The quest for highly efficient cognitive computing has led to extensive research interest for the field of neuromorphic computing. Neuromorphic computing aims to mimic the behavior of biological neurons and synapses using solid-state devices and circuits. Among various approaches, emerging non-volatile memory technologies are of special interest for mimicking neuro-synaptic behavior. These devices allow the mapping of the rich dynamics of biological neurons and synapses onto their intrinsic device physics. In this letter, we focus on Spike Timing Dependent Plasticity (STDP) behavior of biological synapses and propose a method to implement the STDP behavior in Magnetic Tunnel Junction (MTJ) devices. Specifically, we exploit the time-dependent heat dynamics and the response of an MTJ to the instantaneous temperature to imitate the STDP behavior. Our simulations, based on a macro-spin model for magnetization dynamics, show that, STDP can be imitated in stochastic magnetic tunnel junctions by applying simple voltage waveforms as the spiking response of pre- and post-neurons across an MTJ device.

中文翻译：

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热力学介导的随机磁性隧道结中的固有尖峰时间依赖性可塑性

对高效认知计算的追求引起了对神经形态计算领域的广泛研究。神经形态计算旨在使用固态设备和电路来模拟生物神经元和突触的行为。在各种方法中，新兴的非易失性存储器技术对模仿神经突触行为特别感兴趣。这些设备允许将生物神经元和突触的丰富动态映射到它们内在的设备物理上。在这封信中，我们专注于生物突触的脉冲定时相关可塑性 (STDP) 行为，并提出了一种在磁隧道结 (MTJ) 设备中实现 STDP 行为的方法。具体来说，我们利用瞬态热动力学和 MTJ 对瞬时温度的响应来模拟 STDP 行为。