Scientists have made significant progress in the understanding of turbulence. This chaotic phenomenon is observed in many natural systems, such as water flowing, ocean currents and blood flow.
Over the past 200 years, physicists struggled to simulate and predict turbulence. Turbulence is a complex fluid movement that involves large swirling vortices breaking down into smaller ones.
A new method inspired from quantum computing may change this.
Quantum-inspired approach to understanding complex fluid behaviour
A study published in Science Advances on January 29, 2015, revealed a novel method of simulating turbulent flow that makes use of quantum computing principles.
This breakthrough is important because accurately modeling turbulent flow can have far-reaching benefits. These include improving car and aircraft designs, weather forecasting and even medical devices such as artificial hearts.
Nik Gourianov – a physicist from the University of Oxford – explained that traditional turbulence models rely on deterministic approaches, meaning that they produce the same results under specific conditions. The new research, however, uses a probabilistic method.
What makes this work different?
This method takes into account the random fluctuations and natural fluctuations within turbulent flows.
This work is unique in that it uses quantum computing algorithms.
Quantum computers are different from traditional computers in the way they process information.
Quantum computers, unlike traditional computers, use quantum bits or qubits that can exist simultaneously in different states.
Scientists can simulate turbulence using a supercomputer in a fraction the time.
The team of researchers was able complete simulations that would have required days to perform using traditional algorithms in just a few hours.
James Beattie is a Princeton University postdoctoral research fellow who praised this new method’s ability to significantly reduce memory consumption and speed up calculations.
This is particularly important for fluid simulations that can include complex variables.
Beattie pointed out that the team’s approach would allow such simulations to run on hardware more accessible, including laptops.
The authors of the study acknowledge that despite this progress, there is much more work to be done.
Turbulence can be simulated on a wide range of scales, ranging from micro-scales to large cosmic phenomena.
It is difficult to accurately model these different scales within one simulation, as it requires a lot of memory and computation.
Beattie stressed that it is crucial to understand how the different scales interact in order to solve the turbulence mystery.
Gourianov’s team has made some impressive progress, but many experts believe that the problem of turbulence is still far from being solved.
This new approach reduces the computational complexity but does not fully address how different-sized turbulence flows are related to each other.
Next steps in turbulence will include developing new algorithms and computer systems that can better handle these challenges.
Turbulence is one of the oldest and most difficult problems in physics.
A complete solution is still out of reach despite decades of research.
The latest findings of Gourianov’s team are a step forward in unraveling the complexity of turbulence.
This post Scientists make breakthroughs in understanding fluid turbulence and patterns may be updated as new information becomes available.
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