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Routing in quantum communication networks using reinforcement machine learning.
- Source :
-
Quantum Information Processing . Mar2024, Vol. 23 Issue 3, p1-20. 20p. - Publication Year :
- 2024
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15700755
- Volume :
- 23
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Quantum Information Processing
- Publication Type :
- Academic Journal
- Accession number :
- 176339291
- Full Text :
- https://doi.org/10.1007/s11128-024-04287-z