AI-Enabled Large-Scale Entanglement Distribution Quantum Networks

Rui Wang; Siddarth Koduru Joshi; George Kanellos; Djeylan Vincent Aktas; John G Rarity; Reza Nejabati; Dimitra Simeonidou

AI-Enabled Large-Scale Entanglement Distribution Quantum Networks

Rui Wang^*, Siddarth Koduru Joshi, George Kanellos, Djeylan Vincent Aktas, John G Rarity, Reza Nejabati, Dimitra Simeonidou

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

127 Downloads (Pure)

Abstract

We propose an entanglement distribution switching architecture to support large-scale dynamic quantum networking. Deep neural networks are further developed for predicting the performance of a dynamic entanglement distribution network utilizing the proposed architecture

Original language	English
Title of host publication	Optical Fiber Communication Conference 2021
Place of Publication	Washington, DC United States
Publisher	Optical Society of America (OSA)
ISBN (Print)	9781943580866
Publication status	Published - 11 Jun 2021

Research Groups and Themes

Bristol Quantum Information Institute
QETLabs
Photonics and Quantum

Access to Document

Full-text PDF (accepted author manuscript)
This is the accepted author manuscript (AAM). The final published version (version of record) is available online via OSA publishing at https://www.osapublishing.org/abstract.cfm?URI=OFC-2021-Tu1I.4. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 455 KB

https://www.osapublishing.org/abstract.cfm?URI=OFC-2021-Tu1I.4

Handle.net

Persistent link

Cite this

@inproceedings{ab748705ec83462a8a1e27a6db743f83,

title = "AI-Enabled Large-Scale Entanglement Distribution Quantum Networks",

abstract = "We propose an entanglement distribution switching architecture to support large-scale dynamic quantum networking. Deep neural networks are further developed for predicting the performance of a dynamic entanglement distribution network utilizing the proposed architecture",

author = "Rui Wang and Joshi, {Siddarth Koduru} and George Kanellos and Aktas, {Djeylan Vincent} and Rarity, {John G} and Reza Nejabati and Dimitra Simeonidou",

year = "2021",

month = jun,

day = "11",

language = "English",

isbn = "9781943580866",

booktitle = "Optical Fiber Communication Conference 2021",

publisher = "Optical Society of America (OSA)",

address = "United States",

}

TY - GEN

T1 - AI-Enabled Large-Scale Entanglement Distribution Quantum Networks

AU - Wang, Rui

AU - Joshi, Siddarth Koduru

AU - Kanellos, George

AU - Aktas, Djeylan Vincent

AU - Rarity, John G

AU - Nejabati, Reza

AU - Simeonidou, Dimitra

PY - 2021/6/11

Y1 - 2021/6/11

N2 - We propose an entanglement distribution switching architecture to support large-scale dynamic quantum networking. Deep neural networks are further developed for predicting the performance of a dynamic entanglement distribution network utilizing the proposed architecture

AB - We propose an entanglement distribution switching architecture to support large-scale dynamic quantum networking. Deep neural networks are further developed for predicting the performance of a dynamic entanglement distribution network utilizing the proposed architecture

M3 - Conference Contribution (Conference Proceeding)

SN - 9781943580866

BT - Optical Fiber Communication Conference 2021

PB - Optical Society of America (OSA)

CY - Washington, DC United States

ER -

AI-Enabled Large-Scale Entanglement Distribution Quantum Networks

Abstract

Research Groups and Themes

Access to Document

Handle.net

Fingerprint

Cite this