Genetic optimization Invents non-Hermitian potentials for Asymmetric Reflectivity

We propose a general design strategy based on genetic optimization to realize asymmetric reflectivity in periodic and non-periodic planar structures containing dielectric and gain-loss layers. By means of an optimization algorithm, it is possible to design the imaginary (or real) part of the complex...

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Detalhes bibliográficos
Autores: Ahmed Waseem, Waqas Waseem, Herrero Simon, Ramon|||0000-0001-5572-1540, Botey Cumella, Muriel|||0000-0001-8984-4899, Wu, Ying, Staliunas, Kestutis|||0000-0002-0539-9538
Formato: informe técnico
Fecha de publicación:2020
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/345572
Acesso em linha:https://hdl.handle.net/2117/345572
Access Level:acceso abierto
Palavra-chave:Light--Transmission
Reflection (Optics)
Llum -- Transmissió
Reflexió (Òptica)
Àrees temàtiques de la UPC::Física
Descrição
Resumo:We propose a general design strategy based on genetic optimization to realize asymmetric reflectivity in periodic and non-periodic planar structures containing dielectric and gain-loss layers. By means of an optimization algorithm, it is possible to design the imaginary (or real) part of the complex permittivity distribution from any given and arbitrary real (or imaginary) permittivity distribution, i.e to create non-Hermitian potentials intended to achieve on-demand light transport for a selected spectral range. Indeed, the asymmetric response of the obtained complex permittivity distribution is directly related to its area in the complex permittivity plane. In particular, unidirectional light reflection can be designed in such a way that it switches from left to right (or vice versa) depending on the operating frequency. Moreover, such controllable unidirectional reflectivity can be realized using a stack of dielectric layers while keeping the refractive index and gain-loss within realistic values.