Quantum computing for nonlinear differential equations and turbulence
Abstract
Many problems in classical physics and engineering, such as turbulence, are governed by nonlinear differential equations, which typically require high-performance computing to be solved. Over the past decade, however, the growth of classical computing power has slowed because the miniaturization of chips is approaching the atomic scale. This development calls for a new computing paradigm: quantum computing is a prime candidate. In this Perspective, we offer a view on the challenges that need to ...
Description / Details
Many problems in classical physics and engineering, such as turbulence, are governed by nonlinear differential equations, which typically require high-performance computing to be solved. Over the past decade, however, the growth of classical computing power has slowed because the miniaturization of chips is approaching the atomic scale. This development calls for a new computing paradigm: quantum computing is a prime candidate. In this Perspective, we offer a view on the challenges that need to be overcome in order to use quantum computing to simulate nonlinear dynamics. We discuss progress in the development of both quantum algorithms for nonlinear equations and quantum hardware. We propose synergies between quantum algorithms for nonlinear equations and quantum hardware concepts that could bear fruit in the near to mid-term future for the simulation of nonlinear systems and turbulence. Quantum computing outperforms classical computing on a number of tasks. This Perspective offers a view on the future potential of quantum computing to enhance simulations of nonlinear systems such as turbulent flows.
Source: Semantic Scholar - Nature Reviews Physics (67 citations) PDF: http://arxiv.org/pdf/2406.04826 Original Link: https://www.semanticscholar.org/paper/d2f7b4c1a3492f8220b77837bb33808c4a25b7db
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Aug 26, 2026
Physics
Peer Reviewed
0