论文标题

使用机器学习设计的自旋镜头的实验演示

Experimental Demonstration of a Spin-Wave Lens Designed with Machine Learning

论文作者

Kiechle, Martina, Maucha, Levente, Ahrens, Valentin, Dubs, Carsten, Porod, Wolfgang, Csaba, Gyorgy, Becherer, Markus, Papp, Adam

论文摘要

我们介绍了像自旋波形镜头一样起作用的设备的设计和实验实现,即它将自旋波聚焦到指定位置。镜头的结构不像任何常规镜头设计,它是由机器学习算法产生的非直觉模式。作为自旋波设计工具,我们使用了具有内置自动梯度计算的自定义微磁性求解器“ spintorch”,并且可以通过时间进行自旋传播的时间进行反向传播。训练本身是用YIG膜作为可变参数的饱和磁化来执行的,其目标是将旋转波引导到预定义的位置。我们通过实现广泛使用的MUMAX3微磁求解器验证了该设备的操作。对于实验实施,我们开发了一种技术,通过直接聚焦离子梁照射在YIG中创建有效的饱和度磁化景观。这使我们能够快速将纳米级设计模式转移到YIG培养基,而无需通过蚀刻来对材料进行图案。我们测量了与FIB剂量水平相对应的有效饱和磁化强度,并使用此映射将设计的散射器转换为所需的剂量水平。我们的演示是工作流程的概念证明,可用于实现具有复杂功能(例如自旋波信号处理器或神经形态设备)的更复杂的自旋波动设备。

We present the design and experimental realization of a device that acts like a spin-wave lens i.e., it focuses spin waves to a specified location. The structure of the lens does not resemble any conventional lens design, it is a nonintuitive pattern produced by a machine learning algorithm. As a spin-wave design tool, we used our custom micromagnetic solver "SpinTorch" that has built-in automatic gradient calculation and can perform backpropagation through time for spin-wave propagation. The training itself is performed with the saturation magnetization of a YIG film as a variable parameter, with the goal to guide spin waves to a predefined location. We verified the operation of the device in the widely used mumax3 micromagnetic solver, and by experimental realization. For the experimental implementation, we developed a technique to create effective saturation-magnetization landscapes in YIG by direct focused-ion-beam irradiation. This allows us to rapidly transfer the nanoscale design patterns to the YIG medium, without patterning the material by etching. We measured the effective saturation magnetization corresponding to the FIB dose levels in advance and used this mapping to translate the designed scatterer to the required dose levels. Our demonstration serves as a proof of concept for a workflow that can be used to realize more sophisticated spin-wave devices with complex functionality, e.g., spin-wave signal processors, or neuromorphic devices.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源