Full three-dimensonal reconstruction of the dyadic Green tensor from electron energy loss spectroscopy of plasmonic nanoparticles

TL;DR

This paper presents a novel method to fully reconstruct the three-dimensional dyadic Green tensor of plasmonic nanoparticles from electron energy loss spectroscopy data, enabling detailed optical analysis of arbitrarily shaped particles.

Contribution

It introduces an inverse problem formulation and a compressed sensing approach to reconstruct the Green tensor without restrictive assumptions on particle shape or plasmonic response.

Findings

Successfully reconstructs Green tensor for various nanoparticle geometries

Lifts previous restrictions like quasistatic approximation and single-mode response

Demonstrates applicability to nanorod, bowtie, and cube shapes

Abstract

Electron energy loss spectroscopy (EELS) has emerged as a powerful tool for the investigation of plasmonic nanoparticles, but the interpretation of EELS results in in terms of optical quantities, such as the photonic local density of states, remains challenging. Recent work has demonstrated that under restrictive assumptions, including the applicability of the quasistatic approximation and a plasmonic response governed by a single mode, one can rephrase EELS as a tomography scheme for the reconstruction of plasmonic eigenmodes. In this paper we lift these restrictions by formulating EELS as an inverse problem, and show that the complete dyadic Green tensor can be reconstructed for plasmonic particles of arbitrary shape. The key steps underlying our approach are a generic singular value decomposition of the dyadic Green tensor and a compressed sensing optimization for the determination of the expansion coefficients. We demonstrate the applicability of our scheme for prototypical nanorod, bowtie, and cube geometries.