Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics

Imtiaz Alamgir; Luigi Di Lauro; Stefania Sciara; Abdul Rahim Aadhi; Celine Mazoukh; Hao Yu; Bennet Fischer; Nicolas Perron; Nicola Montaut; Mario Chemnitz; Brent E. Little; Sai T. Chu; David J. Moss; Zhiming Wang; Roberto Morandotti

doi:10.1109/ICTON62926.2024.10647338

Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics

Imtiaz Alamgir
, Luigi Di Lauro
, Stefania Sciara
, Abdul Rahim Aadhi
, Celine Mazoukh
, Hao Yu
, Bennet Fischer
, Nicolas Perron
, Nicola Montaut
, Mario Chemnitz
, Brent E. Little
, Sai T. Chu
, David J. Moss
, Zhiming Wang
, Roberto Morandotti^*

^*Corresponding author for this work

Department of Physics

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Integrated photonics is contributing to new emerging technologies for advanced signal processing, based on machine learning and quantum information science. In this work, we utilize compact, reconfigurable, on-chip devices to develop photonic artificial neural networks and quantum signal processors for telecommunication applications. Our work demonstrates the recovery and reconstruction of high-speed telecommunication signals with ultralow latency, as well as enhances the speed and security of quantum communication. Characterized by their highly efficient and intelligent processing, parallelization, and reduced power consumption, these technologies are set to pave the way for the next generation of telecom networks. © 2024 IEEE.

Original language	English
Title of host publication	2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings
Editors	Francesco Prudenzano, Marian Marciniak
Publisher	IEEE
ISBN (Electronic)	979-8-3503-7732-3
DOIs	https://doi.org/10.1109/ICTON62926.2024.10647338
Publication status	Published - 2024
Event	24th International Conference on Transparent Optical Networks (ICTON 2024) - Bari, Italy Duration: 14 Jul 2024 → 18 Jul 2024 https://icton2024.fbk.eu/home

Publication series

Name	International Conference on Transparent Optical Networks
ISSN (Print)	2162-7339

Conference

Conference	24th International Conference on Transparent Optical Networks (ICTON 2024)
Abbreviated title	ICTON2024
Place	Italy
City	Bari
Period	14/07/24 → 18/07/24
Internet address	https://icton2024.fbk.eu/home

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

artificial neural networks
entangled photon states
Integrated photonics
machine learning
quantum key distribution

Access Output

10.1109/ICTON62926.2024.10647338

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Alamgir, I., Di Lauro, L., Sciara, S., Aadhi, A. R., Mazoukh, C., Yu, H., Fischer, B., Perron, N., Montaut, N., Chemnitz, M., Little, B. E., Chu, S. T., Moss, D. J., Wang, Z., & Morandotti, R. (2024). Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics. In F. Prudenzano, & M. Marciniak (Eds.), 2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings (International Conference on Transparent Optical Networks). IEEE. https://doi.org/10.1109/ICTON62926.2024.10647338

Alamgir, Imtiaz ; Di Lauro, Luigi ; Sciara, Stefania et al. / Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics. 2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings. editor / Francesco Prudenzano ; Marian Marciniak. IEEE, 2024. (International Conference on Transparent Optical Networks).

@inproceedings{8f16f72fca9248e9b0fd3d4c6115e032,

title = "Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics",

abstract = "Integrated photonics is contributing to new emerging technologies for advanced signal processing, based on machine learning and quantum information science. In this work, we utilize compact, reconfigurable, on-chip devices to develop photonic artificial neural networks and quantum signal processors for telecommunication applications. Our work demonstrates the recovery and reconstruction of high-speed telecommunication signals with ultralow latency, as well as enhances the speed and security of quantum communication. Characterized by their highly efficient and intelligent processing, parallelization, and reduced power consumption, these technologies are set to pave the way for the next generation of telecom networks. {\textcopyright} 2024 IEEE.",

keywords = "artificial neural networks, entangled photon states, Integrated photonics, machine learning, quantum key distribution",

author = "Imtiaz Alamgir and \{Di Lauro\}, Luigi and Stefania Sciara and Aadhi, \{Abdul Rahim\} and Celine Mazoukh and Hao Yu and Bennet Fischer and Nicolas Perron and Nicola Montaut and Mario Chemnitz and Little, \{Brent E.\} and Chu, \{Sai T.\} and Moss, \{David J.\} and Zhiming Wang and Roberto Morandotti",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).; 24th International Conference on Transparent Optical Networks (ICTON 2024), ICTON2024 ; Conference date: 14-07-2024 Through 18-07-2024",

year = "2024",

doi = "10.1109/ICTON62926.2024.10647338",

language = "English",

series = "International Conference on Transparent Optical Networks",

publisher = "IEEE",

editor = "Francesco Prudenzano and Marian Marciniak",

booktitle = "2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings",

address = "United States",

url = "https://icton2024.fbk.eu/home",

}

Alamgir, I, Di Lauro, L, Sciara, S, Aadhi, AR, Mazoukh, C, Yu, H, Fischer, B, Perron, N, Montaut, N, Chemnitz, M, Little, BE, Chu, ST, Moss, DJ, Wang, Z & Morandotti, R 2024, Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics. in F Prudenzano & M Marciniak (eds), 2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings. International Conference on Transparent Optical Networks, IEEE, 24th International Conference on Transparent Optical Networks (ICTON 2024), Bari, Italy, 14/07/24. https://doi.org/10.1109/ICTON62926.2024.10647338

Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics. / Alamgir, Imtiaz; Di Lauro, Luigi; Sciara, Stefania et al.
2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings. ed. / Francesco Prudenzano; Marian Marciniak. IEEE, 2024. (International Conference on Transparent Optical Networks).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics

AU - Alamgir, Imtiaz

AU - Di Lauro, Luigi

AU - Sciara, Stefania

AU - Aadhi, Abdul Rahim

AU - Mazoukh, Celine

AU - Yu, Hao

AU - Fischer, Bennet

AU - Perron, Nicolas

AU - Montaut, Nicola

AU - Chemnitz, Mario

AU - Little, Brent E.

AU - Chu, Sai T.

AU - Moss, David J.

AU - Wang, Zhiming

AU - Morandotti, Roberto

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2024

Y1 - 2024

N2 - Integrated photonics is contributing to new emerging technologies for advanced signal processing, based on machine learning and quantum information science. In this work, we utilize compact, reconfigurable, on-chip devices to develop photonic artificial neural networks and quantum signal processors for telecommunication applications. Our work demonstrates the recovery and reconstruction of high-speed telecommunication signals with ultralow latency, as well as enhances the speed and security of quantum communication. Characterized by their highly efficient and intelligent processing, parallelization, and reduced power consumption, these technologies are set to pave the way for the next generation of telecom networks. © 2024 IEEE.

AB - Integrated photonics is contributing to new emerging technologies for advanced signal processing, based on machine learning and quantum information science. In this work, we utilize compact, reconfigurable, on-chip devices to develop photonic artificial neural networks and quantum signal processors for telecommunication applications. Our work demonstrates the recovery and reconstruction of high-speed telecommunication signals with ultralow latency, as well as enhances the speed and security of quantum communication. Characterized by their highly efficient and intelligent processing, parallelization, and reduced power consumption, these technologies are set to pave the way for the next generation of telecom networks. © 2024 IEEE.

KW - artificial neural networks

KW - entangled photon states

KW - Integrated photonics

KW - machine learning

KW - quantum key distribution

UR - https://www.scopus.com/pages/publications/85204079334

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85204079334&origin=recordpage

U2 - 10.1109/ICTON62926.2024.10647338

DO - 10.1109/ICTON62926.2024.10647338

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - International Conference on Transparent Optical Networks

BT - 2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings

A2 - Prudenzano, Francesco

A2 - Marciniak, Marian

PB - IEEE

T2 - 24th International Conference on Transparent Optical Networks (ICTON 2024)

Y2 - 14 July 2024 through 18 July 2024

ER -

Alamgir I, Di Lauro L, Sciara S, Aadhi AR, Mazoukh C, Yu H et al. Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics. In Prudenzano F, Marciniak M, editors, 2024 24th International Conference on Transparent Optical Networks (ICTON) - Conference Proceedings. IEEE. 2024. (International Conference on Transparent Optical Networks). Epub 2024 Sept 2. doi: 10.1109/ICTON62926.2024.10647338

Quantum information and Artificial Neural Networks-based Signal Processing using Integrated Photonics

Abstract

Publication series

Conference

Bibliographical note

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this