[10p-E219-1~10] 4.7 Quantum Optics, Nonlinear Optics and Structured Optics

3:45 PM - 4:00 PM JST(6:45 AM - 7:00 AM UTC)English Presentation

[10p-E219-6] Interpretable Machine Learning for Secure Key Rate Prediction and Fiber Anomaly Detection in Twin-Field QKD over Multicore Fiber

〇(D)Neha Kumari¹, Ritu Raj Singh¹ (1.Netaji Subhas University of Technology)

Keywords:

Twin-Field Quantum Key Distribution,Multicore Fiber,Quantum Communication

Interpretable machine learning predicts secure key rate and detects fiber anomalies in multicore-fiber Twin-Field QKD (TF-QKD). Trained in 3,000 simulations, XGBoost achieved R²=0.951 and RMSE=0.044 Mbps for secure key rate estimation. SHAP identified classical power and distance as dominant factors. Isolation Forest detected anomalous fiber states with 0.87 precision and 0.83 recall.