Carmen G. Almudever

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.

Ion-trapped Quantum Charge-Coupled Device (QCCD) architectures have emerged as a promising alternative to scale single-trap devices by interconnecting multiple traps through ion shuttling, enabling the execution of parallel operations across different traps. While this parallelism enhances computational throughput, it introduces additional operations, raising the following question: do the benefits of parallelism outweigh the potential loss of fidelity due to increased ion movements? This paper answers this question by exploring the trade-off between the parallelism of operations and fidelity loss due to movement overhead, comparing sequential execution in single-trap devices with parallel execution in QCCD architectures. We first analyze the fidelity impact of both methods, establishing the optimal number of ion movements for the worst-case scenario. Next, we evaluate several quantum algorithms on QCCD architectures by exploiting parallelism through ion distribution across multiple traps. This analysis identifies the algorithms that benefit the most from parallel executions, explores the underlying reasons, and determines the optimal balance between movement overhead and fidelity loss for each algorithm.

Ion trap technologies have earned significant attention as potential candidates for quantum information processing due to their long decoherence times and precise manipulation of individual qubits, distinguishing them from other candidates in the field of quantum technologies. However, scalability remains a challenge, as introducing additional qubits into a trap increases noise and heating effects, consequently decreasing operational fidelity. Trapped-ion Quantum Charge-Coupled Device (QCCD) architectures have addressed this limitation by interconnecting multiple traps and employing ion shuttling mechanisms to transfer ions among traps. This new architectural design requires the development of novel compilation techniques for quantum algorithms, which efficiently allocate and route qubits, and schedule operations. The aim of a compiler is to minimize ion movements and, therefore, reduce the execution time of the circuit to achieve a higher fidelity. In this paper, we propose a novel approach for initial qubit placement, demonstrating enhancements of up to 50\% compared to prior methods. Furthermore, we conduct a scalability analysis on two distinct QCCD topologies: a 1D-linear array and a ring structure. Additionally, we evaluate the impact of the excess capacity -- i.e. the number of free spaces within a trap -- on the algorithm performance.