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QI: Fachverband Quanteninformation

QI 21: Superconducting Qubits

QI 21.2: Vortrag

Mittwoch, 12. März 2025, 15:00–15:15, HS II

Time-resolved noise characterization tool to track fluctuating noise effects in superconducting qubits — •Abhishek Agarwal¹, Ke Wang^2,3, Brian Marinelli^2,3, Lachlan P Lindoy¹, Deep Lall¹, Yannic Rath¹, David I Santiago^2,3, Irfan Siddiqi^2,3, and Ivan Rungger^1,4 — ¹National Physical Laboratory, Teddington, United Kingdom — ²Quantum Nanoelectronics Laboratory, Department of Physics, University of California, Berkeley, USA — ³Applied Math and Computational Research Division, Lawrence Berkeley National Lab, Berkeley, USA — ⁴Department of Computer Science, Royal Holloway, University of London, Egham, United Kingdom

Superconducting qubits have seen rapid increases in their coherence in the last few decades. However, low-frequency noise present in the qubits still causes non-Markovian errors and qubit instability. Collectively characterising different sources of low-frequency noise can be challenging, and typically noise sources such as charge parity switching and coupling to thermal fluctuators are characterised independently. In order to characterise the combined noise, we develop a tool that uses few-shot data to detect and diagnose qubit frequency fluctuations, as well as a time series segmentation tool to further disambiguate different sources of fluctuations. We demonstrate the tool by computing time and spectrally resolved noise properties. Our framework for fluctuation detection and disambiguation can be used to thoroughly characterize low-frequency noise in qubits as well as develop methods to mitigate the noise.

Keywords: noise; fluctuations; tls; superconducting qubits; characterisation