Enabling Large-Scale and High-Precision Fluid Simulations on Near-Term Quantum Computers
Abstract
Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation. The Poiseuille flow simulation achieved a relative error of less than , and the unsteady acoustic wave simulation solved a 5043-dimensional matrix. We emphasize the utilization of the quantum-classical hybrid approach in applications of near-term quantum computers. By adapting to quantum hardware constraints and offering scalable solutions for large-scale CFD problems, our method paves the way for practical applications of near-term quantum computers in computational science.
Cite
@article{arxiv.2406.06063,
title = {Enabling Large-Scale and High-Precision Fluid Simulations on Near-Term Quantum Computers},
author = {Zhao-Yun Chen and Teng-Yang Ma and Chuang-Chao Ye and Liang Xu and Ming-Yang Tan and Xi-Ning Zhuang and Xiao-Fan Xu and Yun-Jie Wang and Tai-Ping Sun and Yong Chen and Lei Du and Liang-Liang Guo and Hai-Feng Zhang and Hao-Ran Tao and Tian-Le Wang and Xiao-Yan Yang and Ze-An Zhao and Peng Wang and Sheng Zhang and Chi Zhang and Ren-Ze Zhao and Zhi-Long Jia and Wei-Cheng Kong and Meng-Han Dou and Jun-Chao Wang and Huan-Yu Liu and Cheng Xue and Peng-Jun-Yi Zhang and Sheng-Hong Huang and Peng Duan and Yu-Chun Wu and Guo-Ping Guo},
journal= {arXiv preprint arXiv:2406.06063},
year = {2025}
}
Comments
31 pages, 10 figures