动态分析和储计算 非线性微环共振器的应用
Stefano Gretter1, Mattia Mancinelli1, Lorenzo Pavesi1
1Nanoscience Laboratory, Department of Physics, University of Trento, Via Sommarive, 14, 38123 Povo, Trento, Italy.
概括
这项研究简化了用于神经形态计算的分析非线性微光振器. 一种新的线性化方法有效地预测了共振器的性能,避免了用于水库计算应用的复杂模拟.
科学领域:
- 光子学和光学工程的工程.
- 非线性光学是非线性光学.
- 计算神经科学是一种神经科学.
背景情况:
- 非线性微波共振器表现出自我脉冲和记忆效应,这对神经形态计算至关重要.
- 这些共振器在储计算 (RC) 架构中被用作非线性节点.
- 分析振荡器动态和优化控制参数的先前方法是计算密集的.
研究的目的:
- 开发一种计算效率高的方法来分析非线性微波振器的动态行为.
- 为了确定RC系统中高效光学计算的最佳控制参数.
- 在没有广泛的模拟的情况下,在RC应用中预测微环共振器的性能.
主要方法:
- 分析了光学场,温度和自由载体度的支配微分方程.
- 进行了系统的线性化和稳定性分析.
- 用空腔场的adiabatic近似来计算雅可比特固有值.
主要成果:
- 线性化和稳定性分析成功地确定了控制参数空间中的区域,对应于不同的动态行为.
- 雅可比式固有值被计算为可靠的RC性能指标.
- 与传统模拟相比,拟议的方法可显著降低计算成本.
结论:
- 线性化和稳定性分析为微环共振器的计算密集型模拟提供了有效的替代方案.
- 这种方法可以更快地识别神经形态应用程序的最佳操作模式.
- 这些发现有助于设计和实施高性能光学计算系统.
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