  We propose that neuromorphic computing can perform quantum operations.
Spiking neurons in the active or silent states are connected to the two states
of Ising spins. A quantum density matrix is constructed from the expectation
values and correlations of the Ising spins. As a step towards quantum
computation we show for a two qubit system that quantum gates can be learned as
a change of parameters for neural network dynamics. Our proposal for
probabilistic computing goes beyond Markov chains, which are based on
transition probabilities. Constraints on classical probability distributions
relate changes made in one part of the system to other parts, similar to
entangled quantum systems.
