Identifying single electron charge sensor events using wavelet edge detection

Abstract

The operation of solid-state qubits often relies on single-shot readout using a nanoelectronic charge sensor, and the detection of events in a noisy sensor signal is crucial for high fidelity readout of such qubits. The most common detection scheme, comparing the signal to a threshold value, is accurate at low noise levels but is not robust to low-frequency noise and signal drift. We describe an alternative method for identifying charge sensor events using wavelet edge detection. The technique is convenient to use and we show that, with realistic signals and a single tunable parameter, wavelet detection can outperform thresholding and is significantly more tolerant to 1/f and low-frequency noise.

11 pages, 4 figures

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Cited by in corpus (13)

• Quantum Zeno effect in the strong measurement regime of circuit quantum electrodynamics
• Benchmarking high fidelity single-shot readout of semiconductor qubits
• Fast charge sensing of Si/SiGe quantum dots via a high-frequency accumulation gate
• Nonrenewal statistics in transport through quantum dots
• Robust and fast post-processing of single-shot spin qubit detection events with a neural network
• Real-time feedback protocols for optimizing fault-tolerant two-qubit gate fidelities in a silicon spin system
• Characterization of a gate-defined double quantum dot in a Si/SiGe nanomembrane
• Electrostatic control of quasiparticle poisoning in a hybrid semiconductor-superconductor island
• Random telegraph signal analysis with a recurrent neural network
• Determining the parameters of a random telegraph signal by digital low pass filtering
• Wavelet correlation noise analysis for qubit operation variable time series
• Threshold-independent method for single-shot readout of spin qubits in semiconductor quantum dots
• Spin-qubit readout analysis based on a hidden Markov model