Modeling of Radiation-Induced Gain Degradation and Photobleaching in Er/Yb co-doped Fiber Lasers

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Authors: Yiming Zhu, Qiubai Yang, Fan Wang, Chongyun Shao, Meng Wang, Lei Zhang, Chunlei Yu, Lili Hu
Cited by: 0

Abstract

In response to the long-term performance degradation of erbium ytterbium co doped fiber lasers in space radiation environments, this paper establishes a simulation model that simultaneously considers the cumulative radiation damage and photobleaching effect of erbium ytterbium co doped fiber lasers. Based on the theoretical framework of steady-state fiber amplifiers, this model introduces additional radiation-induced losses into the power propagation equation and uses a time convolution based method to describe the bleaching behavior of defects generated at different times under the simultaneous action of irradiation and bleaching, thereby achieving simulation of the dynamic evolution process of fiber gain under irradiation bleaching coupling conditions. The model only requires a small amount of short-term irradiation and bleaching pre experiments to calibrate the key parameters in the model, which can be used to predict the performance evolution under higher doses and longer time conditions. The model was experimentally validated for simulation results in various situations where only irradiation effect, only bleaching effect, and both exist simultaneously. The results show that the simulation results are in good agreement with the experimentally measured gain variation trend, verifying the rationality and effectiveness of the model. This method only requires a small amount of short-term pre experiments to predict the performance evolution behavior of fiber lasers over a longer service period, providing an effective theoretical tool for evaluating the performance of radiation resistant fiber lasers in long-term irradiation environments.

Fields of Study & Subjects

Photonic Crystal and Fiber Optics Semiconductor Lasers and Optical Devices Advanced Fiber Optic Sensors

Publication details

Journal / source
ScienceDB
Publication date
6 March 2026
Language
ZH
Document type
Dataset