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Identifying single electron charge sensor events using wavelet edge detection.

J R Prance1, B J Van Bael, C B Simmons

  • 1University of Wisconsin-Madison, Wisconsin 53706, USA. Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK.

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|May 2, 2015
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Summary
This summary is machine-generated.

Wavelet edge detection offers a robust method for identifying events in noisy nanoelectronic charge sensor signals for solid-state qubits. This technique outperforms traditional thresholding, especially in the presence of low-frequency noise.

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Area of Science:

  • Quantum computing
  • Nanoelectronics
  • Signal processing

Background:

  • Solid-state qubit operation depends on single-shot readout via nanoelectronic charge sensors.
  • Accurate event detection in noisy sensor signals is vital for high-fidelity qubit readout.
  • Traditional thresholding methods struggle with low-frequency noise and signal drift.

Purpose of the Study:

  • To introduce and evaluate wavelet edge detection as an alternative to thresholding for charge sensor event identification.
  • To demonstrate the robustness and performance of wavelet detection in realistic qubit readout scenarios.

Main Methods:

  • Utilized wavelet edge detection for analyzing nanoelectronic charge sensor signals.
  • Compared the performance of wavelet detection against traditional thresholding methods.
  • Employed realistic signal data and a single tunable parameter for evaluation.

Main Results:

  • Wavelet edge detection successfully identified charge sensor events.
  • The technique demonstrated superior performance compared to thresholding.
  • Wavelet detection showed significantly higher tolerance to 1/f and low-frequency noise.

Conclusions:

  • Wavelet edge detection is a convenient and effective method for charge sensor event identification in solid-state qubit readout.
  • This approach enhances readout fidelity by mitigating the impact of noise and signal drift.
  • Wavelet detection represents a significant improvement over conventional thresholding techniques for noisy qubit signals.