How to Suppress Dark States in Quantum Networks and Bio-Engineered Structures

TL;DR

This paper uses graph theory to identify and suppress dark states in quantum networks, improving energy and information transfer, with applications to bio-engineered structures like light-harvesting complexes.

Contribution

It introduces a graph-theoretical approach to identify dark subspaces and demonstrates how to suppress them in small networks through coupling perturbations, with implications for quantum technology.

Findings

Dark subspaces are absent in large networks asymptotically.

Proper perturbations can suppress dark states in small networks.

Application to a bio-engineered light-harvesting structure shows robust transport.

Abstract

Transport across quantum networks underlies many problems, from state transfer on a spin network to energy transport in photosynthetic complexes. However, networks can contain dark subspaces that block the transportation, and various methods used to enhance transfer on quantum networks can be viewed as equivalently avoiding, modifying, or destroying the dark subspace. Here, we exploit graph theoretical tools to identify the dark subspaces and show that asymptotically almost surely they do not exist for large networks, while for small ones they can be suppressed by properly perturbing the coupling rates between the network nodes. More specifically, we apply these results to describe the recently experimentally observed and robust transport behaviour of the electronic excitation travelling on a genetically-engineered light-harvesting cylinder (M13 virus) structure. We believe that these mainly topological tools may allow us to better infer which network structures and dynamics are more favourable to enhance transfer of energy and information towards novel quantum technologies.