An algorithm inspired by quantum computers but used on classical machines can make weather forecasts and other turbulence simulations a thousand times easier to run
By Matthew Sparkes
29 January 2025
Simulating turbulent air flow accurately is vital for weather forecasts
EUMETSAT/ESA
Quantum-inspired algorithms can simulate turbulent fluid flows on a classical computer much faster than existing tools, slashing computation times from several days on a large supercomputer to just hours on a regular laptop. This could improve weather forecasts and increase the efficiency of industrial processes, say researchers.
Turbulence in liquid or air involves numerous interacting eddies that quickly become so chaotically complex that precise simulation is impossible for even the most powerful computers. Quantum counterparts promise to improve matters, but currently even the most advanced machines are incapable of anything but rudimentary demonstrations.
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These turbulence simulations can be simplified by replacing precise calculations with probabilities. But even this approximation leaves scientists with computations that are infeasibly demanding to solve.
Nikita Gourianov at the University of Oxford and his colleagues have now developed a new approach that uses quantum computer-inspired algorithms called tensor networks to represent turbulence probability distributions.
Tensor networks originated in physics and came into common use in the early 2000s. They now offer a promising path to eke out much more performance from existing classical computers before truly useful quantum machines are available.