A model of interacting quantum neurons with a dynamic synapse

TL;DR

This paper models quantum neurons with dynamic, activity-dependent interactions inspired by biological synapses, revealing phenomena like excitation trapping and sustained entanglement, with potential experimental realization.

Contribution

It introduces a minimal quantum neuron model with dynamic synapses, demonstrating novel behaviors such as excitation trapping and long-term entanglement.

Findings

Synaptic depression decreases Rabi oscillation frequency.

Long-term entanglement naturally arises with synaptic depression.

The model's predictions are experimentally feasible.

Abstract

Motivated by recent advances in neuroscience, in this work, we explore the emergent behaviour of quantum systems with a dynamical biologically-inspired qubits interaction. We use a minimal model of two interacting qubits with an activity-dependent dynamic interplay as in classical dynamic synapses that induces the so-called synaptic depression, that is, synapses that present synaptic fatigue after heavy presynaptic stimulation. Our study shows that in absence of synaptic depression the 2-qubits quantum system shows typical Rabi oscillations whose frequency decreases when synaptic depression is introduced, so one can trap excitations for a large period of time. This creates a population imbalance between the qubits even though the Hamiltonian is Hermitian. This imbalance can be sustained in time by introducing a small energy shift between the qubits. In addition, we report that long-time entanglement between the two qubits raises naturally in the presence of synaptic depression. Moreover, we propose and analyse a plausible experimental setup of our 2-qubits system which demonstrates that these results are robust and can be experimentally obtained in a laboratory.