Variational quantum algorithm for constrained topology optimization

Abstract One of the challenging scientific computing problems is topology optimization (TO), where the two tasks of searching through the combinatorially complex configurations and solving the constraints of partial differential equations need to be done simultaneously. In this paper, a novel variational quantum algorithm for constrained TO is proposed, which allows for the single-loop parallel search for the optimal configuration that also satisfies the physical constraints. The optimal configurations and the solutions to physical constraints are encoded with two separate quantum registers. A constraint encoding scheme is also proposed to incorporate volume and connectivity constraints in optimization. The gate complexity of the proposed quantum algorithm is analyzed. The algorithm is demonstrated with compliance minimization problems including truss structures and Messerschmitt–Bölkow–Blohm beams.

Authors

Publication Details

Journal
Quantum Science and Technology
Published
2025-08-18
DOI
https://doi.org/10.1088/2058-9565/adfc92
Citations
1
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
2.48
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article

Variational quantum algorithm for constrained topology optimization

Jungin E. Kim, Yan Wang
1 citations
Quantum Science and Technology
Metaheuristic Optimization Algorithms Research
2.48
article

Variational quantum algorithm for constrained topology optimization

Jungin E. Kim, Yan Wang
article en
1 citations

Abstract

Abstract One of the challenging scientific computing problems is topology optimization (TO), where the two tasks of searching through the combinatorially complex configurations and solving the constraints of partial differential equations need to be done simultaneously. In this paper, a novel variational quantum algorithm for constrained TO is proposed, which allows for the single-loop parallel search for the optimal configuration that also satisfies the physical constraints. The optimal configurations and the solutions to physical constraints are encoded with two separate quantum registers. A constraint encoding scheme is also proposed to incorporate volume and connectivity constraints in optimization. The gate complexity of the proposed quantum algorithm is analyzed. The algorithm is demonstrated with compliance minimization problems including truss structures and Messerschmitt–Bölkow–Blohm beams.

Quantum Science and TechnologyVol. 10(4)
Openalex Percentile: Top 9%
Metaheuristic Optimization Algorithms Research
2.48
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