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Impact of unreliable devices on stability of quantum computations

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arxiv 2307.06833 v3 pith:J6WR2DSR submitted 2023-07-13 quant-ph cs.ET

classification quant-phcs.ET
keywords devicesnisqquantumstabilitybernstein-vaziranidatadeviceerrors
verification ladder T0 review T1 audit T2 compute T3 formal
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Noisy intermediate-scale quantum (NISQ) devices are valuable platforms for testing the tenets of quantum computing, but these devices are susceptible to errors arising from de-coherence, leakage, cross-talk and other sources of noise. This raises concerns regarding the stability of results when using NISQ devices since strategies for mitigating errors generally require well-characterized and stationary error models. Here, we quantify the reliability of NISQ devices by assessing the necessary conditions for generating stable results within a given tolerance. We use similarity metrics derived from device characterization data to derive and validate bounds on the stability of a 5-qubit implementation of the Bernstein-Vazirani algorithm. Simulation experiments conducted with noise data from IBM Washington, spanning January 2022 to April 2023, revealed that the reliability metric fluctuated between 41% and 92%. This variation significantly surpasses the maximum allowable threshold of 2.2% needed for stable outcomes. Consequently, the device proved unreliable for consistently reproducing the statistical mean in the context of the Bernstein-Vazirani circuit.

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

  1. Computational Performance Bounds Prediction in Quantum Computing with Unstable Noise

    quant-ph 2025-07 conditional novelty 5.0 of 10

    QuBound uses historical performance traces decomposed into trend and residual to train an LSTM that predicts tight, fast performance bounds for quantum circuits under time-varying noise.

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