Mitigating Errors on Superconducting Quantum Processors through Fuzzy Clustering

Bibliographic Details
Title: Mitigating Errors on Superconducting Quantum Processors through Fuzzy Clustering
Authors: Ahmad, Halima G., Schiattarella, Roberto, Mastrovito, Pasquale, Chiatto, Angela, Levochkina, Anna, Esposito, Martina, Montemurro, Domenico, Pepe, Giovanni P., Bruno, Alessandro, Tafuri, Francesco, Vitiello, Autilia, Acampora, Giovanni, Massarotti, Davide
Publication Year: 2024
Collection: Condensed Matter
Quantum Physics
Subject Terms: Quantum Physics, Condensed Matter - Superconductivity
More Details: Quantum utility has been 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, we focus on a recent QEM technique that uses Fuzzy C-Means (FCM) clustering to specifically identify measurement error patterns. For the first time, we report a proof-of-principle validation of the technique on a 2-qubit register, obtained as a subset of a real NISQ 5-qubit superconducting quantum processor based on transmon qubits. We demonstrate 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.
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2402.01815
Accession Number: edsarx.2402.01815
Database: arXiv
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