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Diamond color centers have been widely studied in the field of quantum optics. The negatively charged silicon vacancy (SiV−) center exhibits a narrow emission linewidth at the wavelength of 738 nm, a high Debye–Waller factor, and unique spin properties, making it a promising emitter for quantum information technologies, biological imaging, and sensing. In particular, nanodiamond (ND)-based SiV− centers can be heterogeneously integrated with plasmonic and photonic nanostructures and serve as in vivo biomarkers and intracellular thermometers. Out of all methods to produce NDs with SiV− centers, ion implantation offers the unique potential to create controllable numbers of color centers in preselected individual NDs. However, the formation of single color centers in NDs with this technique has not been realized. We report the creation of single SiV− centers featuring stable high-purity single-photon emission through Si implantation into NDs with an average size of ∼20 nm. We observe room temperature emission, with zero-phonon line wavelengths in the range of 730–800 nm and linewidths below 10 nm. Our results offer new opportunities for the controlled production of group-IV diamond color centers with applications in quantum photonics, sensing, and biomedicine.

Multilayer films with continuously varying indices for each layer have attracted great deal of attention due to their superior optical, mechanical, and thermal properties. However, difficulties in fabrication have limited their application and study in scientific literature compared to multilayer films with fixed index layers. In this work we propose a neural network based inverse design technique enabled by a differentiable analytical solver for realistic design and fabrication of single material variable-index multilayer films. This approach generates multilayer films with excellent performance under ideal conditions. We furthermore address the issue of how to translate these ideal designs into practical useful devices which will naturally suffer from growth imperfections. By integrating simulated systematic and random errors just as a deposition tool would into the optimization process, we demonstrated that the same neural network that produced the ideal device can be retrained to produce designs compensating for systematic deposition errors. Furthermore, the proposed approach corrects for systematic errors even in the presence of random fabrication imperfections. The results outlined in this paper provide a practical and experimentally viable approach for the design of single material multilayer film stacks for an extremely wide variety of practical applications with high performance.

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

We present an experimental study of optical time-refraction caused by time-interfaces as short as a single optical cycle. Specifically, we study the propagation of a probe pulse through a sample undergoing a large refractive index change induced by an intense modulator pulse. In these systems, increasing the refractive index abruptly leads to time-refraction where the spectrum of all the waves propagating in the medium is red-shifted, and subsequently blue-shifted when the refractive index relaxes back to its original value. We observe these phenomena in the single-cycle regime. Moreover, by shortening the temporal width of the modulator to ∼5–6 fs, we observe that the rise time of the red-shift associated with time-refraction is proportionally shorter. The experiments are carried out in transparent conducting oxides acting as epsilon-near-zero materials. These observations raise multiple questions on the fundamental physics occurring within such ultrashort time frames, and open the way for experimenting with photonic time-crystals, generated by periodic ultrafast changes to the refractive index, in the near future.

Plasmonic transdimensional materials (TDMs), which are atomically thin metals of precisely controlled thickness, are expected to exhibit large tailorability and dynamic tunability of their optical response as well as strong light confinement and nonlocal effects. Using spectroscopic ellipsometry, we characterize the complex permittivity of ultrathin films of passivated plasmonic titanium nitride with thicknesses ranging from 1 to 10 nm. By measuring passivated TiN, we experimentally distinguish between the contributions of an oxide layer and thickness to the optical properties. A decrease in the Drude plasma frequency and increase in the damping in thinner films is observed due to spatial confinement. We explain the experimental trends using a nonlocal Drude dielectric response theory based on the Keldysh-Rytova (KR) potential that predicts the thickness-dependent optical properties caused by electron confinement in plasmonic TDMs. Our experimental findings are consistent with the KR model and demonstrate quantum-confinement-induced optical properties in plasmonic transdimensional TiN.

Recent advances in ultrafast, large-modulation photonic materials have opened the door to many new areas of research. One specific example is the exciting prospect of photonic time crystals. In this perspective, we outline the most recent material advances that are promising candidates for photonic time crystals. We discuss their merit in terms of modulation speed and depth. We also investigate the challenges yet to be faced and provide our estimation on possible roads to success.

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

Over the past years, broadband achromatic metalenses have been intensively studied due to their great potential for applications in consumer and industry products. Even though significant progress has been made, the efficiency of technologically relevant silicon metalenses is limited by the intrinsic material loss above the bandgap. In turn, the recently proposed achromatic metalens utilizing transparent, high-index materials such as titanium dioxide has been restricted by the small thickness and showed relatively low focusing efficiency at longer wavelengths. Consequently, metalens-based optical imaging in the biological transparency window has so far been severely limited. Herein, we experimentally demonstrate a polarization-insensitive, broadband titanium dioxide achromatic metalens for applications in the near-infrared biological imaging. A large-scale fabrication technology has been developed to produce titanium dioxide nanopillars with record-high aspect ratios featuring pillar heights of 1.5 µm and ~90° vertical sidewalls. The demonstrated metalens exhibits dramatically increased group delay range, and the spectral range of achromatism is substantially extended to the wavelength range of 650–1000 nm with an average efficiency of 77.1%–88.5% and a numerical aperture of 0.24–0.1. This research paves a solid step towards practical applications of flat photonics., Though broadband achromatic metalens are attractive for biological applications, existing metalenses show limited performance in the biological imaging window. Here, the authors report high-efficiency broadband achromatic metalens featuring record-high aspect ratio titanium dioxide metasurfaces.

All-optical switches offer advanced control over the amplitude, phase, and/or polarization of light at ultrafast timescales using optical pulses as both the carrying signal and the control. Limited only by material response times, these switches can operate at terahertz speeds which is 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 generally 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 (ENZ) operational regime of a material with a slow response time, namely, plasmonic titanium nitride, the proposed hybrid switch exhibits a relatively slow, nanosecond response time. The response time then decreases as the probe wavelength increases reaching the picosecond time scale when the hybrid device is probed 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 interactions in a multi-material structure provides an additional degree of freedom in the design of all-optical switches. 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 and performance metrics within key applications in multiband transmission, optical computing, and nonlinear optics.

The dielectric permittivity of a material encapsulates the essential physics of light-matter interaction into the material’s local response to optical excitation. Photo-induced modulation of the permittivity can enable an unprecedented level of control over the phase, amplitude, and polarization of light. Therefore, the detailed dynamic characterization of technology-relevant materials with substantially tunable optical properties and fast response times is a crucial step to realize tunable optical devices. This work reports on the extraordinarily large permittivity changes in zinc oxide thin films (up to −3.6 relative change in the real part of the dielectric permittivity at 1600 nm wavelength) induced by optically generated free carriers. We demonstrate broadband reflectance modulation up to 70% in metal-backed oxide mirrors at the telecommunication wavelengths, with picosecond-scale relaxation times. The epsilon near zero points of the films can be dynamically shifted from 8.5 µm to 1.6 µm by controlling the pump fluence. The modulation can be selectively enhanced at specific wavelengths employing metal-backed zinc oxide disks while maintaining picosecond-scale switching times. This work provides insights into the free-carrier assisted permittivity modulation in zinc oxide and could enable the realization of novel dynamic devices for beam-steering, polarizers, and spatial light modulators.

Plasmonic color printing with semicontinuous metal films is a lithography-free and environment-friendly method for generating nonfading bright colors. Such films are comprised of islands, metal nan...

The recent discovery of room temperature intrinsic single-photon emitters in silicon nitride (SiN) provides the unique opportunity for seamless monolithic integration of quantum light sources with the well-established SiN photonic platform. In this work, we develop a novel approach to realize planar waveguides made of low-autofluorescing SiN with intrinsic quantum emitters and demonstrate the single-photon emission coupling into the waveguide mode. The observed emission coupling from these emitters is found to be in line with numerical simulations. The coupling of the single-photon emission to a waveguide mode is confirmed by second-order autocorrelation measurements of light outcoupled off the photonic chip by grating couplers. Fitting the second-order autocorrelation histogram yields $g^{(2)}(0)=0.35\pm0.12$ without spectral filtering or background correction with an outcoupled photon rate of $10^4$ counts per second. This demonstrates the first successful coupling of photons from intrinsic single-photon emitters in SiN to monolithically integrated waveguides made of the same material. The results of our work pave the way toward the realization of scalable, technology-ready quantum photonic integrated circuitry efficiently interfaced with solid-state quantum emitters., 10 pages, 5 figures

Innovative approaches and tools play an important role in shaping design, characterization and optimization for the field of photonics. As a subset of machine learning that learns multilevel abstraction of data using hierarchically structured layers, deep learning offers an efficient means to design photonic structures, spawning data-driven approaches complementary to conventional physics- and rule-based methods. Here, we review recent progress in deep-learning-based photonic design by providing the historical background, algorithm fundamentals and key applications, with the emphasis on various model architectures for specific photonic tasks. We also comment on the challenges and perspectives of this emerging research direction. The application of deep learning to the design of photonic structures and devices is reviewed, including algorithm fundamentals.

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 metaatoms. Such an approach cannot provide the global solution to a complex optimization problem where metaatom 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 metadevice design. We demonstrate that using an adversarial autoencoder (AAE) coupled with a metaheuristic optimization framework significantly enhances the optimization search efficiency of the metadevice configurations with complex topologies. We showcase the concept of physics-driven compressed design space engineering that introduces advanced regularization into the compressed space of an AAE 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 metadevices with complex topologies and material compositions.

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 ...

As plasmonic materials transition from three-dimensional to two-dimensional (2D) form, unique optical and electronic phenomena arise that are unattainable in bulk materials and conventional thin films. Exceptional sensitivity to external perturbations, including electrical biasing and optical excitation as well as quantum effects, are expected to emerge, as has been demonstrated in graphene. Similarly, metallic or plasmonic films with thicknesses down to a few monolayers, called transdimensional materials (TDMs), are predicted to exhibit remarkably strong tunability of their optical response. The unique properties of 2D materials and TDMs have established them as promising platforms for dynamic nanophotonic devices. While novel 2D materials have been widely explored for nanophotonic devices, until recently, there have been minimal studies on the evolution of the optical properties of plasmonic TDMs. In this article, we highlight progress in exploring the thickness-dependent optical response of plasmonic materials as they approach the 2D regime. Experimental and theoretical investigations of the plasmonic properties of 2D materials, such as graphene and tungsten diselenide, TDMs, and plasmonic thin films, are discussed, with a focus on prospects for their utilization in dynamically tunable flat optical devices or metasurfaces.

In this work, temperature-dependent optical properties of refractory plasmonic transition metal nitrides and dielectric thin films are utilized to design and realize a planar, direct-contact, nanop...

Silicon nitride has great potential for integrated quantum photonics. We demonstrate monolithic integration of intrinsic quantum emitters in SiN with waveguides which show a room-temperature off-chip count rate of ~104 counts/s and clear antibunching behavior.

We demonstrate 300 percent increase of second-harmonic generation from Weyl semimetal TaAs surface by distributing plasmonic silver nanoantennas on TaAs. Normalizing laser spot size area over silver nanoantenna areas yields actual SHG enhancement is 90-fold.

We report on the generation of single-photon emitters in silicon nitride. We demonstrate monolithic integration of these quantum emitters with silicon nitride waveguides showing a room-temperature off-chip count-rate of ~104 counts/s and clear antibunching behavior.

We demonstrate actively tunable third harmonic generation (THG) in zinc oxide, increasing THG by 600%. This is done using an interband pump, generating free carriers to increase Kerr nonlinearities, and enhancing fields through permittivity reduction.

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

Random lasing in organic-inorganic lead halide quasi-2D perovskite was observed by measuring lasing threshold, spectral narrowing, spectral correlations and critical volume. The photon transport mean free path is found to be comparable to the lasing wavelength, suggesting a hybrid localized-diffusive lasing regime.

We experimentally demonstrate quantum confinement induced thickness dependent optical properties in atomically-thin, passivated, epitaxial, metallic TiN films using spectroscopic ellipsometry as predicted by a nonlocal Drude dielectric response model for plasmonic transdimensional materials (TDMs).

Solar-thermal technologies for converting chemicals using thermochemistry require extreme light concentration. Exploiting plasmonic nanostructures can dramatically increase the reaction rates by providing more efficient solar-to-heat conversion by broadband light absorption. Moreover, hot-carrier and local field enhancement effects can alter the reaction pathways. Such discoveries have boosted the field of photothermal catalysis, which aims at driving industrially-relevant chemical reactions using solar illumination rather than conventional heat sources. Nevertheless, only large arrays of plasmonic nano-units on a substrate, i.e., plasmonic metasurfaces, allow a quasi-unitary and broadband solar light absorption within a limited thickness (hundreds of nanometers) for practical applications. Through moderate light concentration (∼10 Suns), metasurfaces reach the same temperatures as conventional thermochemical reactors, or plasmonic nanoparticle bed reactors reach under ∼100 Suns. Plasmonic metasurfaces, however, have been mostly neglected so far for applications in the field of photothermal catalysis. In this Perspective, we discuss the potentialities of plasmonic metasurfaces in this emerging area of research. We present numerical simulations and experimental case studies illustrating how broadband absorption can be achieved within a limited thickness of these nanostructured materials. The approach highlights the synergy among different enhancement effects related to the ordered array of plasmonic units and the efficient heat transfer promoting faster dynamics than thicker structures (such as powdered catalysts). We foresee that plasmonic metasurfaces can play an important role in developing modular-like structures for the conversion of chemical feedstock into fuels without requiring extreme light concentrations. Customized metasurface-based systems could lead to small-scale and low-cost decentralized reactors instead of large-scale, infrastructure-intensive power plants.

We present recent advances and future perspectives in using machine learning for characterization, fabrication, and inverse design for device applications, such as hybrid quantum-classical optimization of nanostructures, hypothesis learning for automated discovery, and pre-characterization binning.