Quantum Algorithms Get Better at Cracking Nature’s ‘Chaotic’ Equations

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Insider Brief

  • Riverlane-led research team published research showing substantial improvement in the use of quantum algorithms to more accurately model highly unpredictable physical systems.
  • The research could help scientists more accurately model highly unpredictable physical systems, from complex weather patterns and solar flares to aerodynamics during turbulence.
  • The paper was published in the open journal, Quantum, in partnership with MIT and the US Department of Energy.

PRESS RELEASE —  – Riverlane, the quantum computing scale-up building the world’s first error-corrected quantum operating system, has published peer-reviewed research that presents substantial improvement in the use of quantum algorithms to more accurately model highly unpredictable physical systems, from complex weather patterns and solar flares to aerodynamics during turbulence.

The paper, published in Quantum –the open journal for quantum science – in partnership with MIT and the US Department of Energy, outlines new quantum algorithms that can be applied to linear and nonlinear differential equations —complex mathematical formulas  that make up the chaotic, physical systems that govern the forces of nature.

The more non-linear the system, the more complex the differential equations it requires. Until now, some equations have been highly complex to solve, if not unsolvable, using even the most advanced existing quantum algorithms.

In the new paper, Riverlane’s Lead Scientist Hari Krovi, solves a larger class of differential equations using a mathematical function called the exponential of a matrix (a quantity used to study the stability of differential equations). The research improves previous quantum algorithms so that they can be applied to a much wider range of differential equations, including some that were previously considered too complex and too time-consuming to replicate.

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The practical use cases could include the more accurate simulation of fluid dynamics in the presence of viscosity and turbulence; weather modelling; and simulations of plasma physics applied to inertial confinement fusion, aiding clean nuclear energy development.

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Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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