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A quantum-inspired approach to exploit turbulence structures

delete2022-01-13
delete44
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OA
AI
N
Nikita Gourianov
M
Michael Lubasch
S
Sergey Dolgov
Q
Quincy Y. van den Berg
H
Hessam Babaee
P
Peyman Givi
M
Martin Kiffner
D
Dieter Jaksch *
DOI:10.1038/s43588-021-00181-1delete
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摘要

摘要

En 中文
Understanding turbulence is key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multiscale nature, describing the coupling between different-sized eddies in space and time. Here we analyze the structure of turbulent flows by quantifying correlations between different length scales using methods inspired from quantum many-body physics. We present the results for interscale correlations of two paradigmatic flow examples, and use these insights along with tensor network theory to design a structure-resolving algorithm for simulating turbulent flows. With this algorithm, we find that the incompressible Navier-Stokes equations can be accurately solved even when reducing the number of parameters required to represent the velocity field by more than one order of magnitude compared to direct numerical simulation. Our quantum-inspired approach provides a pathway towards conducting computational fluid dynamics on quantum computers.
Keyword:
MATRIX PRODUCT STATES
RENORMALIZATION-GROUP
NUMERICAL-SOLUTION
FLUID

期刊

Nature Computational Science 封面图
Nature Computational Science
IF:
18.3
论文数:
3.1K
被引数:
4.0K

机构

U
university of bath
学者数:
1.1W
论文数: 1.3W
被引数: 13
U
University of Pittsburgh
学者数:
4.5W
论文数: 3.6W
被引数: 7.1W
P
pennsylvania commonwealth system of higher education (pcshe)
学者数:
12.9W
论文数: 11.7W
被引数: 177
U
university of oxford
学者数:
9.8W
论文数: 8.6W
被引数: 137
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