Abstract

There is great interest in using quantum computers to efficiently simulate a quantum system’s dynamics as existing classical computers cannot do this. Little attention, however, has been given to quantum simulation of a classical nonlinear continuum system such as a viscous fluid even though this too is hard for classical computers. Such fluids obey the Navier–Stokes nonlinear partial differential equations, whose solution is essential to the aerospace industry, weather forecasting, plasma magneto-hydrodynamics, and astrophysics. Here we present a quantum algorithm for solving the Navier–Stokes equations. We test the algorithm by using it to find the steady-state inviscid, compressible flow through a convergent-divergent nozzle when a shockwave is (is not) present. We find excellent agreement between numerical simulation results and the exact solution, including shockwave capture when present. Finally, we compare the algorithm’s computational cost to deterministic and random classical algorithms and show that a significant speed-up is possible. Our work points to a large new application area for quantum computing with substantial economic impact, including the trillion-dollar aerospace industry, weather-forecasting, and engineered-plasma technologies.

Highlights

  • In one of the earliest papers motivating the development of quantum computers Feynman1 pointed out that such computers are better suited to simulate the dynamics of a quantum system than existing classical digital computers

  • This is because classical computers require computational resources that scale exponentially with the size of the simulated quantum system, while quantum computers do not

  • The Navier–Stokes equations are nonlinear partial differential equations2–5 (PDEs) which express the conservation of mass, linear momentum, and energy of a viscous fluid

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Summary

INTRODUCTION

In one of the earliest papers motivating the development of quantum computers Feynman pointed out that such computers are better suited to simulate the dynamics of a quantum system than existing classical digital computers. An example is a viscous fluid whose flows satisfy the Navier–Stokes nonlinear partial differential equations (PDEs). Solving these PDEs is the primary task for such diverse problems as aerospace flight vehicle design, weather-forecasting, probing the dynamics of turbulence, and determining the magneto-hydrodynamics of plasmas in space and in earth-bound technologies. We point to the large new application area our quantum PDE algorithm opens up for quantum computing which includes many economically important problems. The quantum algorithm we present is independent of the previously cited papers, and of a quantum algorithm for elliptic PDEs19

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