Natural photonic structures exhibit remarkable color effects such as metallic appearance and iridescence. A rigorous study of the electromagnetic response of such complex structures requires to accurately determine some of their relevant optical parameters, e.g. the dielectric constants of the materials involved. In a recent work, we have shown that heuristic optimization strategies are suitable tools for the retrieval of the complex refractive index of the materials comprising natural multilayer systems such as the Coleoptera’s cuticle. Moreover, the numerical results obtained illustrate the great potential of this kind of algorithms not only for the study of natural photonic structures, but also for the design of biomimetic photonic devices for lightning, sensing or anti-counterfeiting applications. In a first stage, we assumed that the materials which comprise the layers are characterized by isotropic non-dispersive dielectric permittivities. However, it is well known that the cuticle of many Coleoptera exhibit anisotropy in their constituent materials, and also dispersion has been reported. In this contribution we improve our previous approach in order to have a more realistic and useful computational tool for the retrieval of the relevant parameters of biological structures. For this, we include, within the inversion algorithm, a dispersion model to describe the frequency-dependent dielectric permittivity of the layers’ materials. Also, in order to guarantee the uniqueness of the solution and the convergence to the global optimum, we simultaneously include in the fitness function the information of several angles of incidence, as well as that of the p- and s-polarization states.
In the present work we employ an heuristic method based on evolutionary algorithms for the solution of an inverse problem in near-field optics. The input for the inversion procedure are some of the experimental data that appear in reference 1. In addition, we make use of the direct model proposed in that reference for the iterative solution of the direct problem. This requirement is directly related to the nature of the evolutionary approach employed. We show the possibility to recover, with a high degree of confidence, some parameters of the sample that originated the experimental information. The usefulness of the inverse method is therefore obvious if the recorded data have to be used for metrologic purpose.