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pro vyhledávání: '"Dudas, Julien"'
Quantum neural networks have the potential to be seamlessly integrated with quantum devices for the automatic recognition of quantum states. However, performing complex tasks requires a large number of neurons densely connected through trainable, par
Externí odkaz:
http://arxiv.org/abs/2411.19112
Autor:
Dudas, Julien, Carles, Baptiste, Plouet, Erwan, Mizrahi, Alice, Grollier, Julie, Marković, Danijela
Quantum reservoir computing is a promising approach for quantum neural networks, capable of solving hard learning tasks on both classical and quantum input data. However, current approaches with qubits suffer from limited connectivity. We propose an
Externí odkaz:
http://arxiv.org/abs/2209.03221
We analyze the properties of a quantum system composed of two coherently coupled quantum oscillators and show through simulations that it fulfills the two properties required for reservoir computing: non-linearity and fading memory. We first show tha
Externí odkaz:
http://arxiv.org/abs/2204.14273
Akademický článek
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