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Nonlinear optical phenomena are at the heart of various technological domains such as high-speed data transfer, optical logic applications, and emerging fields such as non-reciprocal optics and photonic time crystal design. However, conventional nonlinear materials exhibit inherent limitations in the post-fabrication tailoring of their nonlinear optical properties. Achieving real-time control over optical nonlinearities remains a challenge. In this work, we demonstrate a method to switch third harmonic generation (THG), a commonly occurring nonlinear optical response. Third harmonic generation enhancements up to 50 times are demonstrated in zinc oxide films via the photoexcited state generation and tunable electric field enhancement. More interestingly, the enhanced third harmonic generation follows a quadratic scaling with incident power, as opposed to the conventional cubic scaling, which demonstrates a previously unreported mechanism of third harmonic generation. The THG can also be suppressed by modulating the optical losses in the film. This work shows that the photoexcitation of states can not only enhance nonlinearities, but can create new processes for third harmonic generation. Importantly, the proposed method enables real-time manipulation of the nonlinear response of a medium. The process is switchable and reversible, with the modulations occurring at picosecond timescale. Our study paves the way to boost or suppress the nonlinearities of solid-state media, enabling robust, switchable sources for nonlinear optical applications.

The distinctive characteristics of light such as high-speed propagation, low-loss, low cross-talk and power consumption as well as quantum properties, make it uniquely suitable for various critical applications in communication, high-resolution imaging, optical computing, and emerging quantum information technologies. One limiting factor though is the weak optical nonlinearity of conventional media that poses challenges for the control and manipulation of light, especially with ultra-low, few-photon-level intensities. Notably, creating a photonic transistor working at single-photon intensities remains an outstanding challenge. In this work, we demonstrate all-optical modulation using a beam with single-photon intensity. Such low-energy control is enabled by the electron avalanche process in a semiconductor triggered by the impact ionization of charge carriers. This corresponds to achieving a nonlinear refractive index of n2~7*10^-3m^2/W, which is two orders of magnitude higher than in the best nonlinear optical media (Table S1). Our approach opens up the possibility of terahertz-speed optical switching at the single-photon level, which could enable novel photonic devices and future quantum photonic information processing and computing, fast logic gates, and beyond. Importantly, this approach could lead to industry-ready CMOS-compatible and chip-integrated optical modulation platforms operating with single photons.

When an electromagnetic (EM) wave is propagating in a medium whose properties are varied abruptly in time, the wave experiences refractions and reflections known as "time-refractions" and "time-reflections", both manifesting spectral translation as a consequence of the abrupt change of the medium and the conservation of momentum. However, while the time-refracted wave continues to propagate with the same wave-vector, the time-reflected wave is propagating backward with a conjugate phase, despite the lack of any spatial interface. Importantly, while time-refraction is always significant, observing time-reflection poses a major challenge - because it requires a large change in the medium occurring within a single cycle. For that reason, time-reflection of EM waves was observed only recently. Here, we present the observation of microwave pulses at the highest frequency ever observed (0.59 GHz), and the experimental evidence of the phase-conjugation nature of time-reflected waves. Our experiments are carried out in a periodically-loaded microstrip line with optically-controlled picosecond-switchable photodiodes. Our system paves the way to the experimental realization of Photonic Time-Crystals at GHz frequencies.

The efficient use of a multipole expansion of the far field for rapid numerical modeling and optimization of the optical response from ordered and disordered arrays of various structural elements is complicated by the ambiguity in choosing the ultimate expansion centers for individual scatterers. Since the multipolar decomposition depends on the position of the expansion center, the sets of multipoles are not unique. They may require constrained optimization to get the compact and most efficient spatial spectrum for each scatterer. We address this problem by finding {\em the optimal scattering centers} for which the spatial multipolar spectra become unique. We separately derive these optimal positions for the electric and magnetic parts by minimizing the norm of the poloidal electric and magnetic quadrupoles. Employing the long-wave approximation (LWA) ansatz, we verify the approach with the theoretical discrete models and realistic scatterers. We show that the optimal electric and magnetic scattering centers, in all cases, are not co-local with the centers of mass. The optimal multipoles, including the toroidal terms, are calculated for several structurally distinct scattering cases, and their utility for low-cost numerical schemes, including the generalized T-matrix approach, is discussed. Expansion of the work beyond the LWA is possible, with a promise for faster and universal numerical schemes.

We demonstrate a sustainable, lithography-free process for generating non fading plasmonic colors with a prototype device that produces a wide range of vivid colors in red, green, and blue (RGB) ([0-1], [0-1], [0-1]) color space from violet (0.7, 0.72, 1) to blue (0.31, 0.80, 1) and from green (0.84, 1, 0.58) to orange (1, 0.58, 0.46). The proposed color-printing device architecture integrates a semi-transparent random metal film (RMF) with a metal back mirror to create a lossy asymmetric Fabry-P\'erot resonator. This device geometry allows for advanced control of the observed color through the five-degree multiplexing (RGB color space, angle, and polarization sensitivity). An extended color palette is then obtained through photomodification process and localized heating of the RMF layer under various femtosecond laser illumination conditions at the wavelengths of 400 nm and 800 nm. Colorful design samples with total areas up to 10 mm2 and 100 {\mu}m resolution are printed on 300-nm-thick films to demonstrate macroscopic high-resolution color generation. The proposed printing approach can be extended to other applications including laser marking, anti-counterfeiting and chromo-encryption.

Topological photonic crystals, which offer topologically protected and back-scattering-immune transport channels, have recently gained significant attention for both scientific and practical reasons. Although most current studies focus on dielectric materials with weak dispersions, this study focuses on topological phases in dispersive materials and presents a numerical study of Chern insulators in gaseous-phase plasma cylinder cells. We develop a numerical framework to address the complex material dispersion arising from the plasma medium and external magnetic fields and identify Chern insulator phases that are experimentally achievable. Using this numerical tool, we also explain the flat bands commonly observed in periodic plasmonic structures, via local resonances, and how edge states change as the edge termination is periodically modified. This work opens up opportunities for exploring band topology in new materials with non-trivial dispersions and has potential RF applications, ranging from plasma-based lighting to plasma propulsion engines., Comment: 10 pages, 4 figures

All optical switches offer advanced control over the properties of light at ultrafast timescales using optical pulses as both the signal and the control. Limited only by material response times, these switches can operate at terahertz speeds, essential for technology-driven applications such as all-optical signal processing and ultrafast imaging, as well as for fundamental studies such as frequency translation and novel optical media concepts such as photonic time crystals. In conventional systems, the switching time is determined by the relaxation response of a single active material, which is challenging to adjust dynamically. This work demonstrates that the zero-to-zero response time of an all-optical switch can instead be varied through the combination of so-called fast and slow materials in a single device. When probed in the epsilon-near-zero operational regime of a material with a slow response time, namely, plasmonic titanium nitride, the switch exhibits a relatively slow, nanosecond response time. The response time then decreases reaching the picosecond time scale in the ENZ regime of the faster material, namely, aluminum-doped zinc oxide. Overall, the response time of the switch is shown to vary by two orders of magnitude in a single device and can be selectively controlled through the interaction of the probe signal with the constituent materials. The ability to adjust the switching speed by controlling the light-matter interaction in a multi-material structure provides an additional degree of freedom in all-optical switch design. Moreover, the proposed approach utilizes slower materials that are very robust and allow to enhance the field intensities while faster materials ensure an ultrafast dynamic response. The proposed control of the switching time could lead to new functionalities within key applications in multiband transmission, optical computing, and nonlinear optics.

Two-dimensional hexagonal boron nitride (hBN) has been known to host a variety of quantum emitters with properties suitable for a broad range of quantum photonic applications. Among them, the negatively charged boron vacancy (VB-) defect with optically addressable spin states has emerged recently due to its potential use in quantum sensing. Compared to spin defects in bulk crystals, VB- preserves its spin coherence properties when placed at nanometer-scale distances from the hBN surface, enabling nanometer-scale quantum sensing. On the other hand, the low quantum efficiency of VB- has hindered its use in practical applications. Several studies have reported improving the overall quantum efficiency of VB- defects using plasmonic effects; however, the overall enhancements of up to 17 times reported to date are relatively modest. In this study, we explore and demonstrate much higher emission enhancements of VB- with ultralow-loss nano-patch antenna (NPA) structures. An overall intensity enhancement of up to 250 times is observed for NPA-coupled VB- defects. Since the laser spot exceeds the area of the NPA, where the enhancement occurs, the actual enhancement provided by the NPA is calculated to be ~1685 times, representing a significant increase over the previously reported results. Importantly, the optically detected magnetic resonance (ODMR) contrast is preserved at such exceptionally strong enhancement. Our results not only establish NPA-coupled VB- defects as high-resolution magnetic field sensors operating at weak laser powers, but also provide a promising approach to obtaining single VB- defects., Comment: 17 pages, 4 figures

The Starshot lightsail project aims to build an ultralight spacecraft ("nanocraft") that can reach Proxima Centauri b in approximately 20 years, requiring propulsion with a relativistic velocity of ~60 000 km/s. The spacecraft's acceleration approach currently under investigation is based on applying the radiation pressure from a high-power laser array located on Earth to the spacecraft lightsail. However, the practical realization of such a spacecraft imposes extreme requirements to the lightsail's optical, mechanical, thermal properties. Within this work, we apply adjoint topology optimization and variational autoencoder-assisted inverse design algorithm to develop and optimize a silicon-based lightsail design. We demonstrate that the developed framework can provide optimized optical and opto-kinematic properties of the lightsail. Furthermore, the framework opens up the pathways to realizing a multi-objective optimization of the entire lightsail propulsion system, leveraging the previously demonstrated concept of physics-driven compressed space engineering

We describe a fourth-order accurate finite-difference time-domain scheme for solving dispersive Maxwell's equations with nonlinear multi-level carrier kinetics models. The scheme is based on an efficient single-step three time-level modified equation approach for Maxwell's equations in second-order form for the electric field coupled to ODEs for the polarization vectors and population densities of the atomic levels. The resulting scheme has a large CFL-one time-step. Curved interfaces between different materials are accurately treated with curvilinear grids and compatibility conditions. A novel hierarchical modified equation approach leads to an explicit scheme that does not require any nonlinear iterations. The hierarchical approach at interfaces leads to local updates at the interface with no coupling in the tangential directions. Complex geometry is treated with overset grids. Numerical stability is maintained using high-order upwind dissipation designed for Maxwell's equations in second-order form. The scheme is carefully verified for a number of two and three-dimensional problems. The resulting numerical model with generalized dispersion and arbitrary nonlinear multi-level system can be used for many plasmonic applications such as for ab initio time domain modeling of nonlinear engineered materials for nanolasing applications, where nano-patterned plasmonic dispersive arrays are used to enhance otherwise weak nonlinearity in the active media.

Room temperature single-photon sources (SPSs) are critical for the emerging practical quantum applications such as on-chip photonic circuity for quantum communications systems and integrated quantum sensors. However, direct integration of an SPS into on-chip photonic systems remains challenging due to low coupling efficiencies between the SPS and the photonic circuitry that often involve size mismatch and dissimilar materials. Here, we develop an adjoint topology optimization scheme to design high-efficiency couplers between a photonic waveguide and SPS in hexagonal boron nitride (hBN). The algorithm accounts for fabrication constraints and the SPS location uncertainty. First, a library of designs for the different positions of the hBN flake containing an SPS with respect to a Si$_{3}$N$_{4}$ waveguide is generated, demonstrating an average coupling efficiency of 78%. Then, the designs are inspected with dimensionality reduction technique to investigate the relationship between the device geometry (topology) and performance. The fundamental, physics-based intuition gained from this approach could enable the design of high-performance quantum devices

One of the main characteristics of optical imaging systems is the spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical super-resolution techniques, which aim at breaking the diffraction limit in classical systems, there is a class of quantum super-resolution techniques which leverage the non-classical nature of the optical signals radiated by quantum emitters, the so-called antibunching super-resolution microscopy. This approach can ensure a factor of $\sqrt{n}$ improvement in the spatial resolution by measuring the n-th order autocorrelation function. The main bottleneck of the antibunching super-resolution microscopy is the time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed framework paves the way to the practical realization of scalable quantum super-resolution imaging devices that can be compatible with various types of quantum emitters.

In recent years, there is a growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design problems into surrogate quadratic unconstrained binary optimization (QUBO) problems by employing a binary variational autoencoder and a factorization machine. The factorization machine is trained as a low-dimensional, binary surrogate model for the continuous design space and sampled using various QUBO samplers. Using the D-Wave Advantage hybrid sampler and simulated annealing, we demonstrate that by repeated resampling and retraining of the factorization machine, our framework finds designs that exhibit figures of merit exceeding those of its training set. We showcase the framework's performance on two inverse design problems by optimizing (i) thermal emitter topologies for thermophotovoltaic applications and (ii) diffractive meta-gratings for highly efficient beam steering. This technique can be further scaled to leverage future developments in quantum optimization to solve advanced inverse design problems for science and engineering applications.

Plasmonic color printing with semicontinuous metal films is a lithography-free, non-fading, and environment-friendly method of generation of bright colors. Such films are comprised of metal nanoparticles, which resonate at different wavelengths upon light illumination depending on the size and shape of the nanoparticles. To achieve an experimentally demonstrated structure that was optimized in terms of broader color range and increased stability, variable Ag semicontinuous metal films were deposited on a metallic mirror with a sub-wavelength-thick dielectric spacer. Femtosecond laser post-processing was then introduced to extend the color gamut through spectrally induced changes from blue to green, red, and yellow. Long-term stability and durability of the structures were addressed to enable non-fading colors with an optimized overcoating dielectric layer. The thickness of the proposed designs is on the order of 100 nanometers, and it can be deposited on any substrate. These structures generate a broad range of long-lasting colors in reflection that can be applied to real-life artistic or technological applications with a spatial resolution on the order of 0.3 mm or less.

Plasmonic color generation utilizing ultra-thin metasurfaces as well as metallic nanoparticles hold a great promise for a wide range of applications, including color displays, data storage, and information encryption due to its high spatial resolution and mechanical/chemical stability. Most of the recently demonstrated systems generate static colors; however, more advanced applications such as data storage require fast and flexible means to tune the plasmonic colors, while keeping them vibrant and stable. Here, a surface-relief aluminum metasurface that reflects polarization-tunable plasmonic colors is designed and experimentally demonstrated. Excitation of localized surface plasmons encodes discrete combinations of the incident and reflected polarized light into diverse colors. A single storage unit - a nanopixel - stores a multiple-bit piece of information in the orientation of its constituent nanoantennae. This information is then reliably retrieved by inspecting the reflected color sequence with two linear polarizers. It is the broad color variability and high spatial resolution of the proposed encoding approach that supports a strong promise for rapid parallel read-out and encryption of high-density optical data. Our method also enables the robust generation of dynamic kaleidoscopic images with no detrimental "cross-talk" effect. The approach opens up a new route for advanced dynamic steganography, high-density parallel-access optical data storage, and optical information encryption.

Over the past decade, artificially engineered optical materials and nanostructured thin films have revolutionized the area of photonics by employing novel concepts of metamaterials and metasurfaces where spatially varying structures yield tailorable, "by design" effective electromagnetic properties. The current state-of-the-art approach to designing and optimizing such structures relies heavily on simplistic, intuitive shapes for their unit cells or meta-atoms. Such approach can not provide the global solution to a complex optimization problem where both meta-atoms shape, in-plane geometry, out-of-plane architecture, and constituent materials have to be properly chosen to yield the maximum performance. In this work, we present a novel machine-learning-assisted global optimization framework for photonic meta-devices design. We demonstrate that using an adversarial autoencoder coupled with a metaheuristic optimization framework significantly enhances the optimization search efficiency of the meta-devices configurations with complex topologies. We showcase the concept of physics-driven compressed design space engineering that introduces advanced regularization into the compressed space of adversarial autoencoder based on the optical responses of the devices. Beyond the significant advancement of the global optimization schemes, our approach can assist in gaining comprehensive design "intuition" by revealing the underlying physics of the optical performance of meta-devices with complex topologies and material compositions.

The strong electric and magnetic resonances in dielectric subwavelength structures have enabled unique opportunities for efficient manipulation of light-matter interactions. Besides, the dramatic enhancement of nonlinear light-matter interactions near so-called bound states in the continuum (BICs) has recently attracted enormous attention due to potential advancements in all-optical and quantum computing. However, the experimental realizations and the applications of high- Q factor resonances in dielectric resonances in the visible regime have thus far been considerably limited. In this work, we explore the interplay of electric and magnetic dipoles in arrays of dielectric nanoresonators to enhance light-matter interaction. We report on the experimental realization of high-Q factor resonances in the visible through the collective diffractive coupling of electric and magnetic dipoles. Providing direct physical insights, we also show that coupling the Rayleigh anomaly of the array with the electric and magnetic dipoles of the individual nanoresonators can result in the formation of different types of BICs. We utilize the resonances in the visible regime to achieve lasing action at room temperature with high spatial directionality and low threshold. Finally, we experimentally demonstrate multi-mode, directional lasing and study the BIC-assisted lasing mode engineering in arrays of dielectric nanoresonators. We believe that our results enable a new range of applications in flat photonics through realizing on-chip controllable single and multi-wavelength micro-lasers.

Machine-learning tasks performed by neural networks demonstrated useful capabilities for producing reliable, and repeatable intelligent decisions. Integrated photonics, leveraging both component miniaturization and the wave-nature of the signals, can potentially outperform electronics architectures when performing inference tasks. However, the missing photon-photon force challenges non-volatile photonic device-functionality required for efficient neural networks. Here we present a novel concept and optimization of multi-level discrete-state non-volatile photonic memory based on an ultra-compact (<4um) hybrid phase change material GSST-silicon Mach Zehnder modulator, with low insertion losses (3dB), to serve as node in a photonic neural network. An optimized electro-thermal switching mechanism, induced by Joule heating through tungsten contacts, is engineered. This operation allows to change the phase of the GSST film thus providing weight updating functionality to the network. We show that a 5 V pulse-train (<1 us, 20 pulses) applied to a serpentine contact produces crystallization and a single pulse of longer duration (2 us) amorphization, used to set the analog synaptic weights of a neuron. Emulating an opportunely trained 100x100 fully connected multilayered perceptron neural network with this weighting functionality embedded as photonic memory, shows up to 93% inference accuracy and robustness towards noise when performing predictions of unseen data

With the emergence of new photonic and plasmonic materials with optimized properties as well as advanced nanofabrication techniques, nanophotonic devices are now capable of providing solutions to global challenges in energy conversion, information technologies, chemical/biological sensing, space exploration, quantum computing, and secure communication. Addressing grand challenges poses inherently complex, multi-disciplinary problems with a manifold of stringent constraints in conjunction with the required system's performance. Conventional optimization techniques have long been utilized as powerful tools to address multi-constrained design tasks. One example is so-called topology optimization that has emerged as a highly successful architect for the advanced design of non-intuitive photonic structures. Despite many advantages, this technique requires substantial computational resources and thus has very limited applicability to highly constrained optimization problems within high-dimensions parametric space. In our approach, we merge the topology optimization method with machine learning algorithms such as adversarial autoencoders and show substantial improvement of the optimization process by providing unparalleled control of the compact design space representations. By enabling efficient, global optimization searches within complex landscapes, the proposed compact hyperparametric representations could become crucial for multi-constrained problems. The proposed approach could enable a much broader scope of the optimal designs and data-driven materials synthesis that goes beyond photonic and optoelectronic applications.

Integrated on-demand single-photon sources are critical for the implementation of photonic quantum information processing systems. To enable practical quantum photonic devices, the emission rates of solid-state quantum emitters need to be substantially enhanced and the emitted signal must be directly coupled to an on-chip circuitry. The photon emission rate speed-up is best achieved via coupling to plasmonic antennas, while on-chip integration can be easily obtained by directly coupling emitters to photonic waveguides. The realization of practical devices requires that both the emission speed-up and efficient out-couping are achieved in a single architecture. Here, we propose a novel platform that effectively combines on-chip compatibility with high radiative emission rates, a quantum plasmonic launcher. The proposed launchers contain single nitrogen-vacancy (NV) centers in nanodiamonds as quantum emitters that offer record-high average fluorescence lifetime shortening factors of about 7000 times. Nanodiamonds with single NV are sandwiched between two silver films that couple more than half of the emission into in-plane propagating surface plasmon polaritons. This simple, compact, and scalable architecture represents a crucial step towards the practical realization of high-speed on-chip quantum networks.

Deterministic nanoassembly may enable unique integrated on-chip quantum photonic devices. Such integration requires a careful large-scale selection of nanoscale building blocks such as solid-state single-photon emitters by the means of optical characterization. Second-order autocorrelation is a cornerstone measurement that is particularly time-consuming to realize on a large scale. We have implemented supervised machine learning-based classification of quantum emitters as "single" or "not-single" based on their sparse autocorrelation data. Our method yields a classification accuracy of over 90% within an integration time of less than a second, realizing roughly a hundredfold speedup compared to the conventional, Levenberg-Marquardt approach. We anticipate that machine learning-based classification will provide a unique route to enable rapid and scalable assembly of quantum nanophotonic devices and can be directly extended to other quantum optical measurements., Comment: Adv. Quantum Technol. 2020

On-chip scalable integration represents a major challenge for practical quantum devices. One particular challenge is to implement on-chip optical readout of spins in diamond. This readout requires simultaneous application of optical and microwave fields along with an efficient collection of fluorescence. The readout is typically accomplished via bulk optics and macroscopic microwave transmission structures. We experimentally demonstrate an on-chip integrated structure for nitrogen vacancy (NV) spin-based applications, implemented in a single material layer with one patterning step. A nanodiamond with multiple NV centres is positioned at the end of the groove waveguide milled in a thick gold film. The gold film carries the microwave control signal while the groove waveguide acts as a fluorescence collector, partially filtering out the pump excitation. As a result, the device dimensions and fabrication complexity are substantially reduced. Our approach will foster further development of ultra-compact nanoscale quantum sensors and quantum information processing devices on a monolithic platform. NV centre-based nanoscale sensors are the most promising application of the developed interface., Comment: 17 pages, 9 figures

On-demand, switchable phase transitions between topologically non-trivial and trivial photonic states are demonstrated. Specifically, it is shown that integration of a 2D array of coupled ring resonators within a thermal heater array enables unparalleled control over topological protection of photonic modes. Importantly, auxiliary control over spatial phase modulation opens up a way to guide topologically protected edge modes along generated virtual boundaries. The proposed approach can lead to practical realizations of topological phase transitions in many photonic applications, including topologically protected photonic memory/logic devices, robust optical modulators, and switches.

Quantum emitters coupled to plasmonic nanoantennas produce single photons at unprecedentedly high rates in ambient conditions. This enhancement of quantum emitters' radiation rate is based on the existence of optical modes with highly sub-diffraction volumes supported by plasmonic gap nanoantennas. Nanoantennas with gap sizes on the order of few nanometers have been typically produced using various self-assembly or random assembly techniques. Yet, the difficulty of controllably fabricate nanoantennas with the smallest mode sizes coupled to pre-characterized single emitters until now has remained a serious issue plaguing the development of quantum plasmonic devices. We demonstrate the transfer of nanodiamonds with single nitrogen-vacancy (NV) centers to an epitaxial silver substrate and their subsequent deterministic coupling to plasmonic gap nanoantennas. Through fine control of the assembled nanoantenna geometry, a dramatic shortening of the NV fluorescence lifetime was achieved. We furthermore show that by preselecting NV centers exhibiting a photostable spin contrast, a coherent spin dynamics can be measured in the coupled configuration. The demonstrated approach opens unique applications of plasmon-enhanced quantum emitters for integrated quantum information and sensing devices., Comment: 12 pages, 4 figures

With the recent successes of neural networks (NN) to perform machine-learning tasks, photonic-based NN designs may enable high throughput and low power neuromorphic compute paradigms since they bypass the parasitic charging of capacitive wires. Thus, engineering data-information processors capable of executing NN algorithms with high efficiency is of major importance for applications ranging from pattern recognition to classification. Our hypothesis is therefore, that if the time-limiting electro-optic conversion of current photonic NN designs could be postponed until the very end of the network, then the execution time of the photonic algorithm is simple the delay of the time-of-flight of photons through the NN, which is on the order of picoseconds for integrated photonics. Exploring such all-optical NN, in this work we discuss two independent approaches of implementing the optical perceptrons nonlinear activation function based on nanophotonic structures exhibiting i) induced transparency and ii) reverse saturated absorption. Our results show that the all-optical nonlinearity provides about 3 and 7 dB extinction ratio for the two systems considered, respectively, and classification accuracies of an exemplary MNIST task of 97% and near 100% are found, which rivals that of software based trained NNs, yet with ignored noise in the network. Together with a developed concept for an all-optical perceptron, these findings point to the possibility of realizing pure photonic NNs with potentially unmatched throughput and even energy consumption for next generation information processing hardware.

A bound state in the continuum (BIC) is a localized state of an open structure with access to radiation channels, yet it remains highly confined with, in theory, infinite lifetime and quality factor. There have been many realizations of such exceptional states in dielectric systems without loss. However, realizing BICs in systems with losses such as plasmonics remains a challenge. In this Letter, we explore the possibility of realizing BICs in a hybrid plasmonic-photonic structure consisting of a plasmonic grating coupled to a dielectric optical waveguide. The plasmonic-photonic system supports two distinct groups of BICs: symmetry protected BICs at the {\Gamma}-point and off-{\Gamma} Friedrich-Wintgen BICs. The photonic waveguide modes are strongly coupled to the gap plasmons in the grating leading to an avoided crossing behavior with a high value of Rabi splitting of 150 meV. Moreover, we show that the strong coupling significantly alters the band diagram of the hybrid system revealing opportunities for supporting stopped light at an off-{\Gamma} wide angular span.

An advanced full-wave time-domain numerical model for reverse saturable absorption (RSA) is presented and verified against established methods. Rate equations, describing atomic relaxations and excitation dynamics, are coupled to Maxwell equations by using a Lorentzian oscillator. These oscillator models the kinetics-dependent light-matter interaction in the form of averaged polarizations. The coupled equations are discretized in space and time using a finite-difference time-domain method which provides a versatile platform to design complex structures and integrate diverse material models. We believe that our models are crucial tools enabling for the realization and optimization of optical limiting and all-optical switching systems.

Over the past years, photonic metasurfaces have demonstrated their remarkable and diverse capabilities for achieving advanced control over light propagation by confining electromagnetic radiation within the deeply subwavelength thickness of these artificial films. Here, we demonstrate that metasurfaces also offer new unparalleled capabilities for decreasing the overall dimensions of integrated optical components and systems. We propose an original approach of embedding a metasurface inside one of the most fundamental optical elements -an optical cavity- to drastically scale-down the thickness of the optical cavity. We apply this methodology to design and implement a metasurfaces-based nano-cavity where the Fabry-Perot interferometric principle has been modified to reduce the cavity thickness below the conventional half-wavelength minimum. In addition, the nano-cavities with embedded metasurfaces can support independently tunable resonances at multiple bands. As a proof-of-concept, using nano-structured metasurfaces within 100-nm nano-cavities, we experimentally demonstrate high spatial resolution color filtering and spectral imaging. The proposed approach can be extrapolated to compact integrated optical systems on-a-chip such as VCSEL, high-resolution spatial light modulators, imaging spectroscopy systems, and bio-sensors.

The demand for faster magnetization switching speeds and lower energy consumption has driven the field of spintronics in recent years. The magnetic tunnel junction is the most developed spintronic memory device in which the magnetization of the storage layer is switched by spin-transfer-torque or spin-orbit torque interactions. Whereas these novel spin-torque interactions exemplify the potential of electron-spin-based devices and memory, the switching speed is limited to the ns regime by the precessional motion of the magnetization. All-optical magnetization switching, based on the inverse Faraday effect, has been shown to be an attractive method for achieving magnetization switching at ps speeds. Successful magnetization reversal in thin films has been demonstrated by using circularly polarized light. However, a method for all-optical switching of on-chip nanomagnets in high density memory modules has not been described. In this work we propose to use plasmonics, with CMOS compatible plasmonic materials, to achieve on-chip magnetization reversal in nanomagnets. Plasmonics allows light to be confined in dimensions much smaller than the diffraction limit of light. This in turn, yields higher localized electromagnetic field intensities. In this work, through simulations, we show that using localized surface plasmon resonances, it is possible to couple light to nanomagnets and achieve significantly higher opto-magnetic field values in comparison to free space light excitation., Comment: 11 pages (10 pages main paper and 1 page supplementary), 7 figures (6 figures in main paper with 1 figure in supplementary)

Due to their exceptional plasmonic properties, noble metals such as gold and silver have been the materials of choice for the demonstration of various plasmonic and nanophotonic phenomena. However, noble metals' softness, lack of tailorability and low melting point along with challenges in thin film fabrication and device integration have prevented the realization of real-life plasmonic devices.In the recent years, titanium nitride (TiN) has emerged as a promising plasmonic material with good metallic and refractory (high temperature stable) properties. The refractory nature of TiN could enable practical plasmonic devices operating at elevated temperatures for energy conversion and harsh-environment industries such as gas and oil. Here we report on the temperature dependent dielectric functions of TiN thin films of varying thicknesses in the technologically relevant visible and near-infrared wavelength range from 330 nm to 2000 nm for temperatures up to 900 0C using in-situ high temperature ellipsometry. Our findings show that the complex dielectric function of TiN at elevated temperatures deviates from the optical parameters at room temperature, indicating degradation in plasmonic properties both in the real and imaginary parts of the dielectric constant. However, quite strikingly, the relative changes of the optical properties of TiN are significantly smaller compared to its noble metal counterparts. Using simulations, we demonstrate that incorporating the temperature-induced deviations into the numerical models leads to significant differences in the optical responses of high temperature nanophotonic systems. These studies hold the key for accurate modeling of high temperature TiN based optical elements and nanophotonic systems for energy conversion, harsh-environment sensors and heat-assisted applications., Comment: 23 pages, 9 figures and 5 tables

Coherent nanoscale photon sources are of paramount importance to achieving all-optical communication. Several nanolasers smaller than the diffraction limit have been theoretically proposed and experimentally demonstrated using plasmonic cavities to confine optical fields. Such compact cavities exhibit large Purcell factors, thereby enhancing spontaneous emission, which feeds into the lasing mode. However, most plasmonic nanolasers reported so far have employed resonant nanostructures and therefore had the lasing restricted to the proximity of the resonance wavelength. Here, we report on an approach based on gold nanorod hyperbolic metamaterials for lasing. Hyperbolic metamaterials provide broadband Purcell enhancement due to large photonic density of optical states, while also supporting surface plasmon modes to deliver optical feedback for lasing due to nonlocal effects in nanorod media. We experimentally demonstrate the advantage of hyperbolic metamaterials in achieving lasing action by its comparison with that obtained in a metamaterial with elliptic dispersion. The conclusions from the experimental results are supported with numerical simulations comparing the Purcell factors and surface plasmon modes for the metamaterials with different dispersions. We show that although the metamaterials of both types support lasing, emission with hyperbolic samples is about twice as strong with 35% lower threshold vs. the elliptic ones. Hence, hyperbolic metamaterials can serve as a convenient platform of choice for nanoscale coherent photon sources in a broad wavelength range.

The use of hot electrons generated from the decay of surface plasmons is a new paradigm to increase the conversion yield in solar energy technologies. Titanium nitride (TiN) is an emerging plasmonic ceramic that offers compatibility with CMOS technology, corrosion resistance, as well as mechanical strength and durability thus outperforming noble metals (i.e., Au, Ag) in terms of cost, mechanical, chemical and thermal stability. Here, we show that plasmonic TiN nanoparticles produce 25% higher photocurrent enhancement than Au nanoparticles decorated on TiO2 nanowires for photoelectrochemical water splitting. Our results highlight that TiN offers superior performance in hot carrier generation due to enhanced absorption efficiency, increased electron mean free path, and the ability to form an Ohmic junction with TiO2, thus enabling an extremely efficient electron collection not achievable with plasmonic Au nanoparticles. Our findings show that transition metal nitrides enable practical plasmonic devices with enhanced performance for solar energy conversion., Comment: 31 pages (Manuscript+Supporting Information), 4 figures, 13 supplementary figures

Understanding the temperature dependence of the optical properties of thin metal films is critical for designing practical devices for high temperature applications in a variety of research areas, including plasmonics and near-field radiative heat transfer. Even though the optical properties of bulk metals at elevated temperatures have been studied, the temperature-dependent data for thin metal films, with thicknesses ranging from few tens to few hundreds of nanometers, is largely missing. In this work we report on the optical constants of single- and polycrystalline gold thin films at elevated temperatures in the wavelength range from 370 to 2000 nm. Our results show that while the real part of the dielectric function changes marginally with increasing temperature, the imaginary part changes drastically. For 200-nm-thick single- and polycrystalline gold films the imaginary part of the dielectric function at 500 0C becomes nearly twice larger than that at room temperature. In contrast, in thinner films (50-nm and 30-nm) the imaginary part can show either increasing or decreasing behavior within the same temperature range and eventually at 500 0C it becomes nearly 3-4 times larger than that at room temperature. The increase in the imaginary part at elevated temperatures significantly reduces the surface plasmon polariton propagation length and the quality factor of the localized surface plasmon resonance for a spherical particle. We provide experiment-fitted models to describe the temperature-dependent gold dielectric function as a sum of one Drude and two Critical Point oscillators. These causal analytical models could enable accurate multiphysics modelling of gold-based nanophotonic and plasmonic elements in both frequency and time domains., Comment: 39 pages and 16 figures

Plasmonic resonances in metallic nanostructures have been shown to drastically enhance local electromagnetic fields, and thereby increase the efficiency of nonlinear optical phenomena, such as second harmonic generation (SHG). While it has been experimentally observed that enhanced fields can significantly boost SHG, to date it proved difficult to probe electrical and magnetic resonances in one and the same nanostructure. This however is necessary to directly compare relative contributions of electrical and magnetic components of SHG enhancement. In this paper we report an experimental study of a metasurface capable of providing electrical and magnetic resonant SHG enhancement for TM polarization. Our metasurface could be engineered such that the peak frequencies of electrical and magnetic resonances could be adjusted independently. We used this feature to distinguish their relative contributions. Experimentally it was observed that the magnetic resonance provides only 50% as much enhancement to SHG as compared to the electric resonance. In addition aligning both resonances in frequency results in conversion efficiency of 1.32 x 10^(-10)., Comment: 9 pages; 7 figures

Plasmon resonance in nanopatterned single layer graphene nanoribbon (SL-GNR), double layer graphene nanoribbon (DL-GNR) and triple layer graphene nanoribbon (TL-GNR) structures is studied both experimentally and by numerical simulations. We use 'realistic' graphene samples in our experiments to identify the key bottle necks in both experiments and theoretical models. The existence of electrical tunable plasmons in such stacked multilayer GNRs was first experimentally verified by infrared microscopy. We find that the strength of the plasmonic resonance increases in DL-GNR when compared to SL-GNRs. However, we do not find a further such increase in TL-GNRs compared to DL-GNRs. We carried out systematic full wave simulations using finite element technique to validate and fit experimental results, and extract the carrier scattering rate as a fitting parameter. The numerical simulations show remarkable agreement with experiments for unpatterned SLG sheet, and a qualitative agreement for patterned graphene sheet. We believe that further improvements such as introducing a bandgap into the numerical model could lead to a better quantitative agreement of numerical simulations with experiments. We also note that such advanced modeling would first require better quality graphene samples and accurate measurements.