论文标题
磁性域壁跑道中强大的边缘状态
Robust edge states in magnetic domain-wall racetrack
论文作者
论文摘要
可控的人造固定是在许多域壁（DW）设备中必不可少的，例如内存，传感器，逻辑门和神经形态计算硬件。然而，固定电势的有效弹簧常数的高准确性确定仍然具有挑战性，因为外部固定通常与材料缺陷和随机性引起的固有固定固定混合在一起。在这里，我们研究了与固定距离的固定位点相互作用DWS的集体动力学。通过将DW运动的管理方程映射到Su-Schrieffer-Heeger模型并评估量化的Zak阶段，我们预测了赛马场中的两个拓扑不同阶段。强大的边缘状态在一个或两端出现，具体取决于DW数的奇偶校验和交替的间间长度的比率。我们表明，间隙DW振荡频率具有固定值，仅取决于固定缺口的几何形状，并且对设备缺陷和不均匀性不敏感。我们建议准确地量化等于稳健DW频率平方的弹簧系数乘以其恒定质量。我们的发现也表明，DW赛道是研究拓扑相变的理想平台。
Controllable artificial pinning is indispensable in numerous domain-wall (DW) devices, such as memory, sensor, logic gate, and neuromorphic computing hardware. The high-accuracy determination of the effective spring constant of the pinning potential, however, remains challenging, because the extrinsic pinning is often mixed up with intrinsic ones caused by materials defects and randomness. Here, we study the collective dynamics of interacting DWs in a racetrack with pinning sites of alternate distances. By mapping the governing equations of DW motion to the Su-Schrieffer-Heeger model and evaluating the quantized Zak phase, we predict two topologically distinct phases in the racetrack. Robust edge state emerges at either one or both ends depending on the parity of the DW number and the ratio of alternating intersite lengths. We show that the in-gap DW oscillation frequency has a fixed value which depends only on the geometrical shape of the pinning notch, and is insensitive to device imperfections and inhomogeneities. We propose to accurately quantify the spring coefficient that equals the square of the robust DW frequency multiplied by its constant mass. Our findings suggest as well that the DW racetrack is an ideal platform to study the topological phase transition.
