  To improve artificial intelligence/autonomous systems and help with treating
neurological conditions, there's a requirement for artificial neuron hardware
that mimics biological. We examine experimental artificial neurons with quantum
tunneling memory using 4.2 nm of ionic Hafnium oxide and Niobium metal inserted
in the positive and negative feedback of an oscillator. These neurons have
adaptive spiking behavior and hybrid non-chaotic/chaotic modes. When networked,
they output with strong itinerancy. The superconducting state at 8.1 Kelvin
results in Josephson tunneling with signs that the ionic states are influenced
by quantum coherent control in accordance with quantum master equation
calculations of the expectation values and correlation functions with a
calibrated time dependent Hamiltonian. We experimentally demonstrate a learning
network of 4 artificial neurons, and the modulation of signals.
