Neural networks with quantum gated nodes

With a view to investigating similarities in aspects of biological neural networks with quantum ones, so that quantum machines can be developed in future with some of the advantages of biological systems of information processing where a certain amount of indeterminism and the multiple connectivities between nodes offer advantages not seemingly obtainable from usual electronic devices working with classical gates, we present here some results for a quantum neural network with quantum gates. After reviewing the general principles of a biological network and a quantum one, we study a specific model network with qubits, i.e. quantum bits, replacing classical neurons having deterministic states, and also with quantum operators in place of the classical action potentials observed in biological contexts. With our choice of gates interconnecting the neural lattice, the state of the system behaves in ways reflecting both the strength of coupling between neurons as well as the initial conditions, as in biological systems. We find that, depending on whether there is a threshold for emission from excited to ground state, the system shows either chaotic oscillations or coherent ones with periodicity that depends on the strength of coupling. The initial input also affects the subsequent dynamic behavior of the system, which indicates that it can serve as a dynamic memory system analogous to biological ones. Our results seem to suggest that such quantum networks may contain some advantageous features of biological systems more efficiently than classical electronic devices.