标题： 兴奋性和记忆在时滞光电子神经元中 显示英文标题

标题： Excitability and memory in a time-delayed optoelectronic neuron

摘要： 我们研究由可激发的纳米尺度共振隧穿二极管（RTD）驱动并通过时滞反馈耦合的纳米激光二极管（LD）组成的光电电路的动力学特性。 通过数值路径延续方法和时间仿真相结合的方法，我们证明该RTD-LD系统可以作为人工神经元，生成以时间局部态（TLSs）形式存在的脉冲，这些脉冲可用于神经形态计算中的记忆。 特别是，我们的研究发现，之前用于模拟RTD-LD的典型时滞FitzHugh-Nagumo模型仅在RTD较慢的极限情况下与我们更现实的模型相似。 我们表明，RTD的时间尺度在记忆容量中起着关键作用，因为它决定了脉冲相互作用从排斥到吸引的转变，导致稳定到不稳定多脉冲TLSs的转变。 我们的理论分析揭示了RTD-LD系统之前未知的特征和挑战，包括TLSs的多稳定性以及吸引相互作用力，这些源于之前被忽视的激光器的内在动力学。 这些效应至关重要，因为它们定义了RTD-LD的记忆特性。 显示英文摘要

摘要： We study the dynamics of an optoelectronic circuit composed of an excitable nanoscale resonant-tunneling diode (RTD) driving a nanolaser diode (LD) coupled via time-delayed feedback. Using a combination of numerical path-continuation methods and time simulations, we demonstrate that this RTD-LD system can serve as an artificial neuron, generating pulses in the form of temporal localized states (TLSs) that can be employed as memory for neuromorphic computing. In particular, our findings reveal that the prototypical delayed FitzHugh-Nagumo model previously employed to model the RTD-LD resembles our more realistic model only in the limit of a slow RTD. We show that the RTD time scale plays a critical role in memory capacity as it governs a shift in pulse interaction from repulsive to attractive, leading to a transition from stable to unstable multi-pulse TLSs. Our theoretical analysis uncovers features and challenges previously unknown for the RTD-LD system, including the multistability of TLSs and attractive interaction forces, stemming from the previously neglected intrinsic dynamics of the laser. These effects are crucial to consider since they define the memory properties of the RTD-LD.