Design of plasmonic directional antennas via evolutionary optimization

Nano antenna-assisted quantum dots emission into high-index planar waveguide

Integrated quantum photonic circuits require the efficient coupling of photon sources to photonic waveguides. Hybrid plasmonic/photonic platforms are a promising approach, taking advantage of both plasmon modal confinement for efficient coupling to a nearby emitter and photonic circuitry for optical data transfer and processing. In this work, we established directional quantum dot (QD) emission coupling to a planar TiO2waveguide assisted by a Yagi-Uda antenna. Antenna on waveguide is first designed by scaling radio frequency dimensions to nano-optics, taking into account the hybrid plasmonic/photonic platform. Design is then optimized by full numerical simulations. We fabricate the antenna on a TiO2planar waveguide and deposit a few QDs close to the Yagi-Uda antenna. The optical characterization shows clear directional coupling originating from antenna effect. We estimate the coupling efficiency and directivity of the light emitted into the waveguide.

A newcomer's guide to deep learning for inverse design in nano-photonics

Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as light concentration, routing, and filtering. Designing these devices to achieve precise light-matter interactions using structural parameters and materials is a challenging task. Traditionally, solving this problem has relied on computationally expensive, iterative methods. In recent years, deep learning techniques have emerged as promising tools for tackling the inverse design of nanophotonic devices. While several review articles have provided an overview of the progress in this rapidly evolving field, there is a need for a comprehensive tutorial that specifically targets newcomers without prior experience in deep learning. Our goal is to address this gap and provide practical guidance for applying deep learning to individual scientific problems. We introduce the fundamental concepts of deep learning and critically discuss the potential benefits it offers for various inverse design problems in nanophotonics. We present a suggested workflow and detailed, practical design guidelines to help newcomers navigate the challenges they may encounter. By following our guide, newcomers can avoid frustrating roadblocks commonly experienced when venturing into deep learning for the first time. In a second part, we explore different iterative and direct deep learning-based techniques for inverse design, and evaluate their respective advantages and limitations. To enhance understanding and facilitate implementation, we supplement the manuscript with detailed Python notebook examples, illustrating each step of the discussed processes. While our tutorial primarily focuses on researchers in (nano-)photonics, it is also relevant for those working with deep learning in other research domains. We aim at providing a solid starting point to empower researchers to leverage the potential of deep learning in their scientific pursuits.

Control of light emission of quantum emitters coupled to silicon nanoantenna using cylindrical vector beams

Light emission of europium (Eu3+) ions placed in the vicinity of optically resonant nanoantennas is usually controlled by tailoring the local density of photon states (LDOS). We show that the polarization and shape of the excitation beam can also be used to manipulate light emission, as azimuthally or radially polarized cylindrical vector beam offers to spatially shape the electric and magnetic fields, in addition to the effect of silicon nanorings (Si-NRs) used as nanoantennas. The photoluminescence (PL) mappings of the Eu3+ transitions and the Si phonon mappings are strongly dependent of both the excitation beam and the Si-NR dimensions. The experimental results of Raman scattering and photoluminescence are confirmed by numerical simulations of the near-field intensity in the Si nanoantenna and in the Eu3+-doped film, respectively. The branching ratios obtained from the experimental PL maps also reveal a redistribution of the electric and magnetic emission channels. Our results show that it could be possible to spatially control both electric and magnetic dipolar emission of Eu3+ ions by switching the laser beam polarization, hence the near field at the excitation wavelength, and the electric and magnetic LDOS at the emission wavelength. This paves the way for optimized geometries taking advantage of both excitation and emission processes.

A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics

The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area.

Large-scale controlled coupling of single-photon emitters to high-index dielectric nanoantennas by AFM nanoxerography

Improving the brightness of single-photon sources by means of optically resonant nanoantennas is a major stake for the development of efficient nanodevices for quantum communications. We demonstrate that nanoxerography by atomic force microscopy makes possible the fast, robust and repeatable positioning of model quantum nanoemitters (nitrogen-vacancy NV centers in nanodiamonds) on a large-scale in the gap of silicon nanoantennas with a dimer geometry. By tuning the parameters of the nanoxerography process, we can statistically control the number of deposited nanodiamonds, yielding configurations down to a unique single photon emitter coupled to these high index dielectric nanoantennas, with high selectivity and enhanced brightness induced by a near-field Purcell effect. Numerical simulations are in very good quantitative agreement with time-resolved photoluminescence experiments. A multipolar analysis reveals in particular all the aspects of the coupling between the dipolar single emitter and the Mie resonances hosted by these simple nanoantennas. This proof of principle opens a path to a genuine and large-scale spatial control of the coupling of punctual quantum nanoemitters to arrays of optimized optically resonant nanoantennas. It paves the way for future fundamental studies in quantum nano-optics and toward integrated photonics applications for quantum technologies.

Magnetic and electric Purcell factor control through geometry optimization of high index dielectric nanostructures

We design planar silicon antennas for controlling the emission rate of magnetic or electric dipolar emitters. Evolutionary algorithms coupled to the Green Dyadic Method lead to different optimized geometries which depend on the nature and orientation of the dipoles. We discuss the physical origin of the obtained configurations thanks to modal analysis but also emphasize the role of nanoscale design of the LDOS. We complete our study using finite element method and demonstrate an enhancement up to 2 × 10³ of the magnetic Purcell factor in europium ions. Our work brings together random optimizations to explore geometric parameters without constraint, a first order deterministic approach to understand the optimized designs and a modal analysis which clarifies the physical origin of the exaltation of the magnetic Purcell effect.

Advancing statistical learning and artificial intelligence in nanophotonics inverse design

Nanophotonics inverse design is a rapidly expanding research field whose goal is to focus users on defining complex, high-level optical functionalities while leveraging machines to search for the required material and geometry configurations in sub-wavelength structures. The journey of inverse design begins with traditional optimization tools such as topology optimization and heuristics methods, including simulated annealing, swarm optimization, and genetic algorithms. Recently, the blossoming of deep learning in various areas of data-driven science and engineering has begun to permeate nanophotonics inverse design intensely. This review discusses state-of-the-art optimizations methods, deep learning, and more recent hybrid techniques, analyzing the advantages, challenges, and perspectives of inverse design both as a science and an engineering.

Broadband optical Ta2O5 antennas for directional emission of light

Highly directive antennas with the ability of shaping radiation patterns in desired directions are essential for efficient on-chip optical communication with reduced cross talk. In this paper, we design and optimize three distinct broadband traveling-wave tantalum pentoxide antennas exhibiting highly directional characteristics. Our antennas contain a director and reflector deposited on a glass substrate, which are excited by a dipole emitter placed in the feed gap between the two elements. Full-wave simulations in conjunction with global optimization provide structures with an enhanced linear directivity as high as 119 radiating in the substrate. The high directivity is a result of the interplay between two dominant TE modes and the leaky modes present in the antenna director. Furthermore, these low-loss dielectric antennas exhibit a near-unity radiation efficiency at the operational wavelength of 780 nm and maintain a broad bandwidth. Our numerical results are in good agreement with experimental measurements from the optimized antennas fabricated using a two-step electron-beam lithography, revealing the highly directive nature of our structures. We envision that our antenna designs can be conveniently adapted to other dielectric materials and prove instrumental for inter-chip optical communications and other on-chip applications.

Single plasmon spatial and spectral sorting on a crystalline two-dimensional plasmonic platform

In the context of the emerging field of quantum plasmonics, we demonstrate in this manuscript the wavelength-dependent propagation and sorting of single plasmons launched in a two-dimensional crystalline gold flake by a broadband quantum nanoemitter. The stream of single plasmons in the visible is produced by a nanodiamond hosting a single nitrogen-vacancy color center positioned in the near field of the mesoscopic metallic microplatelet. Spatially and spectrally resolved images of the single plasmon propagation in the pristine hexagonal flake, and then in the same structure after insertion of a Bragg mirror, are obtained by filtered image-plane acquisitions on a leakage-radiation microscope. Our work on two-dimensional crystalline structures paves the way to future fundamental studies and applications in quantum plasmonics.

Resonant broadband unidirectional light scattering based on genetic algorithm

The spectrum overlapping of the radiative power between magnetic and electric dipole moments in nanoparticles can be used to realize unidirectional light scattering, which is promising for various kinds of applications. Nevertheless, it is still challenging to achieve such overlapping in a broadband manner. Herein, we propose that the combination of a genetic algorithm, Maxwell's equations, and electromagnetic multipole expansion can be used to design a nanoparticle that supports resonant broadband forward light scattering. Microwave experiments are performed to demonstrate our numerical results. The proposed method is quite general, and it can be straightforwardly generalized to design functional unidirectional scatters.