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Quality, Speed, and Scale: three key attributes to measure the performance of near-term quantum computers

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arxiv 2110.14108 v2 pith:JUOXICHG submitted 2021-10-27 quant-ph

Quality, Speed, and Scale: three key attributes to measure the performance of near-term quantum computers

classification quant-ph
keywords quantumperformancequalityscalespeedattributesclopscomputing
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Defining the right metrics to properly represent the performance of a quantum computer is critical to both users and developers of a computing system. In this white paper, we identify three key attributes for quantum computing performance: quality, speed, and scale. Quality and scale are measured by quantum volume and number of qubits, respectively. We propose a speed benchmark, using an update to the quantum volume experiments that allows the measurement of Circuit Layer Operations Per Second (CLOPS) and identify how both classical and quantum components play a role in improving performance. We prescribe a procedure for measuring CLOPS and use it to characterize the performance of some IBM Quantum systems.

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Cited by 8 Pith papers

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

  1. Helios: A 98-qubit trapped-ion quantum computer

    quant-ph 2025-11 accept novelty 7.0

    Helios achieves 98 qubits with single-qubit gate infidelity 2.5(1)×10^{-5}, two-qubit 7.9(2)×10^{-4}, and SPAM 4.8(6)×10^{-4}, enabling circuits beyond classical simulation.

  2. Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment

    quant-ph 2026-07 conditional novelty 6.5

    A vision-language agent calibrates drifting transmon chips in a physics-grounded simulator and specializes via a gradient-free, human-readable device note that raises worst-case CZ fidelity under budget pressure.

  3. Performance Model for Hybrid Quantum-Classical Workflows

    quant-ph 2026-07 conditional novelty 6.0

    A two-level runtime model decomposes hybrid quantum-classical cycles into quantum, classical, and communication time, allowing a communication-to-computation ratio to classify workflows as compute- or communication-bound.

  4. Accelerating qubit reset through the Mpemba effect

    quant-ph 2026-02 conditional novelty 6.0

    A single entangling gate that turns slow-decaying local qubit coherences into fast-decaying two-qubit coherences shortens passive reset by up to T2/T1 (about 30-50% time reduction) in the T2>T1 regime.

  5. Quantum Fidelity-per-Cost: A Metric for Evaluation of Quantum Computing Systems

    quant-ph 2026-07 conditional novelty 5.5

    Cost-aware ranking of cloud QPUs via QFC disagrees with fidelity-only ranking; billing model, not hardware, fixes how the score scales with shot count.

  6. Benchmarking fault-tolerant quantum computing hardware via QLOPS

    quant-ph 2025-07 unverdicted novelty 5.0

    Proposes QLOPS as an integrated benchmarking metric for FTQC hardware that factors in code rates, decoder throughput, latency, and accuracy, illustrated via RSA-2048 factoring resource estimates.

  7. Applications of the Quantum Phase Difference Estimation Algorithm to the Excitation Energies in Spin Systems on a NISQ Device

    quant-ph 2025-02 unverdicted novelty 4.0

    QPDE applied to 2- and 3-spin Heisenberg models on IBM processors yields 85-93% accuracy versus classical values after noise mitigation.

  8. A System Aware Resource Allocation for Distributed Workflows in Quantum Computing Environments

    quant-ph 2026-05 unverdicted novelty 3.0

    Proposes system-aware allocation for distributed quantum workflows via modified graph algorithms on hybrid classical-quantum networks, claiming average gains of 5% execution time, 30% communication overhead, 40% wait ...