Role of Entanglement in Quantum Neural Networks (QNN)


Starting with the theoretical basis of quantum computing, entanglement has been explored as one of the key resources required for quantum computation, the functional dependence of the entanglement measures on spin correlation functions has been established and the role of entanglement in implementation of QNN has been emphasized. Necessary and sufficient conditions for the general two-qubit state to be maximally entangled state (MES) have been obtained and a new set of MES constituting a very powerful and reliable eigen basis (different from magic bases) of two-qubit systems has been constructed. In terms of the MES constituting this basis, Bell’s States have been generated and all the qubits of two-qubit system have been obtained. Carrying out the correct computation of XOR function in neural network, it has been shown that QNN requires the proper correlation between the input and output qubits and the presence of appropriate entanglement in the system guarantees this correlation.

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Singh, M. and Rajput, B. (2015) Role of Entanglement in Quantum Neural Networks (QNN). Journal of Modern Physics, 6, 1908-1920. doi: 10.4236/jmp.2015.613196.

Conflicts of Interest

The authors declare no conflicts of interest.


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