Active feedback control method for quantum communication system based on machine learning
US11817911B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 6, 2020 |
| Grant date | Nov 14, 2023 |
| Priority date | — |
| Expiry date | Dec 27, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L9/0858
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An active feedback control method for a quantum communication system based on machine learning is disclosed. In the transmission process of a quantum key distribution system, the present invention uses a pre-trained double-layer LSTM network to predict, according to a real-time ambient temperature, humidity and laser light intensity fluctuation, as well as voltage changes in the past moment, a zero-phase voltage value of a phase modulator at a receiving end at the next moment, and updates the network at a fixed time interval, so that the LSTM network can accurately predict for a long time, ensuring that the quantum key distribution system operates stably and efficiently for a long time. The present invention greatly improves the transmission efficiency of the quantum key distribution system by method of active prediction and feedback control. The present invention is not limited to being applied to quantum key distribution systems or phase encoding systems, and also applicable to quantum key distribution systems or quantum communication networks based on other encoding methods.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.