Twin-Field QKD Global Phase Tracking via FPGA S2S Network
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Solution Overview
Problem
Existing twin-field quantum key distribution systems are sensitive to phase interference, leading to unsatisfactory single-photon interference and low code rate efficiency due to inefficient global phase stabilization methods like two-phase or four-phase scanning with time division multiplexing.
Innovation Solution
A global phase tracking and predicting method using a time-aware sequence to sequence network (S2S) mounted on a field-programmable gate array (FPGA), which filters detector counts, calculates weights through an Attention layer, and employs a T-LSTM network for real-time phase compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If two-phase scanning or four-phase scanning with time division multiplexing is used to stabilize global phase, then phase stabilization is achieved, but system efficiency decreases and code rate fluctuation increases
Solution Approach 1:
The patent replaces traditional mechanical scanning methods (two-phase or four-phase scanning with time division multiplexing) with an intelligent prediction system based on LSTM neural networks. The system uses environmental sensors to collect temperature and humidity data, processes this information through a trained LSTM model, and predicts optimal phase compensation values in real-time, eliminating the need for time-consuming phase point scanning while maintaining phase stabilization effectiveness
Solution Approach 2:
The system implements self-service by using environmental sensors to automatically monitor temperature and humidity changes, feeding this data into the LSTM prediction model, and generating phase compensation values without requiring external intervention or traditional scanning procedures. The system serves itself by leveraging environmental data to maintain its own operational stability
2Reliability
If traditional phase scanning methods are used, then global phase can be calibrated, but calibration accuracy is low and code rate fluctuation is high
Solution Approach 1:
The patent replaces traditional mechanical phase scanning and calibration methods with an intelligent prediction system. Instead of relying on periodic scanning to detect phase drift, the system uses environmental sensors combined with an LSTM neural network to predict phase changes proactively, achieving higher calibration accuracy by continuously adapting to environmental conditions rather than periodically measuring them
Solution Approach 2:
The system performs preliminary action by using the LSTM model to predict future phase drift based on current environmental conditions. Rather than waiting for phase instability to occur and then correcting it through scanning, the system anticipates phase changes and applies compensation in advance, preventing code rate fluctuation before it happens
Data Source
AI summary
A global phase tracking and predicting method suitable for a twin-field quantum key distribution system is provided. A time-aware sequence to sequence network (S2S) specially mounted on a field-programmable gate array (FPGA) is designed. In the global phase tracking and predicting method, global phase changes at a plurality of subsequent time points are tracked and predicted according to two-phase scan count and external environmental parameters acquired in real time, and the tracking and prediction results are then used to compensate phase disturbance in real time, thereby ensuring long-time global phase stability.