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SHARE: Secure Hardware Allocation and Resource Efficiency in Quantum Systems

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arxiv 2405.00863 v1 pith:HH53WP3K submitted 2024-05-01 quant-ph

classification quant-ph
keywords hardwarequantumutilizationcomdapacrossallocationaveragemulti
verification ladder T0 review T1 audit T2 compute T3 formal

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Quantum computing (QC) is poised to revolutionize problem solving across various fields, with research suggesting that systems with over 50 qubits may achieve quantum advantage surpassing supercomputers in certain optimization tasks. As the hardware size of Noisy Intermediate Scale Quantum (NISQ) computers continues to grow, Multi tenant computing (MTC) has emerged as a viable approach to enhance hardware utilization by allowing shared resource access across multiple quantum programs. However, MTC can also bring challenges and security concerns. This paper focuses on optimizing quantum hardware utilization in shared environments by implementing multi programming strategies that not only enhance hardware utilization but also effectively manage associated risks like crosstalk and fault injection. We propose a novel partitioning and allocation method called Community Based Dynamic Allocation Partitioning (COMDAP) and Secure COMDAP to refine and secure multi programming capabilities in quantum systems. COMDAP ensures equitable and efficient resource distribution, addresses the issues of suboptimal partitioning, and significantly improves hardware utilization. We report a 23 percent average improvement in hardware utilization rate compared to existing greedy heuristics, with rates averaging 92 percent. COMDAP introduces an average increase of approximately 0.05X in delta CX, alongside a 3.5 percent average reduction in PST across benchmarks.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Forensics of Error Rates of Quantum Hardware

    cs.CR 2025-05 conditional novelty 5.0 of 10

    A frequency-based method ranks qubit link error rates from transpiled circuits, matching IBM's public calibration bins within two ranks for about 80% of links on two 127-qubit machines.

  2. Forensics of Transpiled Quantum Circuits

    cs.CR 2024-12 conditional novelty 5.0 of 10

    From transpiled quantum circuits, the paper recovers the hardware coupling map and identifies the backend used for transpilation with up to 97.33% accuracy.

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