Routing in quantum communication networks using reinforcement machine learning

被引：0

作者：

Roik, Jan ^{[1
]}

Bartkiewicz, Karol ^{[2
]}

Cernoch, Antonin ^{[3
]}

Lemr, Karel ^{[1
]}

机构：

[1] Palacky Univ Olomouc, Fac Sci, Joint Lab Opt Palacky Univ & Inst Phys AS CR, 17 Listopadu 50A, Olomouc 77146, Czech Republic

[2] Adam Mickiewicz Univ, Inst Spintron & Quantum Informat, Uniwersytetu Poznanskiego 2, PL-61614 Poznan, Poland

[3] Czech Acad Sci, Joint Lab Opt PU & IP AS CR, Inst Phys, 17 Listopadu 50A, Olomouc 77146, Czech Republic

来源：

QUANTUM INFORMATION PROCESSING | 2024年 / 23卷 / 03期

关键词：

Routing in quantum networks; Reinforcement learning; Proximal policy optimization; Entanglement swapping; TELEPORTATION; STATE;

D O I：

10.1007/s11128-024-04287-z

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

This paper promotes reinforcement machine learning for route-finding tasks in quantum communication networks, where, due to the non-additivity of quantum errors, classical graph path or tree-finding algorithms cannot be used. We propose using a proximal policy optimization algorithm capable of finding routes in teleportation-based quantum networks. This algorithm is benchmarked against the Monte Carlo search. The topology of our network resembles the proposed 6 G topology and analyzed that quantum errors correspond to typical errors in realistic quantum channels.

引用

页数：20

共 50 条

[1] Routing in quantum communication networks using reinforcement machine learning
Jan Roik
Karol Bartkiewicz
Antonín Černoch
Karel Lemr
[J]. Quantum Information Processing, 23
[2] Entanglement Routing For Quantum Networks: A Deep Reinforcement Learning Approach
Le, Linh
Nguyen, Tu N.
Lee, Ahyoung
Dumba, Braulio
[J]. IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), 2022, : 395 - 400
[3] Using Deep Reinforcement Learning for Routing in IP Networks
Singh, Abhiram
Sharma, Sidharth
Gumaste, Ashwin
[J]. 30TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2021), 2021,
[4] Using Reinforcement Learning to Perform Qubit Routing in Quantum Compilers
Pozzi, Matteo G.
Herbert, Steven J.
Sengupta, Akash
Mullins, Robert D.
[J]. ACM TRANSACTIONS ON QUANTUM COMPUTING, 2022, 3 (02):
[5] Quantum Leap: Exploring the Potential of Quantum Machine Learning for Communication Networks
Cherkaoui, Soumaya
[J]. PROCEEDINGS OF THE INT'L ACM CONFERENCE ON MODELING, ANALYSIS AND SIMULATION OF WIRELESS AND MOBILE SYSTEMS, MSWIM 2023, 2023, : 5 - 5
[6] Decentralized Covert Routing in Heterogeneous Networks Using Reinforcement Learning
Kong, Justin
Moore, Terrence J.
Dagefu, Fikadu T.
[J]. IEEE Communications Letters, 2024, 28 (11) : 2683 - 2687
[7] Routing using reinforcement learning in vehicular ad hoc networks
Saravanan, M.
Ganeshkumar, P.
[J]. COMPUTATIONAL INTELLIGENCE, 2020, 36 (02) : 682 - 697
[8] Improvement of Routing in Opportunistic Communication Networks of Vehicles by Unsupervised Machine Learning
Janku, Ladislava Smitkova
Hyniova, Katerina
[J]. ENGINEERING APPLICATIONS OF NEURAL NETWORKSX, 2019, 1000 : 412 - 423
[9] Using Machine Learning in Communication Networks [Invited]
Cote, David
[J]. JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING, 2018, 10 (10) : D100 - D109
[10] ORuML: Optimized Routing in wireless networks using Machine Learning
Chaudhary, Sapna
Johari, Rahul
[J]. INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2020, 33 (11)

← 1 2 3 4 5 →