Photonics, Volume 9, Issue 3 (March 2022) – 82 articles

An adaptive method for determining the type and magnitude of aberration in a wide range is proposed on the basis of an optical processing of the analyzed wavefront using a multichannel filter matched to the adjustable Zernike phase functions. The approach is based on an adaptive (or step-by-step) compensation of wavefront aberrations based on a dynamically tunable multichannel filter implemented on a spatial light modulator. For adaptive filter adjustment, a set of criteria is proposed that takes into account not only the magnitude of the correlation peak, but also the maximum intensity, compactness, and orientation of the distribution in each diffraction order. The experimental results have shown the efficiency of the proposed approach for detecting wavefront aberrations in a wide range (from 0.1λ to λ). Full article

In order to meet the massively increasing requirements of big-data applications, data centers (DCs) are key infrastructures to cope with the associated demands, such as high performance, easy scalability, low cabling complexity and low power consumption. Many research efforts have been dedicated to traditional wired data center networks (DCNs). However, DCNs’ static and rigid topology based on optical cables significantly limits their flexibility, scalability, and even reconfigurability. The limitations of this wired connection can be addressed with optical wireless technology, which avoids cable complexity problems while allowing dynamic adaption and fast reconfiguration. Here, we propose and investigate a novel optical wireless data-center network (OW-DCN) architecture based on nanoseconds semiconductor optical amplifier (SOA)-based wavelength selectors and arrayed waveguide grating router (AWGR) controlled by fast field-programmable gate array (FPGA)-based switch schedulers. The full architecture, including the design, packet-switching strategy, contention solving methodology, and reconfiguration capability, is presented and demonstrated. Dynamic switch scheduling with a FPGA-based switch scheduler processing optical label and software-defined network (SDN)-based reconfiguration were experimentally confirmed. The proposed OW-DCN was also achieved with a power penalty of less than 2 dB power penalty at BER < 1 × 10⁻⁹ for a 50 Gb/s OOK transmission and packet-switching transmission. Full article

Due to limited data transmission bandwidth and data storage space, it is challenging to perform fast-moving objects classification based on high-speed photography for a long duration. Here we propose a single-pixel classification method with deep learning for fast-moving objects. The scene image is modulated by orthogonal transform basis patterns, and the modulated light signal is detected by a single-pixel detector. Thanks to the property that the natural images are sparse in the orthogonal transform domain, we used a small number of basis patterns of discrete-sine-transform to obtain feature information for classification. The proposed neural network is designed to use single-pixel measurements as network input and trained by simulation single-pixel measurements based on the physics of the measuring scheme. Differential measuring can reduce the difference between simulation data and experiment data interfered by slowly varying noise. In order to improve the reliability of the classification results for fast-moving objects, we employed a measurement data rolling utilization approach for repeated classification. Long-duration classification of fast-moving handwritten digits that pass through the field of view successively is experimentally demonstrated, showing that the proposed method is superior to human vision in fast-moving digit classification. Our method enables a new way for fast-moving object classification and is expected to be widely implemented. Full article

Photoacoustic microscopy (PAM) is an emerging retinal imaging technique that can provide high spatial resolution and high contrast of chorioretinal vessels. PAM is compatible with optical coherence tomography (OCT) and fluorescence imaging, allowing for development of a multimodal imaging system that combines these imaging modalities into one. This study presents a non-invasive, label-free in vivo imaging of retinal and choroidal vascular occlusion using multimodal imaging system, including PAM and OCT. Both retinal vein occlusion (RVO) and choroidal vascular occlusion (CVO) were clearly identified selectively using a spectroscopic PAM imaging. RVO and CVO were created in six rabbits using laser photocoagulation. The dynamic changes of retinal vasculature were observed and evaluated using color fundus photography, fluorescein angiography, OCT, and PAM. The position of RVO and CVO were imaged with different wavelengths ranging from 532 to 600 nm. The data shows that occluded vessels were clearly distinguished from the surrounding retinal vessels on the PAM images. This advanced imaging system is a promising technique for imaging retinal ischemia in preclinical disease models. Full article

In this paper, we develop new classification and estimation algorithms in the context of free space optics (FSO) transmission. Firstly, a new classification algorithm is proposed to address efficiently the problem of identifying structured light modes under jamming effect. The proposed method exploits support vector machine (SVM) and the histogram of oriented gradients algorithm for the classification task within a specific range of signal-to-jamming ratio (SJR). The SVM model is trained and tested using experimental data generated using different modes of the structured light beam, including the 8-ary Laguerre Gaussian (LG), 8-ary superposition-LG, and 16-ary Hermite Gaussian (HG) formats. Secondly, a new algorithm is proposed using neural networks for the sake of predicting the value of SJR with promising results within the investigated range of values between −5 dB and 3 dB. Full article

The heating degree of the inner layers of tumor tissue is an important parameter required to optimize plasmonic photothermal therapy (PPT). This study reports the optical properties of tissue layers of transplanted cholangiocarcinoma and covering tissues in rats without treatment (control group) and after PPT using gold nanorods (experimental group). PPT was carried out for 15 min, and the temperature on the skin surface reached 54.8 ± 1.6 °C. The following samples were cut out ex vivo and studied: skin, subcutaneous connective tissue, tumor capsule, top, center, and bottom part of the tumor. The samples’ absorption and reduced scattering coefficients were calculated using the inverse adding–doubling method at 350–2250 nm wavelength. Diffuse reflectance spectra of skin surface above tumors were measured in vivo in the control and experimental groups before and immediately after PPT in the wavelength range of 350–2150 nm. Our results indicate significant differences between the optical properties of the tissues before and after PPT. The differences are attributed to edema and hemorrhage in the surface layers, tissue dehydration of the deep tumor layers, and morphological changes during the heating. Full article

A Light-Emitting Diode (LED) has a nonlinear characteristic, and it contains fundamental limitations for the performance of Visible Light Communication (VLC) systems in indoor environments when using intensity modulation with Orthogonal Frequency Division Multiplexing (OFDM). In this paper, we investigate this nonlinear characteristic with analysis and proposal. At first, we identified the LED nonlinear characteristics in terms of bit-error performances. After analysis, we propose initial predistortion schemes to mitigate the nonlinearity matters. In the predistortion schemes, the nonlinear distortion compensation model contains predistortion features with the LED inverse characteristics. Considering a Direct-Current-biased Optical OFDM (DCO-OFDM) system, we compared the Bit-Error Rate (BER) performances with and without compensation via simulations. The performance on the LED with the compensation showed LED nonlinearity could significantly improve the bit-error performance. In addition, with consideration that the predistortion model is insufficient to represent LED distortion, we investigated possible opportunities of distortion correction using Bidirectional Long Short-Term Memory (BLSTM), one of the leading deep learning approaches. Its result showed promising improvement of the distortion compensation as well. Full article

In this work, we report a linearity-enhanced dual-parallel Mach–Zehnder modulator (MZM) on a thin-film lithium niobate platform. By setting the optical and electrical splitting ratios at a specific condition, the third-order intermodulation distortions (IMD3) of the child MZMs cancel with each other, whereas the first-order harmonics (FH) reach the maximum. Passive devices instead of thermo-optical switches are used to control the optical power and phase of the child MZMs, which greatly improve the device stability and simplify the operation complexity. To the best of our knowledge, the experimental results show a record-high spurious-free dynamic range on a thin-film lithium niobate platform (110.7 dB·Hz${}^{2/3}$ at 1 GHz). The E-O response decayed about 1.9 dB from 10 MHz to 40 GHz, and the extrapolated E-O 3 dB bandwidth is expected to be 70 GHz. A half-wave voltage of 2.8 V was also achieved. The proposed modulator provides a promising solution for high-bandwidth and low-voltage analog optical links. Full article

We have considered the tight focusing of light with linear polarization. Using the Richards–Wolf formalism, it is shown that before and after the focal plane, there are regions in which the polarization is circular (elliptical). When passing through the focal plane, the direction of rotation of the polarization vector is reversed. If before the focus in a certain area there was a left circular polarization, then directly in the focus in this area there will be a linear polarization, and after the focus in a similar area there will be a right circular polarization. This effect allows linearly polarized light to be used to rotate dielectric microparticles with little absorption around their center of mass. Full article

Jones–Stokes polarimetry is a robust in vitro polarimetric technique that can be used to investigate the anisotropic properties of a birefringent medium. The study of spatially resolved Jones matrix components of an object is a heuristic approach to extract its phase and polarization information. However, direct interpretation of Jones matrix elements and their decomposition into associated anisotropic properties of a sample is still a challenging research problem that needs to be investigated. In this paper, we experimentally demonstrate combined Jones–Stokes polarimetry to investigate the amplitude, phase, and polarization modulation characteristics of a twisted nematic liquid crystal spatial light modulator (TNLC-SLM). The anisotropic response of the SLM is calibrated for its entire grayscale range. We determine the inevitable anisotropic properties viz., diattenuation, retardance, isotropic absorption, birefringence, and dichroism, which are retrieved from the measured Jones matrices of the SLM using Jones polar decomposition and a novel algebraic approach for Jones matrix decomposition. The results of this study provide a complete polarimetric calibration of the SLM within the framework of its anisotropic characteristics. Full article

We demonstrate 60 GHz separation optical two-tone signal generation at arbitrary C-band wavelengths without involving complicated optical wavelength filtering. By utilizing a polarizer, the selective suppression of undesired low-order optical sidebands has been proven and optimized based on model analysis. By utilizing this scheme in conjunction with the optimized parameters, more than 20 dB of suppression of undesired optical sidebands have been successfully achieved over a 40 nm wavelength range. This scheme allows us to generate optical two-tone signals at the desired wavelength. Full article

Plasmonic metallic nanostructures have attracted much interest for their ability to manipulate light on a subwavelength scale and for their related applications in various fields. In this work, a parabola-like gold nanobowtie (PGNB) on a sapphire substrate was designed as a nano-cavity for confining light waves in a nanoscale gap region. The near-field optical properties of the innovative PGNB structure were studied comprehensively, taking advantage of the time-resolved field calculation based on a finite-difference time-domain algorithm (FDTD). The calculation result showed that the resonance wavelength of the nano-cavity was quite sensitive to the geometry of the PGNB. The values that related to the scattering and absorption properties of the PGNB, such as the scattering cross section, absorption cross section, extinction cross section, scattering ratio, and also the absorption ratio, were strongly dependent on the geometrical parameters which affected the surface area of the nanobowtie. Increased sharpness of the gold tips on the parabola-like nano-wings benefited the concentration of high-density charges with opposite electric properties in the narrow gold tips with limited volume, thus, resulting in a highly enhanced electric field in the nano-cavity under illumination of the light wave. Reduction of the gap size between the two gold nano-tips, namely, the size of the nano-cavity, decreased the distance that the electric potential produced by the highly concentrated charges on the surface of each gold nano-tip had to jump across, therefore, causing a significantly enhanced field in the nano-cavity. Further, alignment of the linearly polarized electric field of the incident light wave with the symmetric axis of the PGNB efficiently enabled the free electrons in the PGNB to concentrate on the surface of the sharp gold tips with a high density, thus, strongly improving the field across the nano-cavity. The research provides a new insight for future design, nanofabrication, and characterization of PGNBs for applications in devices that relate to enhancing photons emission, improving efficiency for energy harvesting, and improving sensitivity for infrared detection. Full article

The electro-optic output of light-emitting diodes commonly used in visible light communication systems is generally nonlinear in nature. It is particularly problematic when using advanced modulation formats, such as orthogonal frequency-division multiplexing (OFDM), which have a high peak-to-average power ratio due to clipping and distortion. In this work, we introduce the so-called C-transform to the system architecture, which utilises a Walsh–Hadamard matrix in conjunction with a discrete cosine transform to deterministically spread the information and reduce the peak-to-average power ratio (PAPR). Several bias points along the electro-optic transfer function were selected for comparison purposes, and the new transform was compared with more traditional formulations of OFDM. This paper determines that the C-transform-based OFDM demonstrated the highest degree of independence from the non-linearity and yielded superior bit-error rate (BER) results. We note an improvement of ~2.5 dB in the power penalty at a BER of 10⁻⁴ in comparison to OFDM. Full article

Zoom lens with stationary external entrance pupil and internal stop is a type of special optical system that can be used in cascaded optics to meet the requirements of long focal length or variable magnification. We proposed a 4× zoom lens to improve the pupil walking limitation observed in the conventional design. Varifocal- and pupil-stable differential equations are presented and a paraxial design of the lens with two moving parts was developed. Moreover, the zoom lens, which functions in the visible waveband 500 nm~750 nm, is designed using seven types of common optical glasses, has a constant f-number of 10 and focal range of 100 mm~400 mm, and achieves pupil walking in the range −3.9 mm to +4.3 mm. The results demonstrate that the design had good image quality and tolerance characteristics. Owing to the limited pupil walking and zoom capability, the scheme is of considerable interest for application in electrical optical systems. Full article

In this letter, we construct the neural network (NN)-based transceiver to compensate for the varying inter-symbol-interference (ISI) effect in visible light communication (VLC) systems. For processing variable-length sequences, the convolution neural network (CNN) is utilized, and then the residual network structure is further leveraged at the receiver part to enhance the performance. To cope with varying ISI, the pilot sequence, instead of channel side information (CSI) obtained by an additional module, is integrated into the framework to recover the data sequence directly. Simulation results show that the symbol error rate (SER) performance of the proposed NN-based transceiver can outperform separately designed transceiver schemes and approach the ideal perfect CSI (PCSI) case with a few pilot symbols or even no pilot. Full article

We proposed an ultra-sensitive refractive index sensor by using indium-doped cadmium oxide as a plasmonic material operating in near-infrared based on Fano resonance. The proposed sensor has a hybrid multilayer waveguide structure that supports both a long-range surface plasmon polariton (LRSPP) mode and a dielectric waveguide (DWG) mode. The design strategy of the structure parameters of the inner layers is elaborated in detail through the numerical analysis of the two modes. By suitably tailoring the thickness of the coupling layer, a strong mode coupling between the two modes could be achieved, leading to a sharp asymmetric Fano resonance. With the designed optimal physical parameters, our proposed sensor could achieve a maximum intensity sensitivity of 19,909 RIU⁻¹, a 193-fold enhancement than that of a conventional long-range SPR (LRSPR) based scheme. The proposed design can be a promising platform for biochemical sensing in the near-infrared region. Full article

In this paper, optical components are fabricated using a 3D printing method. The two following strategies are adopted: 1. combining 3D printing, “origami”, and metal coating/attaching to directly manufacture parabolic reflectors; 2. inserting mirrors into 3D-printed frames and assembling the mirrors to form a corner cube retroreflector (CCR). PDLC (polymer dispersed liquid crystal) films are integrated with these optical components to achieve voltage-controlled optical power modulation. The tunable CCR is used to construct a solar light communication system. Using sunlight directly as the light source for communication is rarely seen. In this paper, we demonstrate a proof of concept of sunlight communication, exploring a new route of solar energy utilization, in addition to electricity generation and heating. Full article

Single-beam multiple-intensity iterative phase retrieval is a high-precision and lens-free computational imaging method, which reconstructs the complex-valued distribution of the object from a volume of axially captured diffraction intensities using the post-processing algorithm. However, for the object with slowly-varying waves, the method may encounter the problem of convergence stagnation since the lack of diversity between the captured intensity patterns. In this paper, a novel technique to enhance phase retrieval using holographic illumination is proposed. One special computer-generated hologram is designed, which can generate multiple significantly different images at the required distances. The incident plane wave is firstly modulated by the hologram, and then the exit wave is used to illuminate the object. Benefitting from this holographic illumination, remarkable intensity changes in the given detector planes can be produced, which is conducive to fast and high-accuracy reconstruction. Simulation and optical experiments are performed to verify the feasibility of the proposed method. Full article

In clinical medical applications, sparse-view computed tomography (CT) imaging is an effective method for reducing radiation doses. The iterative reconstruction method is usually adopted for sparse-view CT. In the process of optimizing the iterative model, the approach of directly solving the quadratic penalty function of the objective function can be expected to perform poorly. Compared with the direct solution method, the alternating direction method of multipliers (ADMM) algorithm can avoid the ill-posed problem associated with the quadratic penalty function. However, the regularization items, sparsity transform, and parameters in the traditional ADMM iterative model need to be manually adjusted. In this paper, we propose a data-driven ADMM reconstruction method that can automatically optimize the above terms that are difficult to choose within an iterative framework. The main contribution of this paper is that a modified U-net represents the sparse transformation, and the prior information and related parameters are automatically trained by the network. Based on a comparison with other state-of-the-art reconstruction algorithms, the qualitative and quantitative results show the effectiveness of our method for sparse-view CT image reconstruction. The experimental results show that the proposed method performs well in streak artifact elimination and detail structure preservation. The proposed network can deal with a wide range of noise levels and has exceptional performance in low-dose reconstruction tasks. Full article

Nonlinear effects have been restricting the development of high-speed visible light communication (VLC) systems. Neural network (NN) has become an effective means to alleviate the nonlinearity of a VLC system due to its powerful ability to fit complicated functions. However, the complex training process of traditional NN limits its application in high-speed VLC. Without performance penalty, reservoir computing (RC) simplifies the training process of NN by training only part of the network connection weights, and has become an alternative scheme to NN. For the indoor visible light orthogonal frequency division multiplexing (VLC-OFDM) system, this paper studies the signal recovery effect of the pilot-assisted reservoir computing (PA-RC) frequency domain equalization algorithm. The pilot information is added to the feature engineering of RC to improve the accuracy of channel estimation by traditional least squares (LS) algorithm. The performance of 64 quadrature amplitude modulation (QAM) signal under different transmission rates and peak to peak voltage (Vpp) conditions is demonstrated in the experiments. Compared with the traditional frequency domain equalization algorithms, PA-RC can further expand the Vpp range that meets the 7% hard-decision forward error correction (FEC) limit of 3.8 × 10${}^{-3}$. At the rate of 240 Mbps, the BER of the system is reduced by about 90%, and the utilization rate of the available frequency band of the system reaches 100%. The results show that PA-RC can effectively improve the transmission performance of VLC system well, and has strong generalization ability. Full article

Industrial solid waste refers to the solid waste that is produced in industrial production activities. Without correct treatment and let-off, industrial solid waste may cause environmental pollution due to a variety of pollutants and toxic substances that are contained in it. Conventional detection methods for identifying harmful substances are high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), which are complicated, time-consuming, and highly demanding for the testing environment. Here, we propose a method for the quantitative analysis of harmful components in industrial solid waste by using terahertz (THz) spectroscopy combined with chemometrics. Pyrazinamide, benazepril, cefprozil, and bisphenol A are four usual hazardous components in industrial solid waste. By comparing with the Raman method, the THz method shows a much higher accuracy for their concentration analysis (90.3–99.8% vs. 11.7–86.9%). In addition, the quantitative analysis of mixtures was conducted, and the resulting prediction accuracy rate was above 95%. This work has high application value for the rapid, accurate, and low-cost detection of industrial solid waste. Full article

A two-photon polymerization initiator is a kind of nonlinear optical material. With the demand for more efficient initiators in two-photon polymerization additive manufacturing, there are more and more related studies. In this paper, four conjugate-extended two-photon polymerization initiators with different alkane chain lengths were designed and synthesized, and single-photon, two-photon, and photodegradation experiments were carried out. Additive manufacturing experiments illustrated that the designed molecules can be used as two-photon initiators, and the writing speed can achieve 100,000 μm/s at a laser power of 25 mW. Through theoretical calculation and experimental comparison of the properties of molecules with different conjugation degrees, it was proven that a certain degree of conjugation extension can improve the initiation ability of molecules; however, this improvement cannot be extended infinitely. Solubility tests of different acrylates showed that molecules with different alkane chain lengths have varying solubility. Changing the molecular alkane chain length may be favorable to adapt to different monomers. Full article

Underwater wireless optical communication (UWOC) is able to provide large bandwidth, low latency, and high security. However, there still exist bandwidth limitations in UWOC systems, with a lack of effective compensation methods. In this paper, we systematically study the bandwidth limitation due to the transceiver and underwater channel through experiments and simulations, respectively. Experimental results show that by using the 7-tap maximum likelihood sequence estimation (MLSE) detection, the maximum bitrate of the simple rectangular shape on–off-keying (OOK) signaling is increased from 2.4 Gb/s to 4 Gb/s over 1 GHz transceiver bandwidth, compared to the conventional symbol-by-symbol detection. For the bandwidth limitation caused by the underwater channel, we simulate the temporal dispersion in the UWOC by adopting a Monte Carlo method with a Fournier–Forand phase function. With MLSE adopted at the receiver, the maximum available bitrate is improved from 0.4 to 0.8 Gb/s in 12 m of harbor water at the threshold of hard-decision forward-error-correction (HD-FEC, 3.8 × 10⁻³). Moreover, when the bitrate for 0.4 Gb/s 12 m and 0.8 Gb/s 10 m OOK transmission remains unchanged, the power budget can be reduced from 33.8 dBm to 30 dBm and from 27.8 dBm to 23.6 dBm, respectively. The results of both experiments and simulations indicate that MLSE has great potential for improving the performance of bandwidth-limited communication systems. Full article

Light-slowing effect at band edges in photonic crystals (PCs) is widely utilized to enhance optical absorption. However, according to the Bragg scattering theory, photonic bandgaps (PBGs) in traditional all-dielectric one-dimensional (1-D) PCs shift towards shorter wavelengths as the incident angle increases. Therefore, light-slowing effect in traditional all-dielectric 1-D PCs is also angle-sensitive. Such angle-sensitive property of light-slowing effect in traditional all-dielectric 1-D PCs poses a great challenge to achieve wide-angle absorption. In this paper, we design an angle-insensitive PBG in a 1-D PC containing hyperbolic metamaterials based on the phase-variation compensation theory. Assisted by the angle-insensitive light-slowing effect at the angle-insensitive band edge, we achieve wide-angle absorption at near-infrared wavelengths. The absorptance keeps higher than 0.9 in a wide angle range from 0 to 45.5 degrees. Besides, the wide-angle absorption is robust when the phase-variation compensation condition is slightly broken. Our work not only provides a viable route to realize angle-insensitive light slowing and wide-angle light absorption, but also promotes the development of light-slowing- and absorption-based optical/optoelectronic devices. Full article

An Ethernet passive optical network (EPON) is an optical access network that allows a higher data rate with low power consumption. To improve energy savings for an EPON, the sleep and doze modes for the optical network units (ONUs) play a pivotal role. Many prediction schemes have been proposed to control these modes. To increase the prediction accuracy, this study proposes an energy-efficient approach that uses a support vector regression (SVR) model. A dynamic bandwidth allocation (DBA) scheme called SVR-DBA is designed to allocate bandwidth to ONUs more efficiently and fairly. To determine the effectiveness of the proposed scheme, simulations are performed. The simulation results show that the proposed scheme decreases energy consumption for ONUs by up to 47% and fulfills the quality-of-service (QoS) requirements in terms of delay, jitter, and packet loss. Full article

As an important structured beam, vortex beams have a wide range of applications in many fields. However, conventional vortex beam generators require complex optical systems, and this problem is particularly serious with regards to focused vortex beam generators. The emergence of metasurfaces provides a new idea for solving this problem; however, the accompanying chromatic dispersion limits its practical application. In this paper, we show that the dispersion characteristic of focused vortex beam generators based on metasurfaces can be controlled by simultaneously manipulating the geometric and propagative phases. The simulation results show that the transmission-type focused vortex beam generators exhibit positive dispersion, zero dispersion, and negative dispersion, respectively. This work paves the way for the practical application of focused vortex beam generators. Full article

Near-infrared spectroscopy (NIRS) is widely used in fruit and vegetable quality evaluations, usually after harvesting. In particular, the moisture content is a key parameter for determining product quality; processing phase, e.g., drying process; and economical value. NIRS methods are well-established for laboratory practices where the specimens are properly prepared and measurement conditions are well controlled. On the other hand, it is known that in-field NIRS measurements present several difficulties, as many influencing variables, such as mechanical vibrations, electrical and optical disturbances, and dust or dirt in general, can affect the spectral measurement. In this paper, we propose the design and present the prototype of a NIRS-based measuring system for the rapid determination of the moisture content of bales. The new system uses of a halogen lamp illumination unit to recover water absorption spectral data in the range of 900–1700 nm. The compact stainless steel body makes the instrument portable and easy to transport for rapid in-field MC measurements. The prototype system was characterized and its performance extensively evaluated in a laboratory environment. Finally, a preliminary test was carried out, where the moisture contents of 12 freshly harvested crops samples were measured using the partial least squares (PLSs) regression method. The obtained results show that our prototype system can estimate the alfalfa moisture content information with a coefficient of determination $R^2$ of 0.985 and a root mean square relative error of estimation of 7.1%. Full article

The security of the continuous-variable quantum key distribution (CVQKD) system is subject to various attacks by hackers. The traditional detection method of parameter estimation requires professionals to judge known attacks individually, so the general detection model emerges to improve the universality of detection; however, current universal detection methods only consider the independent existence of attacks but ignore the possible coexistence of multiple attacks in reality. Here, we propose two multi-attack neural network detection models to handle the coexistence of multiple attacks. The models adopt two methods in multi-label learning: binary relevance (BR) and label power (LP) to deal with the coexistence of multiple attacks and can identify attacks in real-time by autonomously learning the features of known attacks in a deep neural network. Further, we improve the model to detect unknown attacks simultaneously. The experimental results show that the proposed scheme can achieve high-precision detection for most known and unknown attacks without reducing the key rate and maximum transmission distance. Full article

Photoacoustic imaging is an emerging biomedical imaging technique that combines optical contrast and ultrasound resolution to create unprecedented light absorption contrast in deep tissue. Thanks to its fusional imaging advantages, photoacoustic imaging can provide multiple structural and functional insights into biological tissues such as blood vasculatures and tumors and monitor the kinetic movements of hemoglobin and lipids. To better visualize and analyze the regions of interest, segmentation and quantitative analyses were used to extract several biological factors, such as the intensity level changes, diameter, and tortuosity of the tissues. Over the past 10 years, classical segmentation methods and advances in deep learning approaches have been utilized in research investigations. In this review, we provide a comprehensive review of segmentation and quantitative methods that have been developed to process photoacoustic imaging in preclinical and clinical experiments. We focus on the parametric reliability of quantitative analysis for semantic and instance-level segmentation. We also introduce the similarities and alternatives of deep learning models in qualitative measurements using classical segmentation methods for photoacoustic imaging. Full article

In this paper, a single humidity sensor for water vapor and heavy oxygen water vapor detection is presented. The sensor is based on tunable diode laser absorption spectroscopy (TDLAS) and thus has high sensitivity, good selectivity, and a short response time. A 1372 nm distributed feedback (DFB) diode laser is utilized as the light source, the wavelength tuning range of which covers the absorption lines of water vapor and heavy oxygen water vapor. A Herriott gas cell with 12 m optical length is designed for signal-to-noise ratio (SNR) enhancement. The sensor can distinguish between water vapor and heavy oxygen water vapor effectively. The accuracy of water detection is within ±0.5% RH. The accuracy of heavy oxygen water vapor detection is within ±1.0% RH. Full article