Scientists make progress in solving turbulence problem
Researchers use quantum computing to advance turbulence modeling, potentially improving aircraft design, weather forecasting, and engineering applications.
[:en]Photo: CNN[:]
Scientists have made a step forward in understanding the patterns and structure of turbulence, a natural phenomenon observed in fluids such as moving water, ocean currents, chemical reactions, blood flow, storm clouds, smoke plumes and even the plasma of stars, reported by CNN.
While turbulent flow is chaotic and irregular, as the motion of the fluid causes larger eddies to form and break up into smaller ones, physicists have long tried to study and model this process using mathematical equations and computers.
The difficulty of modeling turbulence
However, even with modern supercomputers, direct and accurate modeling of all but the simplest turbulent flows remains elusive, and a complete understanding of turbulence has eluded researchers for about 200 years. Now, an international team of scientists has pioneered a new approach to modeling turbulence that uses quantum computing.
The ability to accurately model and predict the phenomenon could have many practical applications in science and engineering. It could potentially improve the design of airplanes, cars, propellers, artificial hearts and make weather forecasting more accurate, said lead author Nick Gurianov, a research fellow in the Department of Physics at the University of Oxford.
Turbulence as an unsolved problem
Turbulence has been and remains an unsolved problem in the sense that we cannot accurately model realistic flows on computers, meaning we still need a wind tunnel to design an airplane wing. But advances like this make it easier to solve the problem. Most previous approaches to modeling turbulence have relied on a deterministic strategy that, given a given set of initial conditions, always produces the same results, Gurianov explained. Instead, the new study modeled turbulence fluctuations in a probabilistic way, an approach that takes into account random variation.
The team applied a quantum computing algorithm to turbulent flows, allowing them to calculate in a few hours what a classical algorithm would take days. Quantum computers process information fundamentally differently than classical computers. The study authors used a mathematical tool called tensor networks, which can be used to model a quantum system.
