Credible Nearest Neighbor Query in Uncertain Network

Gao, Jun

doi:10.14257/ijgdc.2014.7.1.02

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…In [42] Al-akashi Falah proposed a method for improving learning performance in neural networks. In [43] Gao Jun proposed a credible nearest neighbour query in uncertain network. In [44] Bai Xue et al, implemented a new clustering model based on Word2vec mining on Sina Weibo usersꞌ Tags.…”

Section: Related Studiesmentioning

confidence: 99%

Optimal Remote Qubit Teleportation Using Node2vec

Lee

Madhavi

2023

Teh. vjesn.

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Much research work is done on implementing quantum teleportation and entanglement swapping for remote entanglement. Due to dynamical topological changes in quantum networks, nodes have to construct the shortest paths every time they want to communicate with a remote neighbour. But due to the entanglement failures remote entanglement establishment is still a challenging task. Also as the nodes know only about their neighbouring nodes computing optimal paths between source and remote nodes is time consuming too. In finding the next best neighbour in the optimal path between a given source and remote nodes so as to decrease the entanglement cost, deep learning techniques can be applied. In this paper we defined throughput of the quantum network as the maximum qubits transmitted with minimum entanglement cost. Much of research work is done to improve the throughput of the quantum network using the deep learning techniques. In this paper we adopted deep learning techniques for implementing remote entanglement between two non-neighbour nodes using remote qubit teleportation and entanglement swapping. The proposed method called Optimal Remote Qubit Teleportation outperforms the throughput obtained by the state of art approach.

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Section: Related Studiesmentioning

confidence: 99%