Hardware-aware and Resource-efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers

• URL: http://arxiv.org/abs/2512.20554v2
• Date: Wed, 24 Dec 2025 16:38:08 GMT
• Title: Hardware-aware and Resource-efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers
• Authors: Miguel Palma, Shuwen Kan, Wenqi Wei, Juntao Chen, Kaixun Hua, Sara Mouradian, Ying Mao,
• Abstract summary: We present CircPack, a hardware-aware circuit packing framework for trapped-ion devices.<n>Compared to superconducting-based QMP approaches, CircPack achieves up to 70.72% better fidelity, 62.67% higher utilization, and 32.80% improved layer reduction.<n>This framework is also capable of scalable, balanced scheduling across a cluster of independent QCCD modules.
• Score: 8.347426320299165
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multi-programming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lower gate fidelity. Trapped-ion architectures, with all-to-all connectivity, long coherence times, and high-fidelity mid-circuit measurement properties, presents itself as a more suitable platform for scalable QMP. We present CircPack, a hardware-aware circuit packing framework designed for modular trapped-ion devices based on the Quantum Charge-Coupled Device (QCCD) architecture. CircPack formulates static circuit scheduling as a two-dimensional packing problem with hardware-specific shuttling constraints. Compared to superconducting-based QMP approaches, CircPack achieves up to 70.72% better fidelity, 62.67% higher utilization, and 32.80% improved layer reduction. This framework is also capable of scalable, balanced scheduling across a cluster of independent QCCD modules, highlighting trapped-ion systems' potential in improving the throughput of quantum cloud computing in the near future.

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