Two matched-filter algorithms for neutral-atom qubit readout reduce measurement errors by 32-43% versus Gaussian thresholds and use 100x fewer parameters than CNNs while remaining scalable.
For each boundary size, the weights learned in the training step are used to predict the qubit states for all feature vectors x in the validation set by computing ˆ y = ˆWx
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Efficient measurement of neutral-atom qubits with matched filters
Two matched-filter algorithms for neutral-atom qubit readout reduce measurement errors by 32-43% versus Gaussian thresholds and use 100x fewer parameters than CNNs while remaining scalable.