自旋波储备池计算装置中信号探测器布置的数值探讨
A numerical exploration of signal detector arrangement in a spin-wave reservoir computing device
摘要：
本文数值研究了信号检测器的安排如何影响储备池计算的性能，使用自旋波激发在亚铁磁石榴石膜。这一调查是非常重要的，因为输入信息不仅传达，但也转化为高维信息空间的自旋波传播时，在薄膜中的空间分布的方式。这种时空动力学实现了丰富的计算功能。首先，我们模拟自旋波在一个矩形石榴石薄膜与两个输入电极，以获得响应于输入信号，这是表示为自旋矢量和用于机器学习波形分类任务的水库状态的空间分布。通过读出连接权重组合检测到的储层状态以生成最终输出。我们在训练后可视化权重的空间分布，以讨论通过将它们布置在网格点、等角圆形点或随机地布置输出电极的数量和位置。我们通过改变输出电极的数量来评估分类精度，并且发现无论网格、圆形还是随机布置，仅用几十个输出电极就实现了高精度（$>$ 90\%）。这些结果表明，自旋波具有足够复杂和丰富的动力学这类任务。然后，我们调查在哪些区域中有用的信息分布更多的电极局部布置在芯片上。最后，我们证明了该装置在一定的频率范围内对输入波信号频率具有泛化能力。这些结果将导致在不久的将来的低功耗智能计算的自旋波水库设备的实际设计。
英文摘要：
This paper studies numerically how the signal detector arrangement influences the performance of reservoir computing using spin waves excited in a ferrimagnetic garnet film. This investigation is essentially important since the input information is not only conveyed but also transformed by the spin waves into high-dimensional information space when the waves propagate in the film in a spatially distributed manner. This spatiotemporal dynamics realizes a rich reservoir-computational functionality. First, we simulate spin waves in a rectangular garnet film with two input electrodes to obtain spatial distributions of the reservoir states in response to input signals, which are represented as spin vectors and used for a machine-learning waveform classification task. The detected reservoir states are combined through readout connection weights to generate a final output. We visualize the spatial distribution of the weights after training to discuss the number and positions of the output electrodes by arranging them at grid points, equiangularly circular points or at random. We evaluate the classification accuracy by changing the number of the output electrodes, and find that a high accuracy ($>$ 90\%) is achieved with only several tens of output electrodes regardless of grid, circular or random arrangement. These results suggest that the spin waves possess sufficiently complex and rich dynamics for this type of tasks. Then we investigate in which area useful information is distributed more by arranging the electrodes locally on the chip. Finally, we show that this device has generalization ability for input wave-signal frequency in a certain frequency range. These results will lead to practical design of spin-wave reservoir devices for low-power intelligent computing in the near future.
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