In spin Hall nano-oscillators (SHNOs), pure spin currents drive local regions of magnetic films and nanostructures into auto-oscillating precession. If such regions are placed in close proximity to each other they can interact and may mutually synchronize. Here, we demonstrate robust mutual synchronization of two-dimensional SHNO arrays ranging from 2 × 2 to 8 × 8 nano-constrictions, observed both electrically and using micro-Brillouin light scattering microscopy. On short time scales, where the auto-oscillation linewidth [Formula: see text] is governed by white noise, the signal quality factor, [Formula: see text], increases linearly with the number of mutually synchronized nano-constrictions (N), reaching 170,000 in the largest arrays. We also show that SHNO arrays exposed to two independently tuned microwave frequencies exhibit the same synchronization maps as can be used for neuromorphic vowel recognition. Our demonstrations may hence enable the use of SHNO arrays in two-dimensional oscillator networks for high-quality microwave signal generation and ultra-fast neuromorphic computing.

中文翻译：

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用于神经形态计算的二维相互同步自旋霍尔纳米振荡器阵列。

在自旋霍尔纳米振荡器 (SHNO) 中，纯自旋电流驱动磁性薄膜和纳米结构的局部区域进入自振荡进动。如果这些区域彼此靠近放置，则它们可以相互作用并且可以相互同步。在这里，我们展示了二维 SHNO 阵列的稳健相互同步，范围从 2 × 2 到 8 × 8 纳米收缩，通过电学和微布里渊光散射显微镜观察。在短时间尺度上，自振荡线宽 [公式：见正文] 受白噪声控制，信号质量因子 [公式：见正文] 随相互同步的纳米收缩 (N) 的数量线性增加，在最大的阵列中达到 170,000。我们还表明，暴露于两个独立调谐微波频率的 SHNO 阵列表现出与可用于神经形态元音识别相同的同步图。因此，我们的演示可以使 SHNO 阵列在二维振荡器网络中用于高质量微波信号生成和超快速神经形态计算。