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

TL;DR

This paper introduces CircPack, a hardware-aware circuit packing framework for trapped-ion quantum computers that significantly improves fidelity, utilization, and scheduling efficiency compared to superconducting systems, enhancing quantum cloud throughput.

Contribution

CircPack is the first hardware-aware, scalable circuit packing framework tailored for trapped-ion QCCD architectures, optimizing resource utilization and fidelity.

Findings

Achieves up to 70.72% better fidelity

Provides 62.67% higher utilization

Enables 32.80% improvement in layer reduction

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.