Scalable framework for quantum transport across large physical networks

TL;DR

This paper introduces a scalable variational framework for quantum transport modeling in large, complex networks, enabling analysis of systems with hundreds to thousands of sites.

Contribution

It presents a novel partitioning scheme that enhances the scalability of the variational polaron approach for large quantum energy transport systems.

Findings

Enables modeling of large energy transport networks with hundreds to thousands of sites.

Provides a physically motivated method for exploring complex quantum transport systems.

Addresses scalability issues in variational quantum transport frameworks.

Abstract

Accurately modelling many-body quantum transport systems poses a challenge both conceptually and computationally due to the growth of the Hilbert space and the multi-scale nature of the geometries and couplings present in most naturally occurring networks. A compounding complexity of such systems is that the environment typically plays a key role in the transport dynamics. Utilising variational unitary transformations that displace environmental degrees of freedom allows for the deployment of a second-order master equation capable of capturing the dynamics of intermediate and strongly coupled systems, which are ubiquitous in microscopic energy transport systems. However, direct implementations of this approach suffer from fundamental scalability issues due to the complexity of the self-consistent equations required to solve for the variational parameters. Here, we present an efficient partitioning scheme that leverages the inherent multi-scale nature of natural energy transport networks. This enables scaling of the variational polaron framework to quantum energy transport systems, constituting hundreds to thousands of sites. Our work unlocks the physically motivated exploration of large transport networks, for example, those present within light-harvesting complexes and exciton transport in disordered semiconductors.