There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Topological photonics is a rapidly emerging field of research in which geometrical and topological ideas are exploited to design and control the behavior of light. Drawing inspiration from the discovery of the quantum Hall effects and topological insulators in condensed matter, recent advances have shown how to engineer analogous effects also for photons, leading to remarkable phenomena such as the robust unidirectional propagation of light, which hold great promise for applications. Thanks to the flexibility and diversity of photonics systems, this field is also opening up new opportunities to realize exotic topological models and to probe and exploit topological effects in new ways. This article reviews experimental and theoretical developments in topological photonics across a wide range of experimental platforms, including photonic crystals, waveguides, metamaterials, cavities, optomechanics, silicon photonics, and circuit QED. A discussion of how changing the dimensionality and symmetries of photonics systems has allowed for the realization of different topological phases is offered, and progress in understanding the interplay of topology with non-Hermitian effects, such as dissipation, is reviewed. As an exciting perspective, topological photonics can be combined with optical nonlinearities, leading toward new collective phenomena and novel strongly correlated states of light, such as an analog of the fractional quantum Hall effect.

Topological Photonics

This article reviews recent theoretical and experimental advances in the fundamental understanding and active control of quantum fluids of light in nonlinear optical systems. In the presence of effective photon-photon interactions induced by the optical nonlinearity of the medium, a many-photon system can behave collectively as a quantum fluid with a number of novel features stemming from its intrinsically nonequilibrium nature. A rich variety of recently observed photon hydrodynamical effects is presented, from the superfluid flow around a defect at low speeds, to the appearance of a Mach-Cherenkov cone in a supersonic flow, to the hydrodynamic formation of topological excitations such as quantized vortices and dark solitons at the surface of large impenetrable obstacles. While the review is mostly focused on a specific class of semiconductor systems that have been extensively studied in recent years (planar semiconductor microcavities in the strong light-matter coupling regime having cavity polaritons as elementary excitations), the very concept of quantum fluids of light applies to a broad spectrum of systems, ranging from bulk nonlinear crystals, to atomic clouds embedded in optical fibers and cavities, to photonic crystal cavities, to superconducting quantum circuits based on Josephson junctions. The conclusive part of the article is devoted to a review of the future perspectives in the direction of strongly correlated photon gases and of artificial gauge fields for photons. In particular, several mechanisms to obtain efficient photon blockade are presented, together with their application to the generation of novel quantum phases.

Quantum fluids of light

One of the most exciting tools that have entered the material science toolbox in recent years is machine learning. This collection of statistical methods has already proved to be capable of considerably speeding up both fundamental and applied research. At present, we are witnessing an explosion of works that develop and apply machine learning to solid-state systems. We provide a comprehensive overview and analysis of the most recent research in this topic. As a starting point, we introduce machine learning principles, algorithms, descriptors, and databases in materials science. We continue with the description of different machine learning approaches for the discovery of stable materials and the prediction of their crystal structure. Then we discuss research in numerous quantitative structure–property relationships and various approaches for the replacement of first-principle methods by machine learning. We review how active learning and surrogate-based optimization can be applied to improve the rational design process and related examples of applications. Two major questions are always the interpretability of and the physical understanding gained from machine learning models. We consider therefore the different facets of interpretability and their importance in materials science. Finally, we propose solutions and future research paths for various challenges in computational materials science.

/pdf/recent-advances-and-applications-of-machine-learning-in-55gs85xsws.pdf

Recent advances and applications of machine learning in solid-state materials science

Optical Waveguide Theory

Topology opens many new horizons for photonics, from integrated optics to lasers. The complexity of large-scale devices asks for an effective solution of the inverse problem: how best to engineer the topology for a specific application? We introduce a machine-learning approach applicable in general to numerous topological problems. As a toy model, we train a neural network with the Aubry–Andre–Harper band structure model and then adopt the network for solving the inverse problem. Our application is able to identify the parameters of a complex topological insulator in order to obtain protected edge states at target frequencies. One challenging aspect is handling the multivalued branches of the direct problem and discarding unphysical solutions. We overcome this problem by adopting a self-consistent method to only select physically relevant solutions. We demonstrate our technique in a realistic design and by resorting to the widely available open-source TensorFlow library. Topological photonics is a growing field with applications spanning from integrated optics to lasers. This study presents a machine learning method to solve the inverse problem that may help finding optimized solutions to engineer the topology for each specific application

/pdf/machine-learning-inverse-problem-for-topological-photonics-3a4ns7xo9l.pdf

Machine learning inverse problem for topological photonics

We present a theory of topological edge states in one-dimensional resonant photonic crystals with a compound unit cell. Contrary to the conventional electronic topological states, the modes under consideration are radiative; i.e., they decay in time due to the light escape through the structure boundaries. We demonstrate that the edge states survive despite their radiative decay and can be detected both in time- and frequency-dependent light reflection.

Radiative topological states in resonant photonic crystals.

We exploit topological edge states in resonant photonic crystals to attain strongly localized resonances and demonstrate lasing in these modes upon optical excitation. The use of virtually lossless topologically isolated edge states may lead to a class of thresholdless lasers operating without inversion. One needs, however, to understand whether topological states may be coupled to external radiation and act as active cavities. We study a two-level topological insulator and show that self-induced transparency pulses can directly excite edge states. We simulate laser emission by a suitably designed topological cavity and show that it can emit tunable radiation. For a configuration of sites following the off-diagonal Aubry-Andr\'e-Harper model, we solve the Maxwell-Bloch equations in the time domain and provide a first-principles confirmation of topological lasers. Our results open the road to a class of light emitters with topological protection for applications ranging from low-cost energetically effective integrated laser sources, also including silicon photonics, to strong-coupling devices for studying ultrafast quantum processes with engineered vacuum.

Topological lasing in resonant photonic structures

We apply the fermion commutation technique for composite bosons to polariton-polariton scattering in semiconductor planar microcavities. Derivations are presented in a simple and physically transparent fashion. A procedure of orthogonolization of the initial and final two-exciton state wave functions is used to calculate the effective scattering-matrix elements and the scattering rates. We show how the bosonic stimulation of the scattering appears in this full fermionic approach whose equivalence to the bosonization method is thus demonstrated in the regime of low exciton density. We find an additional contribution to polariton-polariton scattering due to the exciton oscillator strength saturation, which we analyze as well. We present a theory of the polariton-polariton scattering with opposite spin orientations and show that this scattering process takes place mainly via dark excitonic states. Analytical estimations of the effective scattering amplitudes are given.

/pdf/polariton-polariton-scattering-in-microcavities-a-v8u1ngrfx6.pdf

Polariton-polariton scattering in microcavities: A microscopic theory

In the recent literature, aspects of exciton-radiation interaction in multilayers have been discussed from the viewpoint of microscopic nonlocal optical response. This renewed interest has also revived a long lasting debate about the problem of additional boundary conditions in dispersive samples. In the present paper, the semiclassical framework for studying self-consistently the radiation-matter interaction in a dispersive multilayer medium is briefly reviewed, and applied to the case of a one-dimensional (1D) cluster of quantum wells under Bragg conditions. The optical response is computed as a function of quantum well number $N$ from the super-radiant regime (for rather small $N$ values) to the 1D Bragg reflector limit $(\stackrel{\ensuremath{\rightarrow}}{N}\ensuremath{\infty}).$ The different contributions of the radiation-matter interaction to the optical response are discussed by Feenberg's decomposition of the polaritonic matrix. The polariton dispersion curves of a quantum well superlattice are computed and compared with the photonic dispersion curves due to the background dielectric function modulation. Finally, the modification of the photonic bands close to a resonance of the material system is discussed using selected numerical examples.

Laura Pilozzi

Papers

Machine learning inverse problem for topological photonics

Radiative topological states in resonant photonic crystals.

Topological lasing in resonant photonic structures

Polariton-polariton scattering in microcavities: A microscopic theory

Spatial dispersion effects on the optical properties of a resonant Bragg reflector