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Quantum Information Processing

Quantum Approach to Accelerate Finite Volume Method on Steady Computational Fluid Dynamics Problems

  • 01-04-2022
Published in:
Authors
Zhao-Yun Chen
Cheng Xue
Si-Ming Chen
Bing-Han Lu
Yu-Chun Wu
Ju-Chun Ding
Sheng-Hong Huang
Guo-Ping Guo
Published in
Quantum Information Processing | Issue 4/2022

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Abstract

The article discusses the application of quantum computing to enhance the finite volume method (FVM) for steady computational fluid dynamics (CFD) problems. It focuses on using quantum linear solvers (QLS) within the implicit Euler time-stepping scheme to achieve exponential speedup. The authors propose a quantum data structure utilizing quantum random access memory (QRAM) and a residual sum tree to efficiently manage quantum inputs and outputs. This approach maintains convergence stability and demonstrates the practical applicability of quantum computing in CFD through numerical experiments. The work highlights the potential of quantum computing to revolutionize the field of CFD by significantly reducing the time complexity of solving large-scale fluid flow simulations.
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previous article Tightening monogamy and polygamy relations of unified entanglement in multipartite systems
next article Local trade-off between information and disturbance in quantum measurements
Title
Quantum Approach to Accelerate Finite Volume Method on Steady Computational Fluid Dynamics Problems
Authors
Zhao-Yun Chen
Cheng Xue
Si-Ming Chen
Bing-Han Lu
Yu-Chun Wu
Ju-Chun Ding
Sheng-Hong Huang
Guo-Ping Guo
Publication date
01-04-2022
Publisher
Springer US
Published in
Quantum Information Processing / Issue 4/2022
Print ISSN: 1570-0755
Electronic ISSN: 1573-1332
DOI
https://doi.org/10.1007/s11128-022-03478-w
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