Neuromorphic method to solve quadratic unconstrained binary optimization (QUBO) problems

Abstract

A method is performed by an electronic device for solving a quadratic unconstrained binary optimization (QUBO) problem. The method comprises implementing a plurality of neurons, each neuron representing a respective binary decision variable of the QUBO problem, each neuron connected to one or both of a respective excitatory noise source and a respective inhibitory noise source. The method further comprises implementing a first plurality of synapses as a plurality of recurrent synapses, each recurrent synapse connected to a respective neuron of the plurality of neurons, each recurrent synapse having a respective weight corresponding to a diagonal coefficient of a QUBO matrix. The method further comprises implementing a second plurality of synapses as a plurality of lateral synapses extending between pairs of neurons of the plurality of neurons, each lateral synapse having a respective weight corresponding to an off-diagonal coefficient of the QUBO matrix.

Images