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Particle swarm optimization for the design and characterization of silica-based photonic crystal fiber amplifiers

机译:粒子群优化技术用于基于二氧化硅的光子晶体光纤放大器的设计和表征

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摘要

In recent years, the development of photonic crystal fibers has allowed novel opportunities for enhancing optical amplifier characteristics. In this field, accurate numerical modeling is a significant need to predict the device behavior. Conventional approaches perform this task by using methods which could yield solutions characterized by divergent or unstably convergent algorithms. Global optimization methods can be considered as efficient tools to face this problem. In this paper, the application of particle swarm optimization to perform the design and characterization of photonic crystal fiber amplifiers is proposed. The employment of this technique shows different attractive features. In particular, solutions are found quickly and the implementation of the algorithm does not require complicated evolutionary operators. Numerical results show the effectiveness of the approach for both the design and characterization of a fiber amplifier. In fact, if considered as a design tool, the obtained numerical results are in good accordance with respect to the ones yielded by a conventional approach. If considered as a characterization tool, the algorithm performs a forecasting, allowing to determine parameters, such as homogeneous upconversion coefficients, whose computation could present difficulties when it is obtained via direct or indirect measurements.
机译:近年来,光子晶体光纤的发展为增强光放大器的特性提供了新的机会。在该领域,准确的数字建模是预测设备行为的重要需求。常规方法通过使用可以产生以发散或不稳定收敛算法为特征的解的方法来执行该任务。全局优化方法可以视为解决此问题的有效工具。本文提出将粒子群算法应用于光子晶体光纤放大器的设计与表征。这项技术的使用显示出不同的吸引力。尤其是,可以快速找到解决方案,并且该算法的实现不需要复杂的进化算子。数值结果表明,该方法对于光纤放大器的设计和特性均有效。实际上,如果将其视为设计工具,则所得数值结果与常规方法得出的数值结果非常一致。如果被认为是表征工具,该算法将执行预测,从而确定参数,例如均质上转换系数,当通过直接或间接测量获得该参数时,其计算可能会遇到困难。

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