Reproducibility in Quantum Computing

Dasgupta, Samudra; Humble, Travis S.

doi:10.1109/isvlsi51109.2021.00090

Cited by 3 publications

(3 citation statements)

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“…Despite the successful validation, we note that this approach has its limitations. A preliminary version of these results used only readout asymmetry and ignored the Hadamard gate error for describing circuit noise [ 32 ]. For example, on 21 August 2021, the typical mean error rates were

for single-qubit Pauli-X error and

for readout assignment error on the 27-qubit IBM quantum device ibmq_toronto.…”

Section: Discussionmentioning

confidence: 99%

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Characterizing the Reproducibility of Noisy Quantum Circuits

Dasgupta

Humble

2022

Entropy

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The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.

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for single-qubit Pauli-X error and

for readout assignment error on the 27-qubit IBM quantum device ibmq_toronto.…”

Section: Discussionmentioning

confidence: 99%

“…This work is a significant extension of an earlier publication [ 32 ], in which the methods and results have been revised and refined to validate experimentally-observed bounds.…”

Section: Introductionmentioning

confidence: 94%

Characterizing the Reproducibility of Noisy Quantum Circuits

Dasgupta

Humble

2022

Entropy

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“…1 Reproducibility is used to quantify how close an instance of a program is to a previously executed instance on the same or potentially different device. 2,3 Reliability studies how select parameters characterizing the device components, such as gate fidelities, deviate from expectation, while stability quantifies whether the program behavior stays bounded in the presence of fluctuations due to noise. 4 In the following sections, we define and quantify these notions and, with the help of depolarizing channel as a running example, explore their behaviors for noisy quantum circuits.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Stability of Noisy Quantum Computation

Dasgupta¹,

Humble²

2022

Preprint

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Quantum computation has made considerable progress in the last decade with multiple emerging technologies providing proof-of-principle experimental demonstrations of such calculations. However, these experimental demonstrations of quantum computation face technical challenges due to the noise and errors that arise from imperfect implementation of the technology. Here, we frame the concepts of computational accuracy, result reproducibility, device reliability and program stability in the context of quantum computation. We provide intuitive definitions for these concepts in the context of quantum computation that lead to operationally meaningful bounds on program output. Our assessment highlights the continuing need for statistical analyses of quantum computing program to increase our confidence in the burgeoning field of quantum information science.

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