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Quantum Optimization Quantum Machine Learning Quantum Compilation Routing Architecture

Adaptive Parallelism-Aware Qubit Routing for Ion Trap QCCD Architectures

arXiv
Authors: Anabel Ovide, Andreu Angles-Castillo, Carmen G. Almudever

Year

2026

Paper ID

35957

Status

Preprint

Abstract Read

~2 min

Abstract Words

115

Citations

N/A

Abstract

Trapped-ion Quantum Charge-Coupled Device (QCCD) architectures promise scalability through interconnected trap zones and dynamic ion transport; however, this transport capability creates a complex compilation challenge: how to move qubits efficiently without degrading fidelity. We introduce a routing strategy that turns this challenge into an advantage by exploiting operational parallelism across traps while adapting to both algorithmic structure and device topology through a configurable multi-parameter scoring mechanism. Across a broad suite of benchmarks and QCCD layouts, the method consistently reduces ion-transport overhead and improves execution fidelity, outperforming state-of-the-art routing techniques. These results highlight that explicitly balancing movement overhead and execution parallelism under architectural constraints is key to unlocking the full potential of modular trapped-ion quantum processors.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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  • Trapped-ion Quantum Charge-Coupled Device (QCCD) architectures promise scalability through interconnected trap zones and dynamic ion transport; however, this transport...

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