Shuttling for Scalable Trapped-Ion Quantum Computers

TL;DR

This paper introduces a heuristic method for optimizing ion shuttling schedules in scalable trapped-ion quantum computers, reducing decoherence and improving efficiency in large quantum architectures.

Contribution

It presents a heuristic approach for efficient shuttling schedules in QCCD architectures, enhancing scalability and performance for large quantum computers.

Findings

Schedules are close to minimal time steps for small devices.

Empirical results show promising performance for large devices.

Open-source implementation available in MQT toolkit.

Abstract

Trapped-ion quantum computers exhibit promising potential to provide platforms for high-quality qubits and reliable quantum computation. The Quantum Charge Coupled Device (QCCD) architecture is a leading example that offers a modular solution to enable the realization of scalable quantum computers, paving the way for practical quantum algorithms with large qubit numbers. Within these devices, ions can be shuttled (moved) throughout the trap and through different dedicated zones, e.g., a memory zone for storage and a processing zone for the actual computation. However, due to decoherence of the ions' quantum states, the qubits lose their quantum information over time. Thus, the required time steps of shuttling operations should be minimized. In this work, we propose a heuristic approach to determining an efficient shuttling schedule, which orchestrates the movement operations within the device. Given a quantum algorithm and a device architecture, the proposed approach produces shuttling schedules with a close-to-minimal amount of time steps for small-size QCCD architectures. For large scale QCCD devices, empirical evaluations show promising results with respect to quality of the solution as well as performance. An implementation of the proposed approach is publicly available as part of the open-source Munich Quantum Toolkit (MQT) at https://github.com/cda-tum/mqt-ion-shuttler.