Mitigating Errors on Superconducting Quantum Processors Through Fuzzy Clustering

Year: 2024

Authors: Ahmad HG., Schiattarella R., Mastrovito P., Chiatto A., Levochkina A., Esposito M., Montemurro D., Pepe GP., Bruno A., Tafuri F., Vitiello A., Acampora G., Massarotti D.

Autors Affiliation: Univ Napoli Federico II, Dipartimento Fis Ettore Pancini, Via Cinthia, I-80126 Naples, Italy; UOS Napoli, CNR SPIN, Via Cinthia, I-80126 Naples, Italy; QuantWare, Elektronicaweg 10, NL-2628 XG Delft, Netherlands; Ist Nazl Ott CNR INO, Consiglio Nazl Ric, Largo Enrico Fermi 6, I-50125 Florence, Italy; Univ Napoli Federico II, Dipartimento Ingn Elettr & Tecnol Informaz, Via Claudio, I-80125 Naples, Italy.

Abstract: Quantum utility is severely limited in superconducting quantum hardware until now by the modest number of qubits and the relatively high level of control and readout errors, due to the intentional coupling with the external environment required for manipulation and readout of the qubit states. Practical applications in the Noisy Intermediate Scale Quantum (NISQ) era rely on Quantum Error Mitigation (QEM) techniques, which are able to improve the accuracy of the expectation values of quantum observables by implementing classical post-processing analysis from an ensemble of repeated noisy quantum circuit runs. In this work, a recent QEM technique that uses Fuzzy C-Means (FCM) clustering to specifically identify measurement error patterns is focused. For the first time, a proof-of-principle validation of the technique on a two-qubit register, obtained as a subset of a real NISQ five-qubit superconducting quantum processor based on transmon qubits is reported. It is demonstrated that the FCM-based QEM technique allows for reasonable improvement of the expectation values of single- and two-qubit gates-based quantum circuits, without necessarily invoking state-of-the-art coherence, gate, and readout fidelities. The performances of superconducting quantum hardware are still limited by the modest number of qubits and the high level of control/readout errors (NISQ era). Among measurement error mitigation techniques, a fuzzy clustering-based approach for identifying readout error patterns is emerging as a novel post-processing method for improving the hardware output. This methodology represents a valuable tool toward reliable quantum computation. image

Journal/Review: ADVANCED QUANTUM TECHNOLOGIES

Volume: 7 (7)      Pages from:   to:

More Information: The work was supported by the project SQUAD-On-chip control and advanced read-out for superconducting qubit arrays Programma STAR PLUS 2020, Finanziamento della Ricerca di Ateneo, University of Napoli Federico II, the project SuperLink – Superconducting quantum-classical linked computing systems, call QuantERA2 ERANET COFUND, CUP B53C22003320005, the PNRR MUR project PE0000023-NQSTI and the PNRR MUR project CN_00000013 -ICSC, and the Project PRIN 2022-Advanced Control and Readout of Scalable Superconducting NISQ Architectures (SuperNISQ)-CUP E53D23001910006. G.A. acknowledges financial support from the project PNRR MUR project PE0000013-FAIR.
KeyWords: fuzzy clustering; superconducting quantum computing; quantum error mitigation
DOI: 10.1002/qute.202300400

Citations: 1
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