aiqbench analysis
This research advances variational quantum algorithms by adapting them to solve complex nonlinear elasticity problems, specifically handling rational power constitutive behaviors like Ogden and Mooney-Rivlin models. By introducing auxiliary variables and penalty constraints, the study demonstrates a method to transform classical material science equations into forms compatible with current quantum algorithmic primitives. The work highlights a potential pathway for near-term quantum hardware to contribute to computational mechanics through iterative correction strategies that improve solution accuracy.
Variational Quantum Algorithms for Hyperelasticity: Incorporating Nonlinear Constitutive Behavior
arXiv:2608.18363v1 Announce Type: new Abstract: This paper extends a recently proposed Variational Quantum Algorithm framework for nonlinear elasticity to a broader class of constitutive nonlinearities involving rational powers of the stretch. One-dimensional incompressible Ogden and Mooney-Rivlin models are employed as representative examples to demonstrate the proposed methodology. Nonlinear constitutive terms are transformed into forms compatible with the available quantum algorithmic primitives through the introduction of auxiliary variables and penalty constraints, yielding approximate solutions via a Variational Quantum Algorithm. An iterative correction strategy based on a sequence of Variational Quantum Algorithms is then introduced to improve solution accuracy. A Numerical example demonstrates the proposed approach.
Abstract:This paper extends a recently proposed Variational Quantum Algorithm framework for nonlinear elasticity to a broader class of constitutive nonlinearities involving rational powers of the stretch. One-dimensional incompressible Ogden and Mooney-Rivlin models are employed as representative examples to demonstrate the proposed methodology. Nonlinear constitutive terms are transformed into forms compatible with the available quantum algorithmic primitives through the introduction of auxiliary variables and penalty constraints, yielding approximate solutions via a Variational Quantum Algorithm. An iterative correction strategy based on a sequence of Variational Quantum Algorithms is then introduced to improve solution accuracy. A Numerical example demonstrates the proposed approach.
arXiv:2608.18363 [quant-ph]
(or arXiv:2608.18363v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2608.18363 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 190 words
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