  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 novel features and
challenges, 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.
