Abstract
We experimentally realize a series of incommensurable metasurface stacks that transition from near-field coupling to a far-field regime. Based on a comparison between a semi-analytic model and measurements, we, furthermore, present an experimental study on the validity of the fundamental mode approximation (FMA). As the FMA is a condition for the homogeneity of a metasurface, its validity allows for strong simplification in the design of stacked metasurfaces. Based on this, we demonstrate a method for the semi-analytic design of stacked periodic metasurfaces with arbitrary period ratios. In particular, incommensurable ratios require computational domains of impractically large sizes and are usually very challenging to fabricate. This results in a noticeable gap in parameter space when optimizing metasurface stacks for specific optical features. Here, we aim to close that gap by utilizing the principles of the FMA, allowing for additional parameter combinations in metasurface design.
Highlights
Design of applications in nano-photonics is a computationally demanding task that usually requires many degrees of freedom and, as a consequence, large parameter spaces.1–3 A large parameter space allows the search for optimal solutions for a given application
Using a semi-analytic framework based on the fundamental mode approximation (FMA), we demonstrate both the design and analysis of incommensurable metasurface stacks, applicable to arbitrary period ratios
From the results of the scanning electron microscopy (SEM) evaluation of the sample, we derived updated model parameters and performed Semi-Analytic Stacking Algorithm (SASA) simulations once more in order to compare them to the experimental findings
Summary
Design of applications in nano-photonics is a computationally demanding task that usually requires many degrees of freedom and, as a consequence, large parameter spaces. A large parameter space allows the search for optimal solutions for a given application. Design of applications in nano-photonics is a computationally demanding task that usually requires many degrees of freedom and, as a consequence, large parameter spaces.. A large parameter space allows the search for optimal solutions for a given application. One straight-forward example of this is nano-photonic color filters that can be designed, for instance, by finding suitable size ratios of periodic nano-cylinders.. A variety of polarization sensitive nano-structures can be designed by adapting the size and symmetry class of nano-structures for almost arbitrary polarization.. One has to strike a balance between the size of the parameter space, computational resources, and a physical understanding of the model or approach.. Having a large parameter space with many degrees of freedom can lead to arbitrary non-intuitive solutions.. One has to strike a balance between the size of the parameter space, computational resources, and a physical understanding of the model or approach. For example, having a large parameter space with many degrees of freedom can lead to arbitrary non-intuitive solutions. On the other hand, a very precise analytic model could be limited in its range of applications, while it might be challenging to derive necessary fabrication parameters from it. Depending on the goal of the design, each approach has its own merits
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