interest. Despite notable progress, many important challenges to creating quantum algorithms for fluid modeling remain. The key challenge of non-linearity of the governing equations in fluid modeling is investigated here in the context of lattice-based modeling of fluids. Quantum circuits for the D1Q3 (one-dimensional, three discrete velocities) Lattice Boltzmann model are detailed along with design trade-offs involving circuit width and depth. Then, the design is extended to a one-dimensional lattice model for the non-linear Burgers equation. To facilitate the evaluation of non-linear terms, the presented quantum circuits employ quantum computational basis encoding. The second part of this work introduces a novel, modular quantum-circuit implementation for non-linear terms in multi-dimensional lattice models. In particular, the evaluation of kinetic energy in two-dimensional models is detailed as the first step toward quantum circuits for the collision term of two- and three-dimensional Lattice Boltzmann methods. The quantum circuit analysis shows that with O(100) fault-tolerant qubits, meaningful proof-of-concept experiments could be performed in the near future.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Steijl, Dr Rene
Authors: Steijl, R.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:Applied Sciences
ISSN (Online):2076-3417
Published Online:30 December 2022
Copyright Holders:Copyright © 2022 The Author
First Published:First published in Applied Sciences 13(1): 529
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record