Open quantum generalisation of Hopfield neural networks - Markus Muller (Journal of Physics A: Mathematical and Theoretical, 2018)
In this work, we propose a new framework to study how quantum effects may impact on the dynamics of neural networks. We consider neural network dynamics in terms of Markovian open quantum systems, which allows us to study both thermal and quantum coherent effects within the same framework. Specifically, we propose and study an open quantum generalisation of the paradigmatic Hopfield neural network model. We determine its phase diagram and encounter a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds, which can be understood as generalisations of storage patterns to the quantum domain.