The statistics of scattering of waves inside single ray-chaotic enclosures have been successfully described by the Random Coupling Model (RCM). We expand the RCM to systems consisting of multiple complex ray-chaotic enclosures with variable coupling scenarios. The statistical properties of the model-generated quantities are tested against measured data of electrically large multi-cavity systems of various designs. The statistics of model-generated trans-impedance and induced voltages on a load impedance agree well with the experimental results. The RCM coupled chaotic enclosure model is general and can be applied to other physical systems including coupled quantum dots, disordered nanowires, and short-wavelength electromagnetic propagation through rooms in buildings, aircraft and ships. arXiv:1909.03827v1 [physics.class-ph]

This Perspective examines the emerging applications of photonic topological insulators (PTIs) in the microwave domain. The introduction of topological protection of light has revolutionized the traditional perspective of wave propagation through the demonstration of backscatter-free waveguides in the presence of sharp bending and strong structural defects. The pseudospin degree of freedom of light enables the invention of unprecedented topological photonic devices with useful functionalities. Our aim is to present a brief introduction of recent developments in microwave PTI demonstrations. We give a clear comparison of different PTI realizations, summarize the key features giving rise to topological protection, and present a discussion of the advantages and disadvantages of PTI technology compared to existing microwave device technology. We conclude with forward-looking perspectives of how the advantages of this technology can best be exploited.

Photonic topological systems, the electromagnetic analog of the topological materials in condensed matter physics, create many opportunities to design optical devices with novel properties. We present an experimental realization of the bi-anisotropic meta waveguide photonic system replicating both quantum Hall (QH) and quantum spin-Hall (QSH) topological insulating phases. With careful design, a composite QH-QSH photonic topological material is created and experimentally shown to support reflection-free edgemodes, a heterogeneous topological structure that is unprecedented in condensed matter physics. The effective spin degree of freedom of such topologically protected modes determines their unique pathways through these systems, free from backscattering and able to travel around sharp corners. As an example of their novel properties, we experimentally demonstrate reflection-less photonic devices including a 2-port isolator, a unique 3-port topological device, and a full 4-port circulator based on composite QH and QSH structures.

The Random Coupling Model (RCM) has been successfully applied to predicting the statistics of currents and voltages at ports in complex electromagnetic (EM) enclosures operating in the short wavelength limit [1-4]. Recent studies have extended the RCM to systems of multi-mode aperturecoupled enclosures. However, as the size (as measured in wavelengths) of a coupling aperture grows, the coupling matrix used in the RCM increases as well, and the computation becomes more complex and time consuming. A simple Power Balance Model (PWB) can provide fast predictions for the averaged power density of waves inside electrically-large systems for a wide range of cavity and coupling scenarios. However, the important interference induced fluctuations of the wave field retained in the RCM are absent in PWB. Here we aim to combine the best aspects of each model to create a hybrid treatment and study the EM fields in coupled enclosure systems. The proposed hybrid approach provides both mean and fluctuation information of the EM fields without the full computational complexity of coupled-cavity RCM. We compare the hybrid model predictions with experiments on linear cascades of over-moded cavities. We find good agreement over a set of different loss parameters and for different coupling strengths between cavities. The range of validity and applicability of the hybrid method are tested and discussed.

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The wave properties of complex scattering systems that are large compared to the wavelength, and show chaos in the classical limit, are extremely sensitive to system details. A solution to the wave equation for a specific configuration can change substantially under small perturbations. Due to this extreme sensitivity, it is difficult to discern basic information about a complex system simply from scattering data as a function of energy or frequency, at least by eye. In this work, we employ supervised machine learning algorithms to reveal and classify hidden information about the complex scattering system presented in the data. As an example we are able to distinguish the total number of connected cavities in a linear chain of weakly coupled lossy enclosures from measured reflection data. A predictive machine learning algorithm for the future states of a perturbed complex scattering system is also trained with a recurrent neural network. Given a finite training data series, the reflection/transmission properties can be forecast by the proposed algorithm. arXiv:1908.04716v1 [cond-mat.dis-nn]

Machine learning (ML) has found widespread application over a broad range of important tasks. To enhance ML performance, researchers have investigated computational architectures whose physical implementations promise compactness, high-speed execution, physical robustness, and low energy cost. Here, we experimentally demonstrate an approach that uses the high sensitivity of reverberant short wavelength waves for physical realization and enhancement of computational power of a type of ML known as reservoir computing (RC). The potential computation power of RC systems increases with their effective size. We here exploit the intrinsic property of short wavelength reverberant wave sensitivity to perturbations to expand the effective size of the RC system by means of spatial and spectral perturbations. Working in the microwave regime, this scheme is tested on different ML tasks. Our results indicate the general applicability of reverberant wave-based implementations of RC and of our effective reservoir size expansion techniques.