Review and perspectives in quantum computing for partial differential equations in structural mechanics

Review (2022)
Author(s)

G.B.L. Tosti Balducci (TU Delft - Aerospace Structures & Computational Mechanics)

Boyang Chen (TU Delft - Aerospace Structures & Computational Mechanics)

M. Möller (TU Delft - Numerical Analysis)

MI Gerritsma (TU Delft - Aerodynamics)

R de Breuker (TU Delft - Aerospace Structures & Computational Mechanics)

Research Group
Aerospace Structures & Computational Mechanics
Copyright
© 2022 G.B.L. Tosti Balducci, B. Y. Chen, M. Möller, M.I. Gerritsma, R. De Breuker
DOI related publication
https://doi.org/10.3389/fmech.2022.914241
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 G.B.L. Tosti Balducci, B. Y. Chen, M. Möller, M.I. Gerritsma, R. De Breuker
Research Group
Aerospace Structures & Computational Mechanics
Volume number
8
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Abstract

Structural mechanics is commonly modeled by (systems of) partial differential equations (PDEs). Except for very simple cases where analytical solutions exist, the use of numerical methods is required to find approximate solutions. However, for many problems of practical interest, the computational cost of classical numerical solvers running on classical, that is, silicon-based computer hardware, becomes prohibitive. Quantum computing, though still in its infancy, holds the promise of enabling a new generation of algorithms that can execute the most cost-demanding parts of PDE solvers up to exponentially faster than classical methods, at least theoretically. Also, increasing research and availability of quantum computing hardware spurs the hope of scientists and engineers to start using quantum computers for solving PDE problems much faster than classically possible. This work reviews the contributions that deal with the application of quantum algorithms to solve PDEs in structural mechanics. The aim is not only to discuss the theoretical possibility and extent of advantage for a given PDE, boundary conditions and input/output to the solver, but also to examine the hardware requirements of the methods proposed in literature.