3+化酸纤维用于0.9微米单频激光器:基于机器学习的组合设计,用于抑制竞争性排放
Optics express
|April 12, 2025
概括
研究人员开发了一种机器学习模型,用于设计新型酸盐纤维,用于高效的0.9微米单频光纤激光器. 这种方法增强了蓝色激光的产生,用于水下通信和显示.
科学领域:
- 材料科学 材料科学 材料科学
- 激光物理 激光物理
- 计算科学 计算科学
背景情况:
- 0.9微米单频光纤激光器对于蓝色激光产生至关重要,对于水下通信,检测和激光显示器至关重要.
- 在0.9μm的4F3/2→4I9/2过渡面临来自4F3/2→4I11/2过渡的竞争,阻碍了性能.
- 设计光纤矩阵是减轻这种竞争的关键,而不会影响设备集成.
研究的目的:
- 应用机器学习方法来开发激光眼镜中的组合结构描述符分支比率模型.
- 引导新型纤维的组合设计,以提高0.9微米激光的性能.
- 通过优化纤维设计,实现高效的蓝色激光生成.
主要方法:
- 开发了一个机器学习模型,根据玻璃的组成和结构来预测分支率.
- 该模型展示了高精度和从三元玻璃系统到四元玻璃系统的推断能力.
- 使用该模型设计了酸盐纤维,具有0.9微米的增强分支率和高净增益系数.
主要成果:
- 在设计的酸盐纤维中,在0.9微米时实现了0.40的增强分支比.
- 在915nm获得4.21dB/cm的高净增益系数.
- 一个紧的单频激光在915nm成功地证明了低门 (11.5mW) 和抑制竞争性发射 (>65dB SNR).
结论:
- 开发的机器学习方法准确地预测了分支比率,并指导光纤设计以实现特定的激光性能.
- 这种方法可以创建高效的0.9微米单频光纤激光器,并抑制不必要的过渡.
- 该方法在设计用于各种激光应用的新型纤维方面具有重大潜力.
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