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Denoising quantum states with Quantum Autoencoders -- Theory and Applications
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We implement a Quantum Autoencoder (QAE) as a quantum circuit capable of correcting Greenberger-Horne-Zeilinger (GHZ) states subject to various noisy quantum channels : the bit-flip channel and the more general quantum depolarizing channel. The QAE shows particularly interesting results, as it enables to perform an almost perfect reconstruction of noisy states, but can also, more surprisingly, act as a generative model to create noise-free GHZ states. Finally, we detail a useful application of QAEs : Quantum Secret Sharing (QSS). We analyze how noise corrupts QSS, causing it to fail, and show how the QAE allows the QSS protocol to succeed even in the presence of noise.
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Unsupervised Feature Extraction and Reconstruction Using Parameterized Quantum Circuits
Quantum autoencoder with QCNN encoder reaches 97.59% accuracy on binary MNIST 0/1 classification using a single compressed qubit and a classical SVM readout.
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