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arXiv 1902.03312cond-mat.mes-hall
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低势垒纳米磁体中的亚纳秒涨落

Subnanosecond Fluctuations in Low-Barrier Nanomagnets

Jan Kaiser, Avinash Rustagi, Kerem Y. Camsari, Jonathan Z. Sun, Supriyo Datta, Pramey Upadhyaya

摘要:

由于热转矩引起的快速磁波动具有从密码学到概率计算的有用的技术功能。到目前为止研究的典型单轴各向异性磁体中波动的特征时间由众所周知的能量弛豫机制从下面限定。该时间尺度为$α^{-1}$,其中$α$参数化耗散过程的强度。在这里,我们从理论上分析了易平面和反铁磁耦合纳米磁体的波动动力学。我们发现,在这样的磁铁,动态的强烈影响波动的内磁场,从而产生一个额外的去相位型机制冲洗相关性。特别是,我们建立了两个时间尺度来表征波动(i)纳米磁体反转的平均时间|其对于低阻尼的实验相关制度主要由移相控制并且变得独立于$α$,(ii)单个纳米磁体的记忆丧失的时间尺度|其缩放为$α^{-1/3}$,并由能量耗散和失相机制的组合控制。对于典型的实验可访问的值的固有字段,所得到的热波动率增加了多个数量级相比,仅由单轴磁铁的能量弛豫机制的约束集。这可能导致利用磁波动的新兴设备的更高操作速度。

英文摘要:

Fast magnetic fluctuations due to thermal torques have useful technological functionality ranging from cryptography to probabilistic computing. The characteristic time of fluctuations in typical uniaxial anisotropy magnets studied so far is bounded from below by the well-known energy relaxation mechanism. This time scales as $α^{-1}$, where $α$ parameterizes the strength of dissipative processes. Here, we theoretically analyze the fluctuating dynamics in easy-plane and antiferromagnetically coupled nanomagnets. We find in such magnets, the dynamics are strongly influenced by fluctuating intrinsic fields, which give rise to an additional dephasing-type mechanism for washing out correlations. In particular, we establish two time scales for characterizing fluctuations (i) the average time for a nanomagnet to reverse|which for the experimentally relevant regime of low damping is governed primarily by dephasing and becomes independent of $α$, (ii) the time scale for memory loss of a single nanomagnet|which scales as $α^{-1/3}$ and is governed by a combination of energy dissipation and dephasing mechanism. For typical experimentally accessible values of intrinsic fields, the resultant thermal-fluctuation rate is increased by multiple orders of magnitude when compared with the bound set solely by the energy relaxation mechanism in uniaxial magnets. This could lead to higher operating speeds of emerging devices exploiting magnetic fluctuations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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