Trapped-ion quantum computers are gaining attention as a promising platform for achieving reliable quantum computation using high-quality qubits. Among them, the Quantum Charge-Coupled Device (QCCD) architecture is recognized as a modular solution for constructing scalable quantum computers with a large number of qubits, significantly enhancing the feasibility of executing practical quantum algorithms. In the QCCD architecture, ions shuttle between different dedicated zones, such as memory zones and processing zones, enabling efficient quantum computation.In this paper, we propose an efficient heuristic approach using Multi-Agent Path Planning (MAPP) to generate an efficient shuttling schedule that optimizes ion movement within the device. The evaluation results show that the numbers of time steps can be improved to only 88.61% for Full-Resister-Access (FRA), 91.46% for Quantum Fourier Transform (QFT) and 88.87% for Random Register Access (RRA) on average compared to a state-of-the art method. In particular, when comparing only the additional time steps spent solely on shuttling the proposed algorithm requires only 76.83% of those required by the existing method for FRA, 35.26% for QFT, and 37.47% for RRA on average.
Trapped-ion quantum computers are gaining attention as a promising platform for achieving reliable quantum computation using high-quality qubits. Among them, the Quantum Charge-Coupled Device (QCCD) architecture is recognized as a modular solution for constructing scalable quantum computers with a large number of qubits, significantly enhancing the feasibility of executing practical quantum algorithms. In the QCCD architecture, ions shuttle between different dedicated zones, such as memory zones and processing zones, enabling efficient quantum computation.In this paper, we propose an efficient heuristic approach using Multi-Agent Path Planning (MAPP) to generate an efficient shuttling schedule that optimizes ion movement within the device. The evaluation results show that the numbers of time steps can be improved to only 88.61% for Full-Resister-Access (FRA), 91.46% for Quantum Fourier Transform (QFT) and 88.87% for Random Register Access (RRA) on average compared to a state-of-the art method. In particular, when comparing only the additional time steps spent solely on shuttling the proposed algorithm requires only 76.83% of those required by the existing method for FRA, 35.26% for QFT, and 37.47% for RRA on average.
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,1 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) athttps://github.com/cda-tum/mqt-ion-shuttler.
Trapped-ion quantum computers are a promising platform, offering high-quality qubits with long coherence times and high-fidelity gate operations. The Quantum Charge Coupled Device (QCCD) architecture provides a scalable blueprint by leveraging the ability to shuttle ions between distinct zones. However, realizing such architectures in practice requires software support to manage ion movement across multi-zone layouts. In this work, we propose a compilation strategy for QCCD architectures with multiple processing zones located outside a grid-type memory zone. Unlike previous approaches that treat processing zones as black-boxes, our method explicitly models their structural constraints, enabling optimized ion movement to and through them. It combines qubit partitioning with dependency-aware gate selection to reduce inter-zone shuttling while enabling simultaneous gate execution. We implemented the method in an open-source tool and empirically demonstrated its effectiveness across several QCCD layouts, laying a foundation for the compilation of multi-zone trapped-ion systems.
The Quantum Charge Coupled Device (QCCD) architecture offers a modular solution to enable the realization of trappedion quantum computers with a large number of qubits. Within these devices, ions can be shuttled (moved) throughout the trap and through different dedicated zones. However, due to decoherence of the ions' quantum states, the qubits lose their quantum information over time. Thus, the shuttling needed for these shuttling operations should be minimized. In this extended abstract, we propose a concept towards a cycle-based heuristic approach to determining an efficient shuttling schedule for a given quantum circuit.
Trapped ions are a promising technology for building scalable quantum computers. Not only can they provide a high qubit quality, but they also enable modular architectures, referred to as Quantum Charge Coupled Device (QCCD) architecture. 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, this movement incurs a cost in terms of required time steps, which increases the probability of decoherence, and, thus, should be minimized. In this paper, we propose a formalization of the possible movements in ion traps via Boolean satisfiability. This formalization allows for determining the minimal number of time steps needed for a given quantum algorithm and device architecture, hence reducing the decoherence probability. An empirical evaluation confirms that—using the proposed approach—minimal results (i.e., the lower bound) can be determined for the first time. An open-source implementation of the proposed approach is publicly available at https://github.com/cda-tum/mqt-ion-shuttler.
The Quantum Charge Coupled Device (QCCD) architecture is a promising pathway toward scalable quantum computation in trapped-ion quantum computers. Devices using this architecture rely on efficient ion shuttling between memory and processing zones to execute quantum circuits. Hardware for trapped-ion quantum computers with multiple different zones is already being developed, but without proper compilation support, there is a risk that we will not be able to use their full potential. Recent approaches to shuttling algorithms have primarily focused on small architectures or devices with a single processing zone. In this work, we propose to extend these algorithms to large grid-type systems with multiple processing zones embedded in the memory zone. For that, a two-step solution is described: first, partitioning quantum circuits to determine where each gate is executed, and second, adapting a publicly available shuttling algorithm for architectures with a single processing zone to handle the increased complexity of multi-zone systems. Empirical evaluations demonstrate the method's effectiveness across a range of grid-type architectures, showing that additional processing zones can significantly reduce quantum circuit execution time. With that, we provide a foundation for the compilation of shuttling-based trapped-ion quantum computers with multiple processing zones. An open-source implementation of the proposed approach is available at https://github.com/cda-tum/mqt-ion-shuttler.
Scalable trapped-ion quantum computing is commonly realized with modular chips that feature distinct zones with specific functionalities, such as storage, state preparation, and gate execution. To execute a quantum circuit, the ions must be transported between these zones. This process is called ion shuttling. To achieve reliable computation results, the shuttling process must be optimized. However, as the number of ions increases, this becomes a high-dimensional optimization problem where optimal solutions cannot be computed efficiently. We demonstrate, to the best of our knowledge, the first use of reinforcement learning (RL) for the optimization of ion shuttling. RL is well-suited for such scenarios, as it enables learning a strategy through direct interaction with the problem. We show that our RL approach outperforms current state-of-the-art heuristic techniques, yielding a reduction in shuttling operations of up to 36.3 %. Furthermore, we show that our method is easily applicable to various chip architectures. Our approach offers a versatile method to study shuttling efficiency during chip design and, therefore, a highly relevant tool for future, more complex architectures.