Optimization parameter prediction-based XGBoost of TF-QKD

DOI10.1007/S11128-022-03579-6OpenAlexW4283715609MaRDI QIDQ2101489

Guoqi Huang, Wei Cui, Qin Dong, Rong-Zhen Jiao

Publication date: 6 December 2022

Published in: Quantum Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11128-022-03579-6

zbMATH Keywords

random forestback-propagation neural networktwin-field quantum key distributionparameters prediction

Mathematics Subject Classification ID

Cryptography (94A60) Software, source code, etc. for problems pertaining to quantum theory (81-04) Quantum cryptography (quantum-theoretic aspects) (81P94)

Uses Software

• randomForest
• xgboost
• XGBoost

Cites Work

• Unnamed Item
• Quantum cryptography: public key distribution and coin tossing
• Predicting optimal parameters with random forest for quantum key distribution
• Improved statistical fluctuation analysis for twin-field quantum key distribution
• Unconditional security in quantum cryptography
• Quantum cryptography based on Bell’s theorem
• Asymmetric twin-field quantum key distribution with both statistical and intensity fluctuations
• Learning representations by back-propagating errors
• Quantum cryptography

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