Disorder information from conductance: a quantum inverse problem

TL;DR

This paper introduces an inversion method to deduce impurity types and concentrations in disordered quantum devices from conductance spectra, demonstrated on graphene nanoribbons, enabling structural insights from standard measurements.

Contribution

The paper presents a novel inversion technique to extract impurity information from conductance data in disordered quantum systems, applicable to various materials.

Findings

Successfully identified impurity types and concentrations in graphene nanoribbons

Demonstrated robustness of the inversion method across different simulation approaches

Showed the method's potential for structural analysis of disordered mesoscopic devices

Abstract

It is straightforward to calculate the conductance of a quantum device once all its scattering centers are fully specified. However, to do this in reverse, i.e., to find information about the composition of scatterers in a device from its conductance, is an elusive task. This is particularly more challenging in the presence of disorder. Here we propose a procedure in which valuable compositional information can be extracted from the seemingly noisy spectral conductance of a two-terminal disordered quantum device. In particular, we put forward an inversion methodology that can identify the nature and respective concentration of randomly-distributed impurities by analyzing energy-dependent conductance fingerprints. Results are shown for graphene nanoribbons as a case in point using both tight-binding and density functional theory simulations, indicating that this inversion technique is general, robust and can be employed to extract structural and compositional information of disordered mesoscopic devices from standard conductance measurements.