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作者机构:Department of Mechanical Engineering National University of Singapore 10 Kent Ridge Crescent 119260 Singapore School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China National University of Singapore Singapore117411 Singapore Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way Singapore138632 Singapore
出 版 物:《arXiv》 (arXiv)
年 卷 期:2022年
核心收录:
摘 要:The prosperous development of both hardware and algorithms for quantum computing (QC) potentially prompts a paradigm shift in scientific computing in various fields. As an increasingly active topic in QC, the variational quantum algorithm (VQA) leads a promising tool for solving partial differential equations on Noisy Intermediate Scale Quantum (NISQ) devices. Although a clear perspective on the advantages of QC over classical computing techniques for specific mathematical and physical problems exists, applications of QC in computational fluid dynamics to solve practical flow problems, though promising, are still in an early stage of development. To explore QC in practical simulation of flow problems, this work applies a variational hybrid quantum-classical algorithm, namely the variational quantum linear solver (VQLS), to resolve the heat conduction equation through finite difference discretization of the Laplacian operator. Details of VQLS implementation are discussed by various test instances of linear systems. Finally, the successful statevector simulations of the heat conduction equation in one and two dimensions demonstrate the validity of the present algorithm by proof-of-concept results. In addition, the heuristic scaling for the heat conduction problem indicates that the time complexity of the present approach is logarithmically dependent on the precision Ε and linearly dependent on the number of qubits n. Copyright © 2022, The Authors. All rights reserved.