A silicon nitride based synthetic metamaterial

Abstract

The recent transfer of topological states from the quantum realm to clas- sical physics has sparked ideas for new approaches in designer materials. These unusually robust configurations were no longer out of reach for classical material design. However, while it is relatively easy to identify a topological state when it appears, the inverse statement is not true. It is hard to find a material structure that will host a specific topological state, which complicates the development of novel materials. What is more, there are experimental challenges to current metama- terial development platforms. These implementations are typically un- tunable, and require a comlete redesign and remanufacturing for minor changes to be applied. While there exist implementations that are re- configurable to some extent, adjustments are typically cumbersome and require for the device to be taken offline for an extended period of time. These limitations lead to long iteration times and manufacturing overhead that keeps stacking up. The above problems are addressed in this thesis in a two pronged ap- proach from the theoretical and the experimental side. To overcome the experimental challenges, a synthetic metamaterial is devised. The goal is a material development platform that can host large hopping models, allows real-time control over all system parameters and is fully reprogrammable by the press of a button via software. This platform only becomes a ma- terial with specific functionality when it is powered up and programmed, hence the nomer “synthetic”. The system as a whole consists of a sample manufactured using standard microfabrication techniques, and custom de- signed surrounding infrastructure, with 11 FPGAs at its core, that provides the desired level of control. The theoretical design issues are approached via the development of a material design framework. The resulting software stack is able to auto- matically discover 2 dimensional structures that host topological states. It is also platform agnostic, and works whether the target system is governed by the Schrödinger (electrons, ultra-cold atoms), the Poisson (vibrations) or the Maxwell equations (photonic crystals). The theoretical platform works, and is successfully cranking out structures. The results found for the experimental platform are very promising. Although it has not quite arrived at the desired final state yet, there exists a clear and short path towards a fully functional system. Furthermore, being a fully parametric system, it is then also suited for the studies of other fields, such as physical neural networks, signal processing and nonlinear phenomena.