Towards optimum phase noise compensation for CV-QKD systems

Hou Man Chin; Nitin Jain; Ulrik L. Andersen; Tobias Gehring

Towards optimum phase noise compensation for CV-QKD systems

Hou Man Chin^*
, Nitin Jain
, Ulrik L. Andersen
, Tobias Gehring

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

We experimentally examine the performance of a machine learning based phase estimation and compensation framework for Gaussian modulated continuous variable quantum key distribution relative to a transmitted local oscillator and ideal phase compensation.

Original language	English
Title of host publication	Proceedings of 2023 Conference on Lasers and Electro-Optics
Number of pages	2
Publisher	IEEE
Publication date	2023
Article number	FF2A.4
ISBN (Electronic)	9781957171258
Publication status	Published - 2023
Event	CLEO: Science and Innovations 2023 - San Jose McEnery Convention Center, San Jose, United States Duration: 7 May 2023 → 12 May 2023 https://www.cleoconference.org

Conference

Conference	CLEO: Science and Innovations 2023
Location	San Jose McEnery Convention Center
Country/Territory	United States
City	San Jose
Period	07/05/2023 → 12/05/2023
Internet address	https://www.cleoconference.org

Bibliographical note

Funding Information:
The authors acknowledge support from Innovation Fund Denmark (CryptQ project #0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 101017733.

Funding Information:
The authors acknowledge support from Innovation Fund Denmark (CryptQ project #0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union,s Horizon 2020 research and innovation programme under Grant Agreement No 101017733.

Publisher Copyright:
© 2023 The Author(s)

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@inproceedings{84678da23e714ec3bbf0645159448778,

title = "Towards optimum phase noise compensation for CV-QKD systems",

abstract = "We experimentally examine the performance of a machine learning based phase estimation and compensation framework for Gaussian modulated continuous variable quantum key distribution relative to a transmitted local oscillator and ideal phase compensation.",

author = "Chin, \{Hou Man\} and Nitin Jain and Andersen, \{Ulrik L.\} and Tobias Gehring",

note = "Funding Information: The authors acknowledge support from Innovation Fund Denmark (CryptQ project \#0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under Grant Agreement No 101017733. Funding Information: The authors acknowledge support from Innovation Fund Denmark (CryptQ project \#0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union,s Horizon 2020 research and innovation programme under Grant Agreement No 101017733. Publisher Copyright: {\textcopyright} 2023 The Author(s); CLEO: Science and Innovations 2023, CLEO 2023 ; Conference date: 07-05-2023 Through 12-05-2023",

year = "2023",

language = "English",

booktitle = "Proceedings of 2023 Conference on Lasers and Electro-Optics",

publisher = "IEEE",

address = "United States",

url = "https://www.cleoconference.org",

}

TY - GEN

T1 - Towards optimum phase noise compensation for CV-QKD systems

AU - Chin, Hou Man

AU - Jain, Nitin

AU - Andersen, Ulrik L.

AU - Gehring, Tobias

N1 - Funding Information: The authors acknowledge support from Innovation Fund Denmark (CryptQ project #0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 101017733. Funding Information: The authors acknowledge support from Innovation Fund Denmark (CryptQ project #0175-00018A), and the DNRF Center for Macroscopic Quantum States (bigQ, DNRF142), and DCC [4]. This project was funded within the QuantERA II Programme that has received funding from the European Union,s Horizon 2020 research and innovation programme under Grant Agreement No 101017733. Publisher Copyright: © 2023 The Author(s)

PY - 2023

Y1 - 2023

N2 - We experimentally examine the performance of a machine learning based phase estimation and compensation framework for Gaussian modulated continuous variable quantum key distribution relative to a transmitted local oscillator and ideal phase compensation.

AB - We experimentally examine the performance of a machine learning based phase estimation and compensation framework for Gaussian modulated continuous variable quantum key distribution relative to a transmitted local oscillator and ideal phase compensation.

M3 - Article in proceedings

AN - SCOPUS:85176331903

BT - Proceedings of 2023 Conference on Lasers and Electro-Optics

PB - IEEE

T2 - CLEO: Science and Innovations 2023

Y2 - 7 May 2023 through 12 May 2023

ER -

Towards optimum phase noise compensation for CV-QKD systems

Abstract

Conference

Bibliographical note

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