Evolution of entanglement in quantum neural network

Ufuk Korkmaz, Deniz Türkpene, Tahir Çetin Akinci*, Serhat Şeker

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

This study concerns with the evolution of entanglement in a quantum neural network (QNN) model that is locally in contact with data environments. As a valuable resource, duration of entanglement in quantum systems is extremely important. Therefore, the effect of various initial states on the occurrence or decay of entanglement are examined in the presence of information reservoirs. In this study, central spin model was investigated as a quantum version of neural networks inspired by biological models. The architecture of the model is based on a central spin system with two nodes where the nodes are coupled to independent spin baths. Numerical results show that initial state preparation has a profound effect on the fate of entanglement. The results show that the entanglement lifetime can be adjusted by engineering the reservoir states as well as the initial states of the system of interest. The results can be used to improve the performance of the formation or distribution of entanglement in realistic communication network states.

Original languageEnglish
Article number012006
JournalIOP Conference Series: Materials Science and Engineering
Volume618
Issue number1
DOIs
Publication statusPublished - 29 Oct 2019
Event8th International Scientific Conference on Engineering, Technologies and Systems, TechSys 2019 - Plovdiv, Bulgaria
Duration: 16 May 201918 May 2019

Bibliographical note

Publisher Copyright:
© 2019 IOP Publishing Ltd.

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