Papers › Neural-network quantum state tomography
Neural-network quantum state tomography
D. Koutny, L. Motka, Z. Hradil, J. Rehacek, L. L. Sanchez-Soto
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We revisit the application of neural networks techniques to quantum state tomography. We confirm that the positivity constraint can be successfully implemented with trained networks that convert outputs from standard feed-forward neural networks to valid descriptions of quantum states. Any standard neural-network architecture can be adapted with our method. Our results open possibilities to use state-of-the-art deep-learning methods for quantum state reconstruction under various types of noise.
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