Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive

The potential analysis of the capabilities of quantum computing, especially before fault tolerance at scale, is difficult due to the variety of existing hardware technologies with a wide spread of maturity. Not only the result of computations, but also the very process of running quantum-enhanced algorithms differ from provider to provider. The study includes a comparative analysis of various hardware architectures with the example of the Traveling Salesperson Problem, a central class of combinatorial optimization. It highlights what steps are necessary to run real-world applications on quantum hardware, showcases how the providers and various technologies differ and presents results in the relative efficiency of exemplary quantum algorithms on neutral atom-based, ion trap and superconducting hardware, the latter including both gate-based and annealing devices. This is an important step in advancing the understanding of quantum computing capabilities from an application standpoint - agnostic to the underlying qubit technology and projecting results into the future to judge what further developments on the application side are necessary.

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Published
2025-08-30
DOI
https://doi.org/10.1109/qce65121.2025.00207
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive

Benedikt Poggel, J. Lorenz, Amine Bentellis
Quantum Computing Algorithms and Architecture
article

Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive

Benedikt Poggel, J. Lorenz, Amine Bentellis
article en

Abstract

The potential analysis of the capabilities of quantum computing, especially before fault tolerance at scale, is difficult due to the variety of existing hardware technologies with a wide spread of maturity. Not only the result of computations, but also the very process of running quantum-enhanced algorithms differ from provider to provider. The study includes a comparative analysis of various hardware architectures with the example of the Traveling Salesperson Problem, a central class of combinatorial optimization. It highlights what steps are necessary to run real-world applications on quantum hardware, showcases how the providers and various technologies differ and presents results in the relative efficiency of exemplary quantum algorithms on neutral atom-based, ion trap and superconducting hardware, the latter including both gate-based and annealing devices. This is an important step in advancing the understanding of quantum computing capabilities from an application standpoint - agnostic to the underlying qubit technology and projecting results into the future to judge what further developments on the application side are necessary.

Fraunhofer Institute for Cognitive Systems (DE)
Openalex Percentile: Top 80%
Quantum Computing Algorithms and Architecture
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Application-Driven Benchmarking of the Traveling Salesperson Problem: a Quantum Hardware Deep-Dive — Benedikt Poggel, J. Lorenz, et al. · (2025) | TGRS Research Map | TGRS