Machine learning on time traces of repetitive qubit readouts improves fidelity over threshold photon counting by identifying back-action.
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Theoretical calculation of phonon-mediated inter-dot tunnel and intra-dot spin-flip rates in a two-electron DQD under phonon temperature gradient, shown to be quantitatively consistent with prior experiment.
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Repetitive Readout Enhanced by Machine Learning
Machine learning on time traces of repetitive qubit readouts improves fidelity over threshold photon counting by identifying back-action.