The 100 most-cited articles in Optics Express, 2019

and is over five orders of magnitude faster than conventional electromagnetic simulation software. We further develop a novel method to solve the inverse modeling problem, termed fast forward dictionary search (FFDS), which offers tremendous controls to the designer and only requires an accurate forward neural network model. These techniques significantly increase the viability of more complex all-dielectric metasurface designs and provide opportunities for the future of tailored light matter interactions.

Phase unwrapping is an important but challenging issue in phase measurement. Even with the research efforts of a few decades, unfortunately, the problem remains not well solved, especially when heavy noise and aliasing (undersampling) are present. We propose a database generation method for phase-type objects and a one-step deep learning phase unwrapping method. With a trained deep neural network, the unseen phase fields of living mouse osteoblasts and dynamic candle flame are successfully unwrapped, demonstrating that the complicated nonlinear phase unwrapping task can be directly fulfilled in one step by a single deep neural network. Excellent anti-noise and anti-aliasing performances outperforming classical methods are highlighted in this paper.

Artificial intelligence (AI) techniques such as deep learning (DL) for computational imaging usually require to experimentally collect a large set of labeled data to train a neural network. Here we demonstrate that a practically usable neural network for computational imaging can be trained by using simulation data. We take computational ghost imaging (CGI) as an example to demonstrate this method. We develop a one-step end-to-end neural network, trained with simulation data, to reconstruct two-dimensional images directly from experimentally acquired one-dimensional bucket signals, without the need of the sequence of illumination patterns. This is in particular useful for image transmission through quasi-static scattering media as little care is needed to take to simulate the scattering process when generating the training data. We believe that the concept of training using simulation data can be used in various DL-based solvers for general computational imaging.

with 7% overhead. The distance can be extended if the received optical power is allowed to reduce to the minimum power to meet the data rate requirement. Based on the measured minimum required power and the power decay model in the water channel, the transmission performance was predicted to be 146 m/500 Mbps and 174 m/100 Mbps.

We report on a laser frequency sweep linearization method by iterative learning pre-distortion for frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) systems. A pre-distorted laser drive voltage waveform that results in a linear frequency sweep is obtained by an iterative learning controller, and then applied to the FMCW LiDAR system. We have also derived a fundamental figure of merit for the maximum residual nonlinearity needed to achieve the transform-limited range resolution. This method is experimentally tested using a commercial vertical cavity surface-emitting laser (VCSEL) and a distributed feedback (DFB) laser, achieving less than 0.005% relative residual nonlinearity of frequency sweep. With the proposed method, high-performance FMCW LiDAR systems can be realized without expensive linear lasers, complex linearization setups, or heavy post-processing.

High-power flip-chip light-emitting diodes (FCLEDs) suffer from low efficiencies because of poor p-type reflective ohmic contact and severe current crowding. Here, we show that it is possible to improve both the light extraction efficiency (LEE) and current spreading of an FCLED by incorporating a highly reflective metallic reflector made from silver (Ag). The reflector, which consists of an Ag film covered by three pairs of TiW/Pt multilayers, demonstrates high reflectance of 95.0% at 460 nm at arbitrary angles of incidence. Our numerical simulation and experimental results reveal that the FCLED with Ag-based reflector exhibits higher LEE and better current spreading than the FCLED with indium-tin oxide (ITO)/distributed Bragg reflector (DBR). As a result, the external quantum efficiency (EQE) of FCLED with Ag-based reflector was 6.0% higher than that of FCLED with ITO/DBR at 750 mA injection current. Our work also suggests that the EQE of FCLED with the Ag-based reflector could be further enhanced 5.2% by replacing the finger-like n-electrodes with three-dimensional (3D) vias…

We present a new class of wavefront sensors by extending their design space based on machine learning. This approach simplifies both the optical hardware and image processing in wavefront sensing. We experimentally demonstrated a variety of image-based wavefront sensing architectures that can directly estimate Zernike coefficients of aberrated wavefronts from a single intensity image by using a convolutional neural network. We also demonstrated that the proposed deep learning wavefront sensor can be trained to estimate wavefront aberrations stimulated by a point source and even extended sources.

We present an all-optical neuron that utilizes a logistic sigmoid activation function, using a Wavelength-Division Multiplexing (WDM) input & weighting scheme. The activation function is realized by means of a deeply-saturated differentially-biased Semiconductor Optical Amplifier-Mach-Zehnder Interferometer (SOA-MZI) followed by a SOA-Cross-Gain-Modulation (XGM) gate. Its transfer function is both experimentally and theoretically analyzed, showing excellent agreement between theory and experiment and an almost perfect fitting with a logistic sigmoid function. The optical sigmoid transfer function is then exploited in the experimental demonstration of a photonic neuron, demonstrating successful thresholding over a 100psec-long pulse sequence with 4 different weighted-and-summed power levels.

Si design, enabling 2.5x faster switching compared to the metal heater. Doped-Si-based heaters are therefore the most practical and efficient on standard SOI. In addition, to optimize the layout density of highly integrated dies, we experimentally characterize internal and external thermal crosstalk for tunable Mach-Zehnder interferometers (MZIs) based on both heater designs for various power, distances, and etching patterns. Deep trenches are the best structures not involving special fabrication techniques to mitigate heat leakage affecting phase-sensitive devices close to heaters. Given the numerous applications of thermal tuners, this work is relevant to almost all silicon photonics designers.

Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and confinement loss for a solid-core PCF. These machine learning algorithms based on artificial neural networks are able to make accurate predictions of above-mentioned optical properties for usual parameter space of wavelength ranging from 0.5-1.8 µm, pitch from 0.8-2.0 µm, diameter by pitch from 0.6-0.9 and number of rings as 4 or 5 in a silica solid-core PCF. We demonstrate the use of simple and fast-training feed-forward artificial neural networks that predicts the output for unknown device parameters faster than conventional numerical simulation techniques. Computation runtimes required with neural networks (for training and testing) and Lumerical MODE solutions are also compared.

In this paper, we numerically investigate various hollow-core anti-resonant (HC-AR) fibers towards low propagation and bend loss with effectively single-mode operation in the telecommunications window. We demonstrate how the propagation loss and higher-order mode modal contents are strongly influenced by the geometrical structure and the number of the anti-resonant cladding tubes. We found that 5-tube nested HC-AR fiber has a wider anti-resonant band, lower loss, and larger higher-order mode extinction ratio than designs with 6 or more anti-resonant tubes. A loss ratio between the higher-order modes and fundamental mode, as high as 12,000, is obtained in a 5-tube nested HC-AR fiber. To the best of our knowledge, this is the largest higher-order mode extinction ratio demonstrated in a hollow-core fiber at 1.55 μm. In addition, we propose a modified 5-tube nested HC-AR fiber, with propagation loss below 1 dB/km from 1330 to 1660 nm. This fiber also has a small bend loss of ~15 dB/km for a bend radius of 1 cm.

Observing the various anatomical and functional information that spans many spatiotemporal scales with high resolution provides deep understandings of the fundamentals of biological systems. Light-field microscopy (LFM) has recently emerged as a scanning-free, scalable method that allows for high-speed, volumetric imaging ranging from single-cell specimens to the mammalian brain. However, the prohibitive reconstruction artifacts and severe computational cost have thus far limited broader applications of LFM. To address the challenge, in this work, we report Fourier LFM (FLFM), a system that processes the light-field information through the Fourier domain. We established a complete theoretical and algorithmic framework that describes light propagation, image formation and system characterization of FLFM. Compared with conventional LFM, FLFM fundamentally mitigates the artifacts, allowing high-resolution imaging across a two- to three-fold extended depth. In addition, the system substantially reduces the reconstruction time by roughly two orders of magnitude. FLFM was validated by…

of only 0.35-1.4 V across 200 nm, low residual amplitude modulation of only 0.1-0.15 dB for 2π phase shift, extremely low static power consumption (<3 nW), and high speed (> 1 GHz). All of these factors make them ideal for next-generation LiDAR systems that employ optical phased arrays.

. In this way, we can computationally discover completely unexpected metasurface designs for challenging multi-frequency, multi-angle problems, including designs for fully coupled multi-layer structures with arbitrary per-layer patterns. Unlike typical metasurface designs based on subwavelength unit cells, our approach can discover both sub- and supra-wavelength patterns and can obtain both the near and far fields.

For the benefit of designing scalable, fault resistant optical neural networks (ONNs), we investigate the effects architectural designs have on the ONNs' robustness to imprecise components. We train two ONNs - one with a more tunable design (GridNet) and one with better fault tolerance (FFTNet) - to classify handwritten digits. When simulated without any imperfections, GridNet yields a better accuracy (∼98%) than FFTNet (∼95%). However, under a small amount of error in their photonic components, the more fault tolerant FFTNet overtakes GridNet. We further provide thorough quantitative and qualitative analyses of ONNs' sensitivity to varying levels and types of imprecisions. Our results offer guidelines for the principled design of fault-tolerant ONNs as well as a foundation for further research.

In this work, the size-dependent effect for InGaN/GaN-based blue micro-light emitting diodes (µLEDs) is numerically investigated. Our results show that the external quantum efficiency (EQE) and the optical power density drop drastically as the device size decreases when sidewall defects are induced. The observations are owing to the higher surface-to-volume ratio for small µLEDs, which makes the Shockley-Read-Hall (SRH) non-radiative recombination at the sidewall defects not negligible. The sidewall defects also severely affect the injection capability for electrons and holes, such that the electrons and holes are captured by sidewall defects for the SRH recombination. Thus, the poor carrier injection shall be deemed as a challenge for achieving high-brightness µLEDs. Our studies also indicate that the sidewall defects form current leakage channels, and this is reflected by the current density-voltage characteristics. However, the improved current spreading effect can be obtained when the chip size decreases. The better current spreading effect takes account for the reduced forward…

. Constructing an OAM multiplexing communication link, the bit-error-rate (BER) of the transmitted signals in each OAM channel is reduced by almost two orders of magnitude under moderate-strong turbulence, and the demodulated constellation diagram also converges well after compensated by the CNN model.

We present a 1024-element near-infrared imaging array of superconducting nanowire single photon detectors (SNSPDs) using a 32×32 row-column multiplexing architecture. The array has an active area of 0.96 × 0.96 mm, making it the largest SNSPD array reported to date in terms of both active area and pixel count. Using a 64-channel time-tagging readout, we have characterized the array's yield, efficiency, and timing resolution. Large arrays of SNSPDs are desirable for applications such as imaging, spectroscopy, or particle detection.

Mask-based lensless imagers are smaller and lighter than traditional lensed cameras. In these imagers, the sensor does not directly record an image of the scene; rather, a computational algorithm reconstructs it. Typically, mask-based lensless imagers use a model-based reconstruction approach that suffers from long compute times and a heavy reliance on both system calibration and heuristically chosen denoisers. In this work, we address these limitations using a bounded-compute, trainable neural network to reconstruct the image. We leverage our knowledge of the physical system by unrolling a traditional model-based optimization algorithm, whose parameters we optimize using experimentally gathered ground-truth data. Optionally, images produced by the unrolled network are then fed into a jointly-trained denoiser. As compared to traditional methods, our architecture achieves better perceptual image quality and runs 20× faster, enabling interactive previewing of the scene. We explore a spectrum between model-based and deep learning methods, showing the benefits of using an intermediate…

) delivers 104 fs pulses with 42.5 nm of bandwidth. Our results contribute to the growing body of work studying the nonlinear optical properties of MXene that underpin new opportunities for ultrafast photonic technology.

Up to now, the measurement of radio-frequency (RF) electric field achieved using the electromagnetically-induced transparency (EIT) of Rydberg atoms has proved to be of high-sensitivity and shows a potential to produce a promising atomic RF receiver at resonance between two chosen Rydberg states. In this paper, we study the extension of the feasibility of digital communication via this quantum-based antenna over a continuously tunable RF-carrier at off-resonance. Our experiment shows that the digital communication at a rate of 500 kbps can be performed reliably within a tunable bandwidth of 200 MHz near a 10.22 GHz carrier. Outside of this range, the bit error rate (BER) increases, rising to, for example, 15% at an RF-detuning of ±150 MHz. In the measurement, the time-varying RF field is retrieved by detecting the optical power of the probe laser at the center frequency of RF-induced symmetric or asymmetric Autler-Townes splitting in EIT. Prior to the digital test, we studied the RF-reception quality as a function of various parameters including the RF detuning and found that a…

Existing for almost four decades, liquid crystal on Silicon (LCOS) technology is rapidly growing into photonic applications. We review the basics of the technology, from the wafer to the driving solutions, the progress over the last decade and the future outlook. Furthermore we review the most exciting industrial and scientific applications of the LCOS technology.

Two-dimensional phase unwrapping algorithms are widely used in optical metrology and measurements. The high noise from interference measurements, however, often leads to the failure of conventional phase unwrapping algorithms. In this paper, we propose a deep convolutional neural network (DCNN) based method to perform rapid and robust two-dimensional phase unwrapping. In our approach, we employ a DCNN architecture, DeepLabV3+, with noise suppression and strong feature representation capabilities. The employed DCNN is first used to perform semantic segmentation to obtain the segmentation result of the wrapped phase map. We then combine the wrapped phase map with the segmentation result to generate the unwrapped phase. We benchmarked our results by comparing them with well-established methods. The reported approach out-performed the conventional path-dependent and path-independent algorithms. We also tested the robustness of the reported approach using interference measurements from optical metrology setups. Our results, again, clearly out-performed the conventional phase unwrap…

We introduce a deep-learning technique to perform complete mode decomposition for few-mode optical fibers for the first time. Our goal is to learn a fast and accurate mapping from near-field beam patterns to the complete mode coefficients, including both modal amplitudes and phases. We train the convolutional neural network with simulated beam patterns and evaluate the network on both the simulated beam data and the real beam data. In simulated beam data testing, the correlation between the reconstructed and the ideal beam patterns can achieve 0.9993 and 0.995 for 3-mode case and 5-mode case, respectively. While in the real 3-mode beam data testing, the average correlation is 0.9912 and the mode decomposition can be potentially performed at 33 Hz frequency on a graphic processing unit, indicating real-time processing ability. The quantitative evaluations demonstrate the superiority of our deep learning-based approach.

conversion efficiency for second-harmonic generation, pumped around 1540 nm. In addition, we measure broadband sum-frequency generation across multiple telecom bands, from 1460 to 1620 nm. As an immediate application of the devices, we use pulses of picojoule-level energy to demonstrate second-harmonic generation with over 10% conversion in a 0.6-mm-long waveguide. Our ultracompact and highly efficient devices address growing demands in integrated-photonic frequency conversion, frequency metrology, atomic physics, and quantum optics, while offering a coherent link between the telecom and visible bands.

3D meso scale structures that can reach up to centimeters in overall size but retain micro- or nano-features, proved to be promising in various science fields ranging from micro-mechanical metamaterials to photonics and bio-medical scaffolds. In this work, we present synchronization of the linear and galvanometric scanners for efficient femtosecond 3D optical printing of objects at the meso-scale (from sub-μm to sub-cm spanning five orders of magnitude). In such configuration, the linear stages provide stitch-free structuring at nearly limitless (up to tens-of-cm) working area, while galvo-scanners allow to achieve translation velocities in the range of mm/s-cm/s without sacrificing nano-scale positioning accuracy and preserving the undistorted shape of the final print. The principle behind this approach is demonstrated, proving its inherent advantages in comparison to separate use of only linear stages or scanners. The printing rate is calculated in terms of voxels/s, showcasing the capability to maintain an optimal feature size while increasing throughput. Full capabilities of…

We investigate the depth imaging of objects through various densities of different obscurants (water fog, glycol-based vapor, and incendiary smoke) using a time-correlated single-photon detection system which had an operating wavelength of 1550 nm and an average optical output power of approximately 1.5 mW. It consisted of a monostatic scanning transceiver unit used in conjunction with a picosecond laser source and an individual Peltier-cooled InGaAs/InP single-photon avalanche diode (SPAD) detector. We acquired depth and intensity data of targets imaged through distances of up to 24 meters for the different obscurants. We compare several statistical algorithms which reconstruct both the depth and intensity images for short data acquisition times, including very low signal returns in the photon-starved regime.

A novel parallel structured fiber-optic Fabry-Perot interferometer (FPI) based on Vernier-effect is theoretically proposed and experimentally demonstrated for ultrasensitive strain measurement. This proposed sensor consists of open-cavity and closed-cavity fiber-optic FPI, both of which are connected in parallel via a 3 dB coupler. The open-cavity is implemented for sensing, while the closed-cavity for reference. Experimental results show that the proposed parallel structured fiber-optic FPI can provide an ultra-high strain sensitivity of -43.2 pm/με, which is 4.6 times higher than that of a single open-cavity FPI. Furthermore, the sensor is simple in fabrication, robust in structure, and stable in measurement. Finally, the parallel structured fiber-optic FPI scheme proposed in this paper can also be applied to other sensing field, and provide a new perspective idea for high sensitivity sensing.

We propose a novel simple patterned monolayer graphene metamaterial structure based on tunable terahertz plasmon-induced transparency (PIT). Destructive interference in this structure causes pronounced PIT phenomenon, and the PIT response can be dynamically controlled by voltage since the existence of continuous graphene bands in the structural design. The theoretical transmission of this structure is calculated by coupled mode theory (CMT), and the results are highly consistent with the simulation curve. After that, the influence of the graphene mobility on the PIT response and absorption characteristics is researched. It is found that the absorption efficiency of our designed structure can reach up to 50%, meaning the structure is competent to prominent terahertz absorber. Moreover, the slow-light performance of this structure is discussed via analyzing the group refractive index and phase shift. It shows that the structure possesses a broad group refractive index band with ultra-high value, and the value is up to 382. This work will diversify the designs for versatile tunable…

-based photonic integrated circuits for energy-efficient nonlinear photonics and quantum optics.

Recently, a novel machine learning model has emerged in the field of reinforcement learning known as deep Q-learning. This model is capable of finding the best possible solution in systems consisting of millions of choices, without ever experiencing it before, and has been used to beat the best human minds at complex games such as, Go and chess, which both have a huge number of possible decisions and outcomes for each move. With a human-level intelligence, it has solved the problems that no other machine learning model has done before. Here, we show the steps needed for implementing this model to an optical problem. We investigate the colour generation by dielectric nanostructures and show that this model can find geometrical properties that can generate much purer red, green and blue colours compared to previously reported results. The model found these results in 9000 steps from a possible 34.5 million solutions. This technique can easily be extended to predict and optimise the design parameters for other optical structures.

Under complex scattering conditions, it is very difficult to capture clear object images hidden behind the media by modelling the inverse problem. With regard to dynamic scattering media, the challenge increases. For solving the inverse problem, we propose a new class-specific image reconstruction algorithm. The method based on deep learning classifies blurred scattering images according to scattering conditions and then recovers to clear images hidden behind the media. The deep learning network is used to learn the mapping relationship between the object and the scattering image rather than characterizing the scattering media explicitly or parametrically. 25000 scattering images are obtained under five sets of dynamic scattering condition to verify the feasibility of the proposed method. In addition, the generalizability of the method has been verified successfully. Compared with common CNN method, it's confirmed that our algorithm has better performance in reconstructing higher-quality images. Furthermore, for a given scattering image with unknown scattering condition, the closest…

In 3D optical metrology, single-shot structured light profilometry techniques have inherent advantages over their multi-shot counterparts in terms of measurement speed, optical setup simplicity, and robustness to motion artifacts. In this paper, we present a new approach to extract height information from single deformed fringe patterns, based entirely on deep learning. By training a fully convolutional neural network on a large set of simulated height maps with corresponding deformed fringe patterns, we demonstrate the ability of the network to obtain full-field height information from previously unseen fringe patterns with high accuracy. As an added benefit, intermediate data processing steps such as background masking, noise reduction and phase unwrapping that are otherwise required in classic demodulation strategies, can be learned directly by the network as part of its mapping function.

/Vs. In addition, the group index can be as high as 328. Thus, our work can pave new way for developing excellent slow-light and light absorption functional devices.

silicon footprint of a commercial foundry silicon photonics process. The optical modulator consumes 2.56 mW for 180° phase modulation over 100-nm optical bandwidth while achieving 1.23-dB optical loss without air-gap trench or silicon undercut post-processing. Geometrical design optimization, at the core of this demonstration, is applicable to the realization of compact thermo-optic devices for large-scale programmable photonic integrated systems, with a potential to reduce power consumption roughly by an order of magnitude without sacrificing scalability and optical modulation bandwidth.

Sidewall emission of a micro-scale light emitting diode (micro-LED) improves the light extraction efficiency, but it causes mismatched angular distributions between AlGaInP-based red micro-LED and InGaN-based blue/green counterparts due to material difference. As a result, color shift of RGB micro-LED displays may become visually noticeable. To address this issue, we first analyze the angular distributions of RGB micro-LEDs and obtain good agreement between simulation and experiment. Next, we propose a device structure with top black matrix and taper angle in micro-LEDs, which greatly suppresses the color shift while keeping a reasonably high light extraction efficiency.

The interferometry technique is commonly used to obtain the phase information of an object in optical metrology. The obtained wrapped phase is subject to a 2π ambiguity. To remove the ambiguity and obtain the correct phase, phase unwrapping is essential. Conventional phase unwrapping approaches are time-consuming and noise sensitive. To address those issues, we propose a new approach, where we transfer the task of phase unwrapping into a multi-class classification problem and introduce an efficient segmentation network to identify classes. Moreover, a noise-to-noise denoised network is integrated to preprocess noisy wrapped phase. We have demonstrated the proposed method with simulated data and in a real interferometric system.

We present an ultra-broadband perfect absorber composed of metal-insulator composite multilayer (MICM) stacks by placing the insulator-metal-insulator (IMI) grating on the metal-insulator-metal (MIM) film stacks. The absorber shows over 90% absorption spanning between 570 nm and 3539 nm, with an average absorption of 97% under normal incidence. The ultra-broadband perfect absorption characteristics are achieved by the synergy of guided mode resonances (GMRs), localized surface plasmons (LSPs), propagating surface plasmons (PSPs), and cavity modes. The polarization insensitivity is demonstrated by analyzing the absorption performance over arbitrary polarization angles. The ultra-broadband absorption remains more than 80% over a wide incident angle up to 50°, for both transverse electric (TE) and transverse magnetic (TM) modes. The ultra-broadband perfect absorber has tremendous potential for various applications, such as solar thermal energy harvesting, thermoelectrics, and imaging.

, achieving the highest laser intensity ever reached.

A demand for division of focal plane (DoFP) polarization imaging technology grows rapidly as nanofabrication technologies become mature. For real-time polarization imaging, a DoFP polarimeter often trades off its spatial resolution, which may cause instantaneous field of view (IFoV) errors. To deal with such problems, interpolation methods are often used to fill the missing polarization information. This paper presents an interpolation technique using Newton's polynomial for DoFP polarimeter demosaicking. The interpolation is performed in the polarization difference domain with the interpolation error taken into consideration. The proposed method uses an edge classifier based on polarization difference and a fusion scheme to recover more accurate boundary features. Experiments using both synthetic and real DoFP images in visible and long-wave infrared spectrum demonstrate that the proposed interpolation method outperforms the state-of-the-art techniques quantitatively as well as visually to reduce nonconformities caused by high-frequency energy.

We present passive, visible light silicon nitride waveguides fabricated on ≈ 100 µm thick 200 mm silicon wafers using deep ultraviolet lithography. The best-case propagation losses of single-mode waveguides were ≤ 2.8 dB/cm and ≤ 1.9 dB/cm over continuous wavelength ranges of 466-550 nm and 552-648 nm, respectively. In-plane waveguide crossings and multimode interference power splitters are also demonstrated. Using this platform, we realize a proof-of-concept implantable neurophotonic probe for optogenetic stimulation of rodent brains. The probe has grating coupler emitters defined on a 4 mm long, 92 µm thick shank and operates over a wide wavelength range of 430-645 nm covering the excitation spectra of multiple opsins and fluorophores used for brain stimulation and imaging.

This paper reports on large field-of-regard, high-efficiency, and large aperture active optical phased arrays (OPAs) for optical beam steering in LIDAR systems. The fabricated 5 mm-long silicon photonic OPA with a 1.3 μm waveguide pitch achieved adjacent waveguide crosstalk below -12dB. A relatively large and uniform emission aperture has been achieved with a low-contrast silicon nitride assisted grating (~20 dB/cm) whose emission profile can be further optimized using an apodized design. The fabricated silicon-photonic OPA demonstrated > 40° lateral beam steering with no sidelobes in a ± 33° field-of-regard and 3.3° longitudinal beam steering via wavelength tuning by 20 nm centered at 1550 nm. We have fully integrated the silicon photonic OPA device with electronic controls and successfully demonstrated 2-dimensional coherent optical beam steering of pre-planned far-field patterns. Future improvements include placement of a distributed Bragg reflector (DBR) underneath the grating emitter in order to achieve nearly a factor of two improvement in emission efficiency.

We present a tunable metamodulator to work at terahertz frequencies by employing the dependency of toroidal dipolar resonance on the conductivity of vanadium dioxide. Numerical results show that toroidal dipolar resonance in the proposed planar structure can be observed around 0.288 THz in transmission spectrum. From the distribution of the anti-phase current flowing in the symmetric split ring resonator, the formation of toroidal dipole is validated. Our design may have potential applications in advanced terahertz devices, such as filter, plasmonic sensor, and fast switch.

In this work, we present two-dimensional beam steering in the near-infrared using a SiN integrated circuit, containing optical phased arrays. Beam steering was achieved over a range of 17.6° × 3°, at a fixed wavelength of 905 nm. The first dimension was steered via phase differences between the optical phased array channels. The second dimension was accessed by actively switching between various optical phased array sub-devices containing output diffraction gratings with different periods. The characterisation was performed on a wafer-level test station.

Three-dimensional imaging in underwater environments was investigated using a picosecond resolution silicon single-photon avalanche diode (SPAD) detector array fabricated in complementary metal-oxide semiconductor (CMOS) technology. Each detector in the 192 × 128 SPAD array had an individual time-to-digital converter allowing rapid, simultaneous acquisition of data for the entire array using the time-correlated single-photon counting approach. A picosecond pulsed laser diode source operating at a wavelength of 670 nm was used to illuminate the underwater scenes, emitting an average optical power up to 8 mW. Both stationary and moving targets were imaged under a variety of underwater scattering conditions. The acquisition of depth and intensity videos of moving targets was demonstrated in dark laboratory conditions through scattering water, equivalent to having up to 6.7 attenuation lengths between the transceiver and target. Data were analyzed using a pixel-wise approach, as well as an image processing algorithm based on a median filter and polynomial approximation.

The measuring technique combining a phase-shifting algorithm and Gray-code light has been widely used in three-dimensional (3D) shape measurement for static scenes because of its high robustness and anti-noise ability. However, in the high-speed measurement, phase unwrapping errors occur easily on the boundaries of adjacent Gray-code words because of the defocus of the projector, the motion of the objects and the non-uniform reflectivity of the surface. To overcome this challenge, a high-speed 3D shape measurement method based on shifting Gray-code light has been proposed in this paper. Firstly, the average intensity of three captured phase-shifting fringe images are used as a pixel-wise threshold to binarize the Gray codes and to eliminate most phase unwrapping errors caused by the non-uniform reflectivity, ambient light variations, and the defocus of projector. Then, the shifting Gray-code (SGC) coding strategy is proposed to avoid the remaining errors of phase unwrapping on the edge of the code words. In this strategy, no additional patterns are projected, and two sets of…

Optical coherence tomography (OCT) has become a very promising diagnostic method in clinical practice, especially for ophthalmic diseases. However, speckle noise and low sampling rates have intensively reduced the quality of OCT images, which prevents the development of OCT-assisted diagnosis. Therefore, we propose a generative adversarial network-based approach (named SDSR-OCT) to simultaneously denoise and super-resolve OCT images. Moreover, we trained three different super-resolution models with different upscale factors (2× , 4× and 8×) to adapt to the corresponding downsampling rates. We also quantitatively and qualitatively compared our proposed method with some well-known algorithms. The experimental results show that our approach can effectively suppress speckle noise and can super-resolve OCT images at different scales.

J/MAC excluding laser power when performing MNIST classification in a 2 hidden layer feed-forward photonic neural network.

Consumer cameras, particularly onboard smartphones and UAVs, are now commonly used as scientific instruments. However, their data processing pipelines are not optimized for quantitative radiometry and their calibration is more complex than that of scientific cameras. The lack of a standardized calibration methodology limits the interoperability between devices and, in the ever-changing market, ultimately the lifespan of projects using them. We present a standardized methodology and database (SPECTACLE) for spectral and radiometric calibrations of consumer cameras, including linearity, bias variations, read-out noise, dark current, ISO speed and gain, flat-field, and RGB spectral response. This includes golden standard ground-truth methods and do-it-yourself methods suitable for non-experts. Applying this methodology to seven popular cameras, we found high linearity in RAW but not JPEG data, inter-pixel gain variations >400% correlated with large-scale bias and read-out noise patterns, non-trivial ISO speed normalization functions, flat-field correction factors varying by up to 2.79…

Object identification in highly turbid optical media depends mainly on the quality of collected images. Underwater images acquired in a turbid environment are generally of very poor quality. Attenuation and backscattering of light by water, by materials dissolved in the water, and by particulate material are the main causes of the degradation of underwater images. It is therefore essential to improve the quality of such images to facilitate object identification. The focus of this paper is to report the principle and validation of a fast and effective method of improving the quality of underwater images. On the one hand, this method uses a polarimetric imaging optical system to reduce the effect of diffusion on the image acquisition. On the other hand, it is based on an optimized version of the dark channel prior (DCP) method that has received a great deal of attention for image dehazing. Results derived from images obtained in a controlled laboratory water tank environment with different turbidity conditions and images from tests using the proposed method at sea demonstrate an…

Terahertz integrated platforms with high efficiency are crucial in a broad range of applications including terahertz communications, radar, imaging and sensing. One key enabling technology is wideband interconnection. This work proposes substrate-less all-dielectric waveguides defined by an effective medium with a subwavelength hole array. These self-supporting structures are built solely into a single silicon wafer to minimize significant absorption in metals and dielectrics at terahertz frequencies. In a stark contrast to photonic crystal waveguides, the guiding mechanism is not based on a photonic bandgap but total internal reflections The waveguides are discussed in the context of terahertz communications that imposes stringent demands on performance. Experimental results show that the realized waveguides can cover the entire 260-400 GHz with single dominant modes in both orthogonal polarizations and an average measured attenuation around 0.05 dB/cm. Limited by the measurement setup, the maximum error-free data rate up to 30 Gbit/s is experimentally achieved at 335 GHz on a 3-cm…

In this work, we report the design of topological filter and all-optical logic gates based on two-dimensional photonic crystals with robust edge states. All major logic gates, including OR, AND, NOT, NOR, XOR, XNOR, and NAND, are suitably designed by using the linear interference approach. Moreover, numerical simulations show that our designed all-optical logic devices can always work well even if significant disorders exist. It is expected that such robust and compact logic devices have potential applications in future photonic integrated circuits.

detection is likely to be a highly effective tool in practical, high-sensitivity, ultra-broadband applications.

microresonators fabricated using a subtractive processing method. These results enhance the possibilities for co-integration of microcombs with high-performance photonic devices, such as narrow-linewidth external-cavity diode lasers, ultra-narrow filters and demultiplexers.

The binary defocusing technique has been widely used in high-speed three-dimensional (3D) shape measurement because it breaks the bottlenecks in high-speed fringe projection and the projector's nonlinear response. However, it is challenging for this method to realize a two- or multi-frequency phase-shifting algorithm because it is difficult to simultaneously generate high-quality sinusoidal fringe patterns with different periods under the same defocusing degree. To bypass this challenge, we proposed a high-speed 3D shape measurement technique for dynamic scenes based on cyclic complementary Gray-code (CCGC) patterns. In this proposed method, the projected phase-shifting sinusoidal fringes kept one same frequency, which is beneficial to ensure the optimum defocusing degree for binary dithering technique. The wrapped phase can be calculated by phase-shifting algorithm and unwrapped with the aid of complementary Gray-code (CGC) patterns in a simple and robust way. Then, the cyclic coding strategy further extends the unambiguous phase measurement range and improves the measurement…

The development of large-scale optical quantum information processing circuits ground on the stability and reconfigurability enabled by integrated photonics. We demonstrate a reconfigurable 8×8 integrated linear optical network based on silicon nitride waveguides for quantum information processing. Our processor implements a novel optical architecture enabling any arbitrary linear transformation and constitutes the largest programmable circuit reported so far on this platform. We validate a variety of photonic quantum information processing primitives, in the form of Hong-Ou-Mandel interference, bosonic coalescence/anti-coalescence and high-dimensional single-photon quantum gates. We achieve fidelities that clearly demonstrate the promising future for large-scale photonic quantum information processing using low-loss silicon nitride.

Deep learning has become an extremely effective tool for image classification and image restoration problems. Here, we apply deep learning to microscopy and demonstrate how neural networks can exploit the chromatic dependence of the point-spread function to classify the colors of single emitters imaged on a grayscale camera. While existing localization microscopy methods for spectral classification require additional optical elements in the emission path, e.g., spectral filters, prisms, or phase masks, our neural net correctly identifies static and mobile emitters with high efficiency using a standard, unmodified single-channel configuration. Furthermore, we show how deep learning can be used to design new phase-modulating elements that, when implemented into the imaging path, result in further improved color differentiation between species, including simultaneously differentiating four species in a single image.

In this paper, we propose a high-speed 3D shape measurement technique based on the optimized composite fringe patterns and stereo-assisted structured light system. Stereo phase unwrapping, as a new-fashioned method for absolute phase retrieval based on the multi-view geometric constraints, can eliminate the phase ambiguities and obtain a continuous phase map without projecting any additional patterns. However, in order to ensure the stability of phase unwrapping, the period of fringe is generally around 20, which limits the accuracy of 3D measurement. To solve this problem, we develop an optimized method for designing the composite pattern, in which the speckle pattern is embedded into the conventional 4-step phase-shifting fringe patterns without compromising the fringe modulation, and thus the phase measurement accuracy. We also present a simple and effective evaluation criterion for the correlation quality of the designed speckle pattern in order to improve the matching accuracy significantly. When the embedded speckle pattern is demodulated, the periodic ambiguities in the…

Multimode fibers (MMF) are remarkable high-capacity information channels. However, the MMF transmission is highly sensitive to external perturbations and environmental changes. Here, we show the successful binary image transmission using deep learning through a single MMF subject to dynamic shape variations. As a proof-of-concept experiment, we find that a convolutional neural network has excellent generalization capability with various MMF transmission states to accurately predict unknown information at the other end of the MMF at any of these states. Our results demonstrate that deep learning is a promising solution to address the high variability and randomness challenge of MMF based information channels. This deep-learning approach is the starting point of developing future high-capacity MMF optical systems and devices and is applicable to optical systems concerning other diffusing media.

In this work, we investigate the evanescent field sensing mechanism provided by an all-dielectric metasurface supporting bound states in the continuum (BICs). The metasurface is based on a transparent photonic crystal with subwavelength thickness. The BIC electromagnetic field is localized along the direction normal to the photonic crystal nanoscale-thin slab (PhCS) because of a topology-induced confinement, exponentially decaying in the material to detect. On the other hand, it is totally delocalized in the PhCS plane, which favors versatile and multiplexing sensing schemes. Liquids with different refractive indices, ranging from 1.33 to 1.45, are infiltrated in a microfluidic chamber bonded to the sensing dielectric metasurface. We observe an experimental exponential sensitivity leading to differential values as large as 226 nm/RIU with excellent FOM. This behavior is explained in terms of the physical superposition of the field with the material under investigation and supported by a thorough numerical analysis. The mechanism is then translated to the case of molecular adsorption…

Optical switches based on dielectric nanostructures are highly desired at present. To enhance the wavelength-selective light absorption, and achieve an absorption-induced switching effect, here we propose a graphene-based metamaterial absorber that consists of a dielectric grating, a graphene monolayer, and a photonic crystal. Numerical results reveal that the dual-band absorption with an ultranarrow spectrum of the system is enhanced greatly due to the critical coupling, which is enabled by the combined effects of guided mode resonances and photonic band gap. The quality factor of the absorber can achieve a high value (>500), which is basically consistent with the coupled mode theory. Slow light emerges within the absorption window. In addition, electrostatic gating of graphene in the proposed structure provides dynamic control of the absorption due to the change of the chemical potential of the graphene, resulting in an optional multichannel switching effect. Unlike other one-dimensional devices, these effects can be applied to another polarization without changing the structure…

Spatial light modulators (SLMs) based on liquid crystals are widely used for wavefront shaping. Their large number of pixels allows one to create complex wavefronts. The crosstalk between neighboring pixels, also known as fringing field effect, however, can lead to strong deviations. The realized wavefront may deviate significantly from the prediction based on the idealized assumption that the response across a pixel is uniform and independent of its neighbors. Detailed numerical simulations of the SLM response based on a full 3D physical model accurately match the measured response and properly model the pixel crosstalk. The full model is then used to validate a simplified model that enables much faster crosstalk evaluation and pattern optimization beyond standard performance. General conclusions on how to minimize crosstalk in liquid crystal on silicon (LCoS) SLM systems are derived, as well as a readily accessible estimation of the amount of fringing in a given SLM.

The magnetostrictive effect provides an opportunity for exploring fundamental phenomena related to the phonon-magnon interaction. Here we show a tunable slow light in a cavity magnetomechanical system consisting of photon, magnon and phonon modes with a nonlinear phonon-magnon interaction, which originates from magnetostrictive forces. For a strong photon-magnon coupling strength, we can observe a transparency (absorption) window for the probe by placing a strong control field on the red (blue) detuned sideband of the hybridized modes, which are comprised of photons and magnons. In this work, we mainly show the characteristic changes in dispersion in the range of the transparency window. The value of group delay can be continuously adjusted by using different frequencies of magnon, which are determined by the external bias magnetic field and therefore can be conveniently tuned in a broad range. Both the intensity and the frequency of the control field have an influence on the transformation from subluminal to superluminal propagation and vice versa. Furthermore, one may achieve…

Experimental observations of spatiotemporal mode-locked multiple-soliton, including harmonic mode locking and multiple pulses, in multimode fiber (MMF) lasers are reported. Numerical simulations are conducted to investigate the nonlinear dynamics of multi-pulsing. The influences of cavity parameters on the spatiotemporal outputs are analyzed by simulations, which agree with the experimental observations qualitatively. This work would contribute to understanding the complex spatiotemporal nonlinear dynamics in MMF lasers.

heterostructure are provided. By employing the prepared SA, a stable and passively erbium-doped fiber laser is implemented. The generated pulse duration of 154 fs is certified to be the shortest among all fiber lasers based on transition mental dichalcogenides. Results in this paper provide the new direction for the fabrication of ultrafast photon modulation devices.

. Compared with the traditional finite impulse response (FIR) based equalizer, the Q factor performance is improved by 1.2dB and the transmission distance is increased by one-third in the same experimental hardware setups. Compared with traditional nonlinear hybrid Volterra equalizers, the significant complexity and system performance advantages of using a LSTM-based equalizer is demonstrated. To the best of our knowledge, this is the first demonstration of using deep LSTM in VLC systems.

In this work, we present a detailed analysis of individual loss mechanisms in silicon nitride partial Euler bends at a wavelength of 850 nm. This structure optimizes the transmission through small radii optical waveguide bends. The partial Euler bend geometry balances losses arising from the transition from the straight to the bend waveguide mode and radiative losses of the bend waveguide mode. Numerical analyses are presented for 45-degree bends commonly employed in S-bend configurations to create lateral offsets, as well as 90- and 180-degree bends. Additionally, 90-degree partial Euler bends were fabricated on a silicon nitride photonic platform to experimentally complement the theoretical findings. The optimized waveguide bends allow for a reduced effective radius without increasing the total bend loss and, thus, enable a higher component density in photonic integrated circuits.

Dual-comb spectroscopy is a rapidly developing spectroscopic technique that does not require any opto-mechanical moving parts and enables broadband and high-resolution measurements with microsecond time resolution. However, for high sensitivity measurements and extended averaging times, high mutual coherence of the comb-sources is essential. To date, most dual-comb systems employ coherent averaging schemes that require additional electro-optical components, which increase system complexity and cost. More recently, computational phase correction approaches that enables coherent averaging of spectra generated by free-running systems have gained increasing interest. Here, we propose such an all-computational solution that is compatible with real-time data acquisition architectures for free-running systems. The efficacy of our coherent averaging algorithm is demonstrated using dual-comb spectrometers based on quantum cascade lasers, interband cascade lasers, mode-locked lasers, and optically-pumped microresonators.

Generation of octave-spanning spectrum that spans from 570 nm to 1300 nm utilizing 1030 nm 170 fs pulses from a Yb:KGW laser and a two-stage multiple-plate arrangement is demonstrated. 3.21 fs sub-single-cycle pulses are obtained after dispersion compensation. The high compression ratio of more than 50 times is achieved for two scenarios with widely different parameters including high input peak power at 1 kHz repetition rate and modest peak power at a high repetition rate of 100 kHz. The output pulses have good spatial mode quality and exhibit long-term stability. The achieved compression ratio and flexibility are unprecedented in ultrafast pulse compression to single-cycle regime. The experiments demonstrate that the technique of multiple-plate pulse compression is versatile and applicable for a wide range of laser pulse parameters.

We report high-speed photo detection at two-micron-wavelength achieved by a GeSn/Ge multiple-quantum-well (MQW) p-i-n photodiode, exhibiting a 3-dB bandwidth (f3-dB) above 10 GHz for the first time. The epitaxy of device layer stacks was performed on a standard (001)-oriented 300 mm Si substrate by using reduced pressure chemical vapor deposition (RPCVD). The results showed promise for large-scale manufacturing. To our knowledge, this is also the first photodiodes-on-Si with direct radio-frequency (RF) measurement to quantitatively confirm high-speed functionality with tens of GHz f3-dB at 2 µm, which is considered as a promising candidate for the next data communication window. This work illustrates the potential for using GeSn to extend the utility of Si photonics in 2 µm band integrated optical transceivers for communication applications.

High performance solar-blind photodetectors have been fabricated from diamond wafers. The peak responsivity is 13.0 A/W at 222 nm with a dark current of 0.93 nA under 60 V bias. The rise and decay times of the photodetector are about 1.3 µs and 203 µs, respectively. The responsivity and response time of the device are both among the best values ever reported for diamond-based photodetectors. A solar-blind optical communication system has been constructed by employing the diamond photodetector as a signal receiver for the first time. Benefiting from the high spectral selectivity of the diamond photodetector, the communication system has excellent anti-interference ability. The results reported in this paper may pave the way for the future application of diamond-based solar-blind photodetectors in confidential communications.

The fabrication of hollow core microstructured fibers is significantly more complex than solid fibers due to the necessity to control the hollow microstructure with high precision during the draw. We present the first model that can recreate tubular anti-resonant hollow core fiber draws, and accurately predict the draw parameters and geometry of the fiber. The model was validated against two different experimental fiber draws and very good agreement was found. We identify a dynamic within the draw process that can lead to a premature and irreversible contact between neighboring capillaries inside the hot zone, and describe mitigating strategies. We then use the model to explore the tolerance of the draw process to unavoidable structural variations within the preform, and to study feasibility and limiting phenomena of increasing the produced yield. We discover that the aspect ratio of the capillaries used in the preform has a direct effect on the uniformity of drawn fibers. Starting from high precision preforms the model predicts that it could be possible to draw 100 km of fiber from…

Existing wavefront sensorless (WFS-less) adaptive optics (AO) generally require a search algorithm that takes lots of iterations and measurements to get optimal results. So the latency is a serious problem in the current WFS-less AO system, especially in applications to free-space optics communication. To solve this issue, we propose a deep neural network (DNN)-based aberration correction method. The DNN model can detect the wavefront distortion directly from the intensity images, thereby avoiding time-consuming iterative processes. Since the tip-and-tilt mode of Zernike coefficients are considered, the tip-tilt correction system is not necessarily required in the proposed method. From our simulation results, the proposed method can effectively reduce the computation time and has an impressive improvement of root mean square (RMS) in different turbulence conditions.

Fiber-optic interferometric sensors (FOISs) are widely used in seismometers, hydrophones, and gyroscopes. The arctangent approach of phase-generated carrier (PGC-Arctan) demodulation algorithm is one of the key demodulation techniques in FOISs. The conventional PGC-Arctan demodulation algorithm requires the specific value of the phase modulation depth C to work properly. However, C will variate with laser wavelength, temperature, and humidity in the actual working environment, which leads to harmonic distortion and even demodulation failure. In this paper, a novel PGC demodulation algorithm called self-calibration PGC-Arctan (PGC-Arctan-SC) demodulation algorithm is presented. The proposed algorithm can jointly estimate the accurate C value by the elliptical parameters and C-related components while suppressing nonlinear distortion by ellipse fitting algorithm (EFA). Then C can be calibrated to the specific predefined optimal value by the closed-loop proportion integration differentiation (PID) module. The simulation results are consistent with theoretical analysis, and the…

The accuracy of quantitative absorption spectroscopy depends on correctly distinguishing molecular absorption signatures in a measured transmission spectrum from the varying intensity or 'baseline' of the light source. Baseline correction becomes particularly difficult when the measurement involves complex, broadly absorbing molecules or non-ideal transmission effects such as etalons. We demonstrate a technique that eliminates the need to account for the laser intensity in absorption spectroscopy by converting the measured transmission spectrum of a gas sample to a modified form of the time-domain molecular free induction decay (m-FID) using a cepstral analysis approach developed for audio signal processing. Much of the m-FID signal is temporally separated from and independent of the source intensity, and this portion can be fit directly with a model to determine sample gas properties without correcting for the light source intensity. We validate the new approach in several complex absorption spectroscopy scenarios and discuss its limitations. The technique is applicable to spectra…

A novel electromagnetically induced transparency (EIT) all-dielectric metamaterial is proposed, fabricated, and characterized. The unit cell of the proposed metamaterial comprises of two asymmetric split ring resonators (a-SRRs) positioned with a mirror symmetry. The asymmetric nature of a-SRRs results from the length difference of two arcs. Optical properties of the fabricated metamaterial are investigated numerically using finite difference method, as well as experimentally using a terahertz time-domain spectroscopy. The results confirm that the proposed metamaterial exhibits an EIT transparent window in the frequency range around 0.78THz with a Q-factor of ~75.7 and a time-delay up to ~28.9ps. Theoretical investigations show that EIT effects in our metamaterial are achieved by hybridizing two bright modes in the same unit cell, which are aroused by the excitation of magnetic moments. We also confirm that the proposed metamaterial has great potential for sensing applications with high sensitivity and high figure of merit (FOM), which guarantees potential applications in in situ…

Underwater imaging provides human vision system friendly images; however, it often suffers from severe image degradation. This research developed an underwater polarization imaging model, which considers the water scattering effect, as well as absorption effect. It fully explored the polarization information of the target scene that backscattered light is partially polarized and target light is unpolarized. Then backscattered light is first estimated and removed. The target scene's distance information is derived based upon the polarization information, and then applied to develop a distance-based Lambertian model. This model enables estimation of the intensity loss caused by water absorption and accurate target radiance recovery. Furthermore, real-world experiments show that the developed model handled the underwater image degradation well. In particular, it enables effective color cast correction resulting from water absorption, which traditional imaging methods always ignore.

Two-dimensional materials (2DMs) such as graphene and black phosphorus (BP) have aroused considerable attentions in the past few years. Engineering and enhancing their light-matter interaction is possible due to their support for localized surface plasmon resonances in the infrared regime. In this paper, we have proposed an infrared broadband absorber consisting of multilayer graphene-BP nanoparticles sandwiched between dielectric layers. Benefiting from the properties of graphene and BP, the absorber exhibits both perfect broadband responses and strong anisotropy beyond individual graphene and BP layers. The absorber is tunable with the variation of geometric parameters as well as the doping levels of graphene and BP. The physical insight is revealed by electric field distributions. Furthermore, the angular robustness for incident wave is investigated. The proposed anisotropic omnidirectional broadband absorber may have promising potential applications in various biosensing, communication and imaging systems.

We report on the design, realization, and performance of novel quartz tuning forks (QTFs) optimized for quartz-enhanced photoacoustic spectroscopy (QEPAS). Starting from a QTF geometry designed to provide a fundamental flexural in-plane vibrational mode resonance frequency of ~16 kHz, with a quality factor of 15,000 at atmospheric pressure, two novel geometries have been realized: a QTF with T-shaped prongs and a QTF with prongs having rectangular grooves carved on both surface sides. The QTF with grooves showed the lowest electrical resistance, while the T-shaped prongs QTF provided the best photoacoustic response in terms of signal-to-noise ratio (SNR). When acoustically coupled with a pair of micro-resonator tubes, the T-shaped QTF provides a SNR enhancement of a factor of 60 with respect to the bare QTF, which represents a record value for mid-infrared QEPAS sensing.

A dual-parameter sensor based on a photonic crystal fiber (PCF) concatenated with a fiber Bragg grating (FBG) is proposed and experimentally demonstrated for simultaneous measurement of magnetic field and temperature. Novel magnetic fluids (MF) with different concentration and surfactant are filled in the air holes of PCF. The magnetic field measurement property is only determined by PCF, while the temperature is co-determined by PCF and FBG. Experimental results show that the wavelength shift has a good linearity corresponding with temperature and magnetic field. Temperature and magnetic field sensitivity are proportional to concentration of MF and are affected by different surfactants. For PCF point, when polyethylene glycol is used as a surfactant and the magnetic fluid concentration is equal to 0.15, the highest magnetic field sensitivity is up to 924.63 pm/mT. The proposed sensor has a high sensitivity as well as cross-sensitivity resistance, which provides a promising candidate for dual-channel filtering or multi-parameter measurement applications.

Random Phase Encoding (RPE) techniques for image encryption have drawn increasing attention during the past decades. We demonstrate in this contribution that the RPE-based optical cryptosystems are vulnerable to the chosen-plaintext attack (CPA) with deep learning strategy. A deep neural network (DNN) model is employed and trained to learn the working mechanism of optical cryptosystems, and finally obtaining a certain optimized DNN that acts as a decryption system. Numerical simulations were carried out to verify its feasibility and reliability of not only the classical Double RPE (DRPE) scheme but also the security-enhanced Tripe RPE (TRPE) scheme. The results further indicate the possibility of reconstructing images (plaintexts) outside the original data set.

In an optical vortex (OV) field, the orbital angular momentum (OAM) distribution strongly depends on the intensity, which results in difficulty in OAM independent modulation. To overcome this limitation, we propose a grafted optical vortex (GOV) via spiral phase reconstruction of two or more OVs with different topological charges (TCs). To remain the annular shape of the GOV's intensity, the Dirac δ-function is employed to restrict the energy in a ring. Theoretical analysis and manipulation experiments of polystyrene microspheres show that the magnitude and direction of the GOV's local OAM are controllable by modulating the grafted TCs while the intensity remains constant. The results of this work provide an ingenious method to control the local tangential force on the light ring, which will promote potential applications in optical trapping and rotating micro-particles.

Accurate estimation of ground elevation on a large scale is essential and worthwhile in topography, geomorphology, and ecology. The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) mission, launched in September 2018, offers an opportunity to obtain global elevation data over the earth's surface. This paper aimed to evaluate the performance of ICESat-2 data for ground elevation retrieval. To fulfill this objective, our study first tested the availability of existing noise removal and ground photon identification algorithms on ICESat-2 data. Second, the accuracy of ground elevation data retrieved from ICESat-2 data was validated using airborne LiDAR data. Finally, we explored the influence of various factors (e.g., the signal-to-noise ratio (SNR), slope, vegetation height and vegetation cover) on the estimation accuracy of ground elevation over forest, tundra and bare land areas in interior Alaska. The results indicate that the existing noise removal and ground photon identification algorithms for simulated ICESat-2 data also work well for ICESat-2 data. The overall mean…

The correct numerical calculation of the resonance characteristics and, principally, the quality factor Q of contemporary photonic and plasmonic resonant systems is of utmost importance, since Q defines the bandwidth and affects nonlinear and spontaneous emission processes. Here, we comparatively assess the commonly used methods for calculating Q using spectral simulations with commercially available, general-purpose software. We study the applicability range of these methods through judiciously selected examples covering different material systems and frequency regimes from the far-infrared to the visible. We take care in highlighting the underlying physical and numerical reasons limiting the applicability of each one. Our findings demonstrate that in contemporary systems (plasmonics, 2D materials) Q calculation is not trivial, mainly due to the physical complication of strong material dispersion and light leakage. Our work can act as a reference for the mindful and accurate calculation of the quality factor and can serve as a handbook for its evaluation in guided-wave and…

We propose an autoencoding sequence-based transceiver for communication over dispersive channels with intensity modulation and direct detection (IM/DD), designed as a bidirectional deep recurrent neural network (BRNN). The receiver uses a sliding window technique to allow for efficient data stream estimation. We find that this sliding window BRNN (SBRNN), based on end-to-end deep learning of the communication system, achieves a significant bit-error-rate reduction at all examined distances in comparison to previous block-based autoencoders implemented as feed-forward neural networks (FFNNs), leading to an increase of the transmission distance. We also compare the end-to-end SBRNN with a state-of-the-art IM/DD solution based on two level pulse amplitude modulation with an FFNN receiver, simultaneously processing multiple received symbols and approximating nonlinear Volterra equalization. Our results show that the SBRNN outperforms such systems at both 42 and 84 Gb/s, while training fewer parameters. Our novel SBRNN design aims at tailoring the end-to-end deep learning-based systems…

are obtained at averaging times of 1 s and 2000 s respectively, indicating that the stability of the generated THz wave is limited by the maser reference signal. Moreover, the terahertz signal is successfully used to perform a proof-of-principle demonstration of terahertz imaging of peanuts. Combining the monolithically integrated UTC-PD with an on-chip microcomb, the demonstrated technique could provide a route towards highly stable continuous terahertz wave generation in chip-scale packages for out-of-the-lab applications. In particular, such systems would be useful as compact tools for high-capacity wireless communication, spectroscopy, imaging, remote sensing, and astrophysical applications.

An erratum is presented to correct the sizes of feature maps of Fig. 1(a) in [Opt. Express27, 33504 (2019)10.1364/OE.27.033504].

's material property, the proposed metamaterial absorbers have the potential for strong modulation and switching of broadband THz radiation.

In this work, we show a proof-of-principle benchtop single-photon light detection and ranging (LIDAR) depth imager at 2.3µm, utilizing superconducting nanowire single-photon detectors (SNSPDs). We fabricate and fiber-couple SNSPDs to exhibit enhanced photon counting performance in the mid-infrared. We present characterization results using an optical parametric oscillator source and deploy these detectors in a scanning LIDAR setup at 2.3µm wavelength. This demonstrates the viability of these detectors for future free-space photon counting applications in the mid-infrared where atmospheric absorption and background solar flux are low.

A novel approach for fiber optics 3D shape sensing, applicable to mini-invasive bio-medical devices, is presented. The approach exploits the optical backscatter reflectometry (OBR) and an innovative setup that permits the simultaneous spatial multiplexing of an optical fibers parallel. The result is achieved by means of a custom-made enhanced backscattering fiber whose core is doped with MgO-based nanoparticles (NP). This special NP-doped fiber presents a backscattering-level more than 40 dB higher with respect to a standard SMF-28. The fibers parallel is built to avoid overlap between NP-doped fibers belonging to different branches of the parallel, so that the OBR can distinguish the more intense backscattered signal coming from the NP-doped fiber. The system is tested by fixing, with epoxy glue, 4 NP-doped fibers along the length of an epidural needle. Each couple of opposite fibers senses the strain on a perpendicular direction. The needle is inserted in a custom-made phantom that simulates the spine anatomy. The 3D shape sensing is obtained by converting the measured strain in…

We demonstrate monolithically defined grating couplers in Z-cut lithium niobate on insulator for efficient vertical coupling between an optical fiber and a single mode waveguide. The grating couplers exhibit ∼ 44.6%/coupler and ∼ 19.4%/coupler coupling efficiency for TE and TM polarized light respectively. Taperless grating couplers are investigated to realize a more compact design.

For the [0001] oriented AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs), the holes in the p-type electron blocking layer (p-EBL) are depleted due to the polarization induced positive sheet charges at the last quantum barrier (LQB)/p-EBL interface. The hole depletion effect significantly reduces the hole injection capability across the p-EBL. In this work, we propose inserting a thin AlN layer between the LQB and the p-EBL, which can generate the hole accumulation at the AlN/p-EBL interface. Meanwhile, the holes can obtain the energy when traveling from the p-EBL into the multiple quantum wells (MQWs) by intraband tunneling through the thin AlN layer. As a result, the hole injection and the external quantum efficiency (EQE) have been remarkably enhanced. Moreover, we point out that the thick AlN insertion layer can further generate the hole accumulation in the p-EBL and increase the hole energy which helps to increase the hole injection. We also prove that the intraband tunneling for holes across the thick AlN insertion layer is facilitated by using the optimized…

Fourier single-pixel imaging is one of the main single-pixel imaging techniques. To improve the imaging efficiency, some of the recent method typically select the low-frequency and discard the high-frequency information to reduce the number of acquired samples. However, sampling only a small amount of low-frequency components will lead to the loss of object details and will reduce the imaging resolution. At the same time, the ringing effect of the restored image due to frequency truncation is significant. In this paper, a new sparse Fourier single-pixel imaging method is proposed that reduces the number of samples explorations while maintaining increased image quality. The proposed method makes a special use of the characteristics of the Fourier spectrum distribution based on which the power of image information decreases gradually from low to high frequencies in the Fourier space. A variable density random sampling matrix is employed to achieve random sampling with Fourier single-pixel imaging technology, followed by the processing of the sparse Fourier spectra using compressive…

Alvarez lenses offer accurate and high-speed, dynamic tuning of optical power through a lateral shifting of two lens elements, making them an appealing solution to eliminate the inherent decoupling of accommodation and convergence seen in conventional stereoscopic displays. In this paper, we present a design of a compact eyepiece coupled with two lateral-shifting freeform Alvarez lenses to enable a compact, high-resolution, optical see-through head-mounted display (HMD). The proposed design is able to tune its focal depth from 0 to 3 diopters, rendering near-accurate focus cues with high image quality and a large undistorted see-through field of view (FOV). Our design utilizes an 1920x1080 color resolution organic light-emitting diode (OLED) microdisplay to achieve a >30 degree virtual diagonal FOV, with an angular resolution of <0.85 arcminutes and an average optical performance of > 0.4 contrast over the full field. We also experimentally demonstrate a fully functional benchtop prototype using mostly off-the-shelf optics.

Metasurfaces are an emerging technology that may supplant many of the conventional optics found in imaging devices, displays, and precision scientific instruments. Here, we develop a method for designing optical systems composed of multiple unique metasurfaces aligned in sequence and separated by distances much larger than the design wavelengths. Our approach is based on computational inverse design, also known as the adjoint-gradient method. This technique enables thousands or millions of independent design variables (e.g., the shapes of individual meta-atoms) to be optimized in parallel, with little or no intervention required by the user. The assumptions underlying our method are as follows: we use the local periodic approximation to determine the phase-response of a given meta-atom, we use the scalar wave approximation to propagate light fields between metasurface layers, and we do not consider multiple reflections between metasurface layers (analogous to a sequential-optics ray-tracer). To demonstrate the broad applicability of our method, we use it to design an achromatic…

Heavy metal pollution is one of the main problems in water pollution, which is harmful to humans. Surface-enhanced laser-induced breakdown spectroscopy (SENLIBS) has been applied to detect trace amounts of heavy metal elements in aqueous solution; however, it is still a big challenge to explore the relationship between the LIBS detection sensitivity and the substrate's physical properties. In this work, four typical substrates, zinc (Zn), magnesium alloy (Mg), nickel (Ni), and silicon (Si), were compared; and the mechanism of spectral enhancement by different substrates in SENLIBS was investigated. The results indicated that the limit of detection (LoD) of heavy metal elements on different substrates is positively proportional to the boiling of the substrate. That is mainly because a higher plasma excitation temperature and electron density are obtained, leading to more intense collision between particles. The signal enhancement is associated with the lower boiling point of the substrate (corresponding to a lower ablation threshold and higher ablation quantity from the substrate).…

We present a generic approach for the generation of pseudo non-diffracting Bessel beams using polarization insensitive metasurfaces with high efficiency. Cascaded unit cells, which are fully symmetric, are designed for the complete 2π phase control in the transmission mode. Based on the topological arrangements of such unit cells, two metasurfaces for the generation of zero-order (i.e., single phase profile) and first-order (i.e., merger of two distinct phase profiles) Bessel beams are designed and characterized. Both numerical simulations and experimental measurements are in agreement with each other, confirming the electromagnetic characteristics of the reported Bessel beams. Owing to the isotropy of the unit cells and the rotational symmetry of the arrangements, the proposed metasurfaces are polarization insensitive, providing a promising avenue for achieving such wave manipulations with any linear or circular polarization.

Dynamically and independently tunable absorbers based on multilayer metal-graphene metamaterials are proposed to achieve multi-band and ultra-wide-band absorbing properties at mid-infrared frequencies. Dual-band, triple-band and even more bands absorption can be arbitrarily customized by etching the appropriate number of tandem gold strips in each meta-molecule, as well as stacking multiple metal-graphene layers. Through tuning the Fermi energy level of the graphene in each metal-graphene layer separately, the multiple absorption resonances can be dynamically and independently adjusted. With side-by-side arrangement of the gold strips in each supercell, the proposed structure is rendered to be a promising candidate for ultra-wide-band absorber. The extreme bandwidth exceeding 80% absorption up to 7.5THz can be achieved with a dual-layered structure, and the average peak absorption is 88.5% in the wide-band range for lossless insulating interlayer. For a triple-layered structure, the average peak absorption is 84.7% from 27.5 THz to 38.4 THz with a minimum of 60%. The absorption…