A Novel Hybrid Digital and Analog Laser Synchronization System
Laser synchronization is a technique of stabilizing the frequency difference between two lasers so that their frequencies change in synchronization. This technique is vital for both scientific and industrial applications. Conventional synchronization systems, whether digital or analog, exhibit inherent limitations in terms of accuracy and bandwidth. Current hybrid synchronization systems are usually based on hybrid digital and analog phase-locked loops (PLLs), which can partially address this limitation. However, since they are structured serially, their bandwidth remains constrained by the design of the analog component. This paper presents a hybrid “digital + analog” laser synchronization system with a parallel structure. The system's digital and analog locking loops operate independently, providing long-term stability and locking accuracy, respectively. This approach addresses the accuracy and bandwidth limitations present in serial hybrid digital and analog PLLs. We synchronized a single-frequency laser (SFL) to a mode-locked laser (MLL), achieving a frequency offset fluctuation of less than 2.5 Hz over 24 hours. Additionally, by synchronizing two SFLs to a repetition-frequency locked MLL, we achieved indirect synchronization between SFLs with a frequency offset of 10.6 GHz and a fluctuation of less than 5 Hz in 24 hours. These results demonstrate the robust long-term and short-term stability of the system. Based on this synchronization system, we proposed a photonic-assisted microwave frequency identification scheme with a detection error of less than 0.6 MHz. The high performance of the synchronization system enables the proposed frequency identification scheme to achieve high measurement accuracy and a theoretically extensive frequency range.
Authors
- Tianwei Jiang (ORCID: https://orcid.org/0000-0002-9005-4779)
- Shangsu Ding (ORCID: https://orcid.org/0000-0003-3019-1293)
- Mingwen Zhu
- Bin Luo (ORCID: https://orcid.org/0000-0001-9231-0273)
- Jianming Shang (ORCID: https://orcid.org/0000-0002-3522-8035)
- Song Yu (ORCID: https://orcid.org/0000-0003-1489-9021)
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- Journal of Lightwave Technology
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1109/jlt.2024.3504576
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00