Posner computing: a quantum neural network model

Abstract

We present a construction, rendered in Quipper, of a quantum algorithm which probabilistically computes a classical function from n bits to n bits. The construction is intended to be of interest primarily for the features of Quipper it highlights. However, intrigued by the utility of quantum information processing in the context of neural networks, we present the algorithm as a simplest example of a particular quantum neural network which we first define. As the definition is inspired by recent work of Fisher concerning possible quantum substrates to cognition, we precede it with a short description of that work.