Scientists have made a significant breakthrough in understanding and modeling turbulence, a ubiquitous yet notoriously complex phenomenon found in everything from swirling ocean currents to the flow of blood, CNN reports.
This breakthrough, published January 29 in the journal Science Advances, utilizes a quantum computing-inspired approach that promises to revolutionize areas like airplane design, weather forecasting, and the development of artificial hearts.
For two centuries, researchers have struggled to fully comprehend and accurately model turbulent flow, where chaotic and irregular fluid movement leads to the formation and breakdown of vortices and eddies. Even the most powerful supercomputers struggle to simulate anything beyond the simplest turbulent flows.
Now, an international team led by Nik Gourianov, a researcher at the University of Oxford’s Department of Physics, has pioneered a novel approach that tackles the problem with a probabilistic strategy inspired by the principles of quantum computing.
The team utilized a quantum computing-inspired algorithm, specifically a mathematical tool called tensor networks that are traditionally used to simulate quantum systems, to analyze turbulent flows. This innovative method dramatically reduced the computational time required for complex calculations. In fact, simulations that would have taken several days on a supercomputer were completed in mere hours.
Quantum computers leverage quantum bits, or “Qbits,” which can exist in multiple states simultaneously, unlike the standard bits used in traditional computers that can only represent a one or a zero. This allows quantum computers to process information in a fundamentally different and often faster way.
The implications of this breakthrough are vast and potentially transformative. According to Gourianov, accurately modeling and predicting turbulence could lead to significant improvements in numerous scientific and engineering fields.
James Beattie, a postdoctoral research associate and fellow in the Department of Astrophysical Sciences at Princeton University, who was not involved in the study, commented that the team’s ability to represent complex data with a simpler method has greatly accelerated the complex calculations necessary to begin to understand turbulence.
