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Validating quantum computers using randomized model circuits

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arxiv 1811.12926 v2 pith:UFBXWUQY submitted 2018-11-30 quant-ph

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

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abstract

We introduce a single-number metric, quantum volume, that can be measured using a concrete protocol on near-term quantum computers of modest size ($n\lesssim 50$), and measure it on several state-of-the-art transmon devices, finding values as high as 16. The quantum volume is linked to system error rates, and is empirically reduced by uncontrolled interactions within the system. It quantifies the largest random circuit of equal width and depth that the computer successfully implements. Quantum computing systems with high-fidelity operations, high connectivity, large calibrated gate sets, and circuit rewriting toolchains are expected to have higher quantum volumes. The quantum volume is a pragmatic way to measure and compare progress toward improved system-wide gate error rates for near-term quantum computation and error-correction experiments.

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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. Clifford Volume and Free Fermion Volume: Complementary Scalable Benchmarks for Quantum Computers

    quant-ph 2025-12 conditional novelty 6.0 of 10

    Two new classically verifiable benchmark scores, Clifford Volume and Free Fermion Volume, are defined, simulated under noise, and Clifford Volume is measured on the Quantinuum H2-1 device as 34 qubits.

  2. Classifying single-qubit noise using machine learning

    quant-ph 2019-08 conditional novelty 6.0 of 10

    Supervised classifiers distinguish coherent from stochastic single-qubit noise on GST data, with near-perfect accuracy after feature engineering and margin-based robustness to sampling noise.

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