  Spiking artificial neurons emulate the voltage spikes of biological neurons,
and constitute the building blocks of a new class of energy efficient,
neuromorphic computing systems. Antiferromagnetic materials can, in theory, be
used to construct spiking artificial neurons. When configured as a neuron, the
magnetizations in antiferromagnetic materials have an effective inertia that
gives them intrinsic characteristics that closely resemble biological neurons,
in contrast with conventional artificial spiking neurons. It is shown here that
antiferromagnetic neurons have a spike duration on the order of a picosecond, a
power consumption of about 10^-3 pJ per synaptic operation, and built-in
features that directly resemble biological neurons, including response latency,
refraction, and inhibition. It is also demonstrated that antiferromagnetic
neurons interconnected into physical neural networks can perform unidirectional
data processing even for passive symmetrical interconnects. Flexibility of
antiferromagnetic neurons is illustrated by simulations of simple neuromorphic
circuits realizing Boolean logic gates and controllable memory loops.
