用于储备池计算的互同步无偏置场自旋霍尔纳米振荡器中的相位二值化
Phase Binarization in Mutually Synchronized Bias Field-free Spin Hall Nano-oscillators for Reservoir Computing
AI总结：
该研究通过微磁模拟证明两个非相同纳米收缩SHNO可在无偏置磁场和微波注入下由纯直流电流实现互同步与相位二值化，并用于储备池计算波形分类。
摘要：
相互耦合的自旋霍尔纳米振荡器（SHNO）可以呈现二值化的相位状态，为实现Ising机和高效神经形态硬件提供了途径。传统上，在存在偏置磁场的情况下，通过以振荡器频率两倍的频率注入外部微波，可在耦合SHNO中实现相位二值化。然而，该技术带来了更高能耗和复杂电路设计的潜在挑战。此外，制备引起的SHNO尺寸失配可能阻碍互同步。为应对这些挑战，我们展示了在没有偏置磁场和微波注入的情况下，两个非相同纳米收缩SHNO的纯直流电流驱动互同步和相位二值化。我们利用微磁模拟彻底研究了这些现象及其底层机制。我们进一步证明，无偏置场的同步SHNO对利用电流可调相位二值化，高效执行了储备池计算基准学习任务：正弦波和方波分类。我们的结果展示了耦合无偏置场SHNO在未来计算应用中具有前景的磁化动力学。
英文摘要：
Mutually coupled spin Hall nano-oscillators (SHNO) can exhibit binarized phase state, offering pathways to realize Ising machines and efficient neuromorphic hardware. Conventionally, phase binarization is achieved in coupled SHNOs via injecting an external microwave at twice of the oscillator frequency in presence of a biasing magnetic field. However, this technology poses potential challenges of higher energy consumption and complex circuit design. Moreover, fabrication-induced mismatch in SHNO dimensions may hinder mutual synchronization. Addressing these challenges, we demonstrate purely DC current-driven mutual synchronization and phase binarization of two non-identical nanoconstriction SHNOs without biasing magnetic field and microwave injection. We thoroughly investigate these phenomena and underlying mechanisms using micromagnetic simulation. We further demonstrate the bias field-free synchronized SHNO pair efficiently performing a reservoir computing benchmark learning task: sin and square wave classification, utilizing current tunable phase binarization. Our results showcase promising magnetization dynamics of coupled bias field-free SHNOs for future computing applications.
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