  Neuro-inspired computing architectures are one of the leading candidates to
solve complex, large-scale associative learning problems. The two key building
blocks for neuromorphic computing are the synapse and the neuron, which form
the distributed computing and memory units. Solid state implementations of
these units remain an active area of research. Specifically, voltage or current
controlled oscillators are considered a minimal representation of neurons for
hardware implementations. Such oscillators should demonstrate synchronization
and coupling dynamics for demonstrating collective learning behavior, besides
the desirable individual characteristics such as scaling, power, and
performance. To this end, we propose the use of nanoscale, epitaxial
heterostructures of phase change oxides and oxides with metallic conductivity
as a fundamental unit of an ultralow power, tunable electrical oscillator
capable of operating in the microwave regime. Our simulations show that
optimized heterostructure design with low thermal boundary resistance can
result in operation frequency of up to 3 GHz and power consumption as low as 15
fJ/cycle with rich coupling dynamics between the oscillators.
