A benchmark of seven neural architectures for quantum state tomography finds CNNs and CGANs most accurate and scalable, with a spiking variational autoencoder as a lower-power but less accurate option.
Efficient quantum state tomography.Nature communications 1, 149 (2010)
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Neural Network Architectures for Scalable Quantum State Tomography: Benchmarking and Memristor-Based Acceleration
A benchmark of seven neural architectures for quantum state tomography finds CNNs and CGANs most accurate and scalable, with a spiking variational autoencoder as a lower-power but less accurate option.