Role of Entanglement in Quantum Neural Networks (QNN)

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 sta...

Neural Networks and Quantum Entanglement

مروری بر شبکه­ های عصبی کوانتومی

In this paper the development of quantum neural networks (QNN), and some of presented models and physical implementation are reviewed. How of making use of double-slit experiment for implementing QNN and methods of designing as well as examples of two-layer hybrid networks in QNN constructed from quantum neurons and classical neurons are represented. Some application models of the networks (QNN...

Quantum Networks for Concentrating Entanglement

If two parties, Alice and Bob, share some number, n, of partially entangled pairs of qubits, then it is possible for them to concentrate these pairs into some smaller number of maximally entangled states. We present a simplified version of the algorithm for such entanglement concentration, and we describe efficient networks for implementing these operations.

Entanglement percolation in quantum complex networks.

Quantum networks are essential to quantum information distributed applications, and communicating over them is a key challenge. Complex networks have rich and intriguing properties, which are as yet unexplored in the quantum setting. Here, we study the effect of entanglement percolation as a means to establish long-distance entanglement between arbitrary nodes of quantum complex networks. We de...