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A quantum-inspired approach to exploit turbulence structures.

Nikita Gourianov1, Michael Lubasch2, Sergey Dolgov3

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Researchers analyzed turbulent flow structures using quantum physics methods. This quantum-inspired approach significantly reduces computational needs for simulating fluid dynamics, paving the way for quantum computing applications.

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Area of Science:

  • Fluid Dynamics
  • Quantum Physics
  • Computational Science

Background:

  • Turbulence is a complex phenomenon crucial for understanding natural and technological flows.
  • Its multiscale nature, involving interactions between eddies of various sizes, presents significant computational challenges.
  • Current simulation methods often require substantial computational resources.

Purpose of the Study:

  • To analyze the structure of turbulent flows by quantifying interscale correlations.
  • To develop a novel, structure-resolving algorithm for simulating turbulent flows.
  • To explore the application of quantum many-body physics methods in fluid dynamics.

Main Methods:

  • Quantifying correlations between different length scales in turbulent flows.
  • Utilizing methods inspired by quantum many-body physics.
  • Applying tensor network theory to design a new simulation algorithm.
  • Comparing simulation results with direct numerical simulation (DNS).

Main Results:

  • Identified intricate interscale correlations within turbulent flow structures.
  • Developed a quantum-inspired algorithm that accurately solves the incompressible Navier-Stokes equations.
  • Achieved over a tenfold reduction in the parameters needed to represent the velocity field compared to DNS.
  • Demonstrated the efficacy of the new algorithm on two paradigmatic flow examples.

Conclusions:

  • The study presents a novel quantum-inspired approach to turbulence simulation.
  • This method significantly enhances computational efficiency in computational fluid dynamics (CFD).
  • The findings open new avenues for performing CFD simulations on quantum computers.