from CNN: Scientists have made a leap forward in understanding the pattern and structure of turbulence — a natural phenomenon observed in fluids such as moving water, ocean currents, chemical reactions, blood flow, storm clouds, plumes of smoke and even the plasma of stars.

Turbulence
While turbulent flow is chaotic and irregular, physicists have long attempted to study and model the process using mathematical equations and computers. However, even with modern supercomputers, a direct and accurate simulation of all but the simplest turbulent flows remains out of reach, and a complete understanding of turbulence has eluded researchers for some 200 years. Now, an international team of scientists has pioneered a new approach to simulating turbulence that deploys a quantum computing-inspired method, described in a study published January 29 in the journal Science Advances.
The ability to accurately model and predict the phenomenon could have many practical applications in science and engineering, potentially improving the design of airplanes, cars, propellers, artificial hearts and making weather prediction more accurate, said the study’s lead author Nik Gourianov, a researcher in the department of physics at the University of Oxford.
“Turbulence was and still is an unsolved problem in the sense that we cannot exactly simulate realistic flows on computers, i.e. we still need a wind tunnel to design an aircraft wing. But advances such as ours ‘chip away’ at the problem and push the frontier,” Gourianov said. The team applied a quantum computing-inspired algorithm to turbulent flows, allowing them to compute in a few hours what would take a classical algorithm several days to do on an entire supercomputer.
Quantum computers process information in a fundamentally different way from classical computers. Traditional computers do calculations using bits: data that exists in one state at a time, a one or a zero. Quantum computers use quantum bits (or “Qbits), which can be zeros, ones or any combination of both. The study authors used a mathematical tool called tensor networks that can be used to simulate a quantum system.
James Beattie, a postdoctoral research associate and fellow in the department of astrophysical sciences at Princeton University in New Jersey, said that, by representing data with many variables in a simpler way, the team had been able to speed up complex calculations necessary to begin to understand turbulence. Beattie was not involved in the research.
“The simulation they are running is a fluid simulation of two different chemicals mixing and reacting. By using this representation, it means that this rather complex calculation can use significantly less memory, allowing it to be run on a laptop,” Beattie added.
“Seeing advances like this (a million times better utilization of memory and a thousand times speed-up in computation) is rare, making this an exciting advancement in the modeling of turbulence,” he said.
While the latest study is “amazing progress,” it is not the full story, Beattie added, noting that it doesn’t address issues of scale, or how turbulent vortices of different sizes relate to one another.
“Turbulence, as the authors say, is a multi-scale problem, i.e., turbulence can span from thousands of lightyears to less than a foot,” he said via email. “We want to know how these scales talk to each other.”
“This is an aspect that makes simulating turbulent fluids so challenging — we want to resolve many, many scales in the simulation, which take up lots and lots of memory and computation, which means putting these simulations on large supercomputers,” Beattie said.