We are pleased to highlight our recent publication in Entropy:
Georgios Maragkopoulos, Aikaterini Mandilara, Thomas Nikas, and Dimitris Syvridis
“Real-Time Diagnostics on a QKD Link via QBER Time-Series Analysis,” Entropy 26(11):922, 2024.
🔗 Access the paper: https://doi.org/10.3390/e26110922
Key Highlights:
- Introduces a machine learning model that performs real-time detection and classification of impairments affecting QKD links—based solely on QBER and SKR time-series data.
- Capable of identifying challenges like photon addition from coexisting classical signals or fiber-related attenuation, without assumptions about the specific QKD protocol or hardware.
- Enables proactive response by network operators and key management systems, supporting timely diagnostics and remediation in hybrid quantum-classical optical networks.
This work demonstrates a crucial step toward resilient, augmentation-ready QKD-enabled infrastructure—aligned with Allegro’s mission to integrate quantum technologies into practical communications systems.