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2020-04-01 - Article/Dans un journal avec peer-review - Anglais - page(s)

Rosolen Gilles , Chen Parry Yu, Maes Bjorn , Sivan Yonatan, "Overcoming the bottleneck for quantum computations of complex nanophotonic structures: Purcell and Förster resonant energy transfer calculations using a rigorous mode-hybridization method" in Physical Review. B, Condensed Matter and Materials Physics, 101, 15, 155401

  • Edition : American Physical Society (MD)
  • Codes CREF : Matériaux optiques (DI1256)
  • Unités de recherche UMONS : Matériaux Micro et Nanophotoniques (S803)
  • Instituts UMONS : Institut de Recherche en Science et Ingénierie des Matériaux (Matériaux)
  • Centres UMONS : Physique des matériaux (CRPM)
Texte intégral :

Abstract(s) :

(Anglais) A calculation of the photonic Green's tensor of a structure is at the heart of many photonic problems, but for non-trivial nanostructures, it is typically a prohibitively time-consuming task. Recently, a general normal mode expansion (GENOME) was implemented to construct the Green's tensor from eigenpermittivity modes. Here, we employ GENOME to the study the response of a cluster of nanoparticles. To this end, we use the rigorous mode hybridization theory derived earlier by D. J. Bergman [Phys. Rev. B 19, 2359 (1979)], which constructs the Green's tensor of a cluster of nanoparticles from the sole knowledge of the modes of the isolated constituent. The method is applied, for the first time, to a scatterer with a non-trivial shape (namely, a pair of elliptical wires) within a fully electrodynamic setting, and for the computation of the Purcell enhancement and F\"{o}rster Resonant Energy Transfer (FRET) rate enhancement, showing a good agreement with direct simulations. The procedure is general, trivial to implement using standard electromagnetic software, and holds for arbitrary shapes and number of scatterers forming the cluster. Moreover, it is orders of magnitude faster than conventional direct simulations for applications requiring the spatial variation of the Green's tensor, promising a wide use in quantum technologies, free-electron light sources and heat transfer, among others.