QUANTUM NEURAL NETWORK
作者： Neven Hartmut , Farhi Edward Henry
DOI:
关键词: Quantum neural network 、 Logic gate 、 Qubit 、 Quantum state 、 Topology 、 Quantum gate 、 Task (computing) 、 Encoding (memory) 、 Layer (object-oriented design) 、 Computer science
摘要: A quantum neural network architecture. In one aspect, a trained to perform machine learning task includes: an input layer comprising (i) multiple qubits prepared in initial state encoding data input, and (ii) target qubit; sequence of intermediate layers, each logic gates that operate on the output measurement gate operates qubit provides as representing solution task.
lens.org 参考文章(5)
Panchi Li, Hong Xiao, Model and algorithm of quantum-inspired neural network with sequence input based on controlled rotation gates Applied Intelligence. ,vol. 40, pp. 107- 126 ,(2014) , 10.1007/S10489-013-0447-3
Adenilton J. da Silva, Wilson R. de Oliveira, Teresa B. Ludermir, Classical and superposed learning for quantum weightless neural networks Neurocomputing. ,vol. 75, pp. 52- 60 ,(2012) , 10.1016/J.NEUCOM.2011.03.055
H. Neven, J. Goldstone, E. Farhi, S. Gutmann, Quantum Algorithms for Fixed Qubit Architectures arXiv: Quantum Physics. ,(2017)
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, Hartmut Neven, Barren plateaus in quantum neural network training landscapes arXiv: Quantum Physics. ,(2018) , 10.1038/S41467-018-07090-4
Oscar Dahlsten, M. S. Kim, Kwok Ho Wan, Robert Gardner, Hlér Kristjánsson, Quantum generalisation of feedforward neural networks arXiv: Quantum Physics. ,(2016) , 10.1038/S41534-017-0032-4