Mitigation of correlated readout errors without randomized measurements

Quantum simulation, the study of strongly correlated quantum matter using synthetic quantum systems, has been the most successful application of quantum computers to date. It often requires determining observables with high precision, for example when studying critical phenomena near quantum phase t...

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Hauptverfasser: Aasen, Adrian Skasberg (VerfasserIn) , Di Giovanni, Andras (VerfasserIn) , Rotzinger, Hannes (VerfasserIn) , Ustinov, Alexey (VerfasserIn) , Gaerttner, Martin (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 4 August, 2025
In: Physical review
Year: 2025, Jahrgang: 112, Heft: 2, Pages: 1-17
ISSN:2469-9934
DOI:10.1103/6p6s-t8b7
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1103/6p6s-t8b7
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Verfasserangaben:Adrian Skasberg Aasen, Andras Di Giovanni, Hannes Rotzinger, Alexey Ustinov, and Martin Gaerttner
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Zusammenfassung:Quantum simulation, the study of strongly correlated quantum matter using synthetic quantum systems, has been the most successful application of quantum computers to date. It often requires determining observables with high precision, for example when studying critical phenomena near quantum phase transitions. Thus, readout errors must be carefully characterized and mitigated in data postprocessing, using scalable and noise-model agnostic protocols. We present a readout error-mitigation protocol that uses only single-qubit Pauli measurements and avoids experimentally challenging randomized measurements. The proposed approach captures a very broad class of correlated noise models and is scalable to large qubit systems. It is based on a complete and efficient characterization of few-qubit correlated positive operator-valued measures, using overlapping detector tomography. To assess the effectiveness of the protocol, observables are extracted from simulations involving up to 100 qubits employing readout errors obtained from experiments with superconducting qubits.
Beschreibung:Gesehen am 11.12.2025
Beschreibung:Online Resource
ISSN:2469-9934
DOI:10.1103/6p6s-t8b7