Quantum mechanics

Theoretical physics

Turbulence

Scale (ratio)

Exploit

Computer security

Theoretical computer science

Operating system

Computer science

Classical mechanics

Statistical physics

Tensor (intrinsic definition)

Physics

Mathematics

Flow (mathematics)

Geometry

Quantum

Eddy

Mechanics

Space (punctuation)

Nature Computational Science

Understanding turbulence is the key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multi-scale nature, describing the coupling between different-sized eddies in space and time. Here we introduce a new paradigm for analyzing the structure of turbulent flows by quantifying correlations between different length scales using methods inspired from quantum many-body physics. We present 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 within a computational space reduced by over an order of magnitude compared to direct numerical simulation. Our quantum-inspired approach provides a pathway towards conducting computational fluid dynamics on quantum computers.

A quantum-inspired approach to exploit turbulence structures