Search

This article proposes a variable-leakage-flux flux-intensifying permanent magnet machine (VLF-FIPMM). Through the addition of magnetic bridge and the innovative design of magnetic barrier, the machine owns the feature of Ld

In order to overcome the shortcomings of the existing single terminal leakage protection methods, the leakage protection technology based on multi-terminal information should be studied. Based on the analysis of the characteristics of singlephase leakage faults in low-voltage distribution lines, a leakage protection method based on double terminal residual current sudden changes is proposed in this paper, which uses the amplitudes of the double-terminal residual current sudden changes of the protected section as the protection criteria. The protection will act when the double terminal criteria both meet the requirements of their respective setting thresholds. The realization processes and performances of the method are given in the paper. The double terminal residual current information of the protected section is comprehensively utilized by this method, which can effectively eliminate the influence of unbalanced leakage current of line during normal operation and other factors, reduce protection maloperation and improve the utilization rate of protection. It doesn't need multi-level protection delay coordination and has fast action speed; and it has low setting thresholds and high sensitivity. The effectiveness of the method is verified by MATLAB simulation.

The polarization characteristic of ocean or atmospheric optical sensor is one of the important factors affecting the accuracy of radiation measurement and quantitative inversion. According to polarization ray tracing algorithm, a calculating model of the polarization sensitivity based on the Muller pupil is proposed. A complete coastal zone remote sensor with low polarization sensitivity is designed, optimized and controlled, by the cooperative design of optical configuration compensating and coating. The result shows that the linear polarization sensitivity is less than 2.5% at B1, and below 1.5% for other four bands respectively.

In recent years, the emerging global navigation satellite system reflectometry (GNSS-R) technology has become a research hotspot for its lightweight, high sensitivity and rich technology application scenarios. It has broad application prospects in the field of remote sensing detection and navigation technology. The role of GNSS-R remote sensing satellite in the field of marine remote sensing is becoming increasingly prominent. The acquisition of data and information and the observation performance of GNSS-R remote sensing satellite are not only constrained by the remote sensing equipment itself, but also affected by the satellite orbit. Based on the technical characteristics of GNSS-R remote sensing satellite, this paper proposes a grid based coverage efficiency statistical method, analyzes some influencing factors of GNSS-R remote sensing satellite efficiency based on the remote sensing task, and analyzes the influence of each factor on GNSS-R remote sensing satellite efficiency by modeling -It can provide theoretical reference for GNSS-R satellite orbit selection and optimization, onboard load design optimization and large-scale system construction.

LiDAR echo intensity information can reflect the reflection characteristics of the target surface, and can be used as an important data source in the aspects of LiDAR point cloud image vision, classification and feature extraction. Geiger mode avalanche photodiode (Gm-APD) has the ability of single photon detection and high range sensitivity, and is widely used in the field of lidar. The number of statistics is often taken as the target intensity information obtained. In order to make the intensity image accurately reflect the reflection characteristics of the target surface, a kind of intensity information correction method of Gm-APD lidar is proposed. By eliminating the distortion caused by the detection model and target distance of the detector, the average reflectivity estimation error can be increased from 51.97% to 8.86%. Aiming at Gm-APD lidar, the determination method of parameters in parameter estimation method is systematically described in this paper. On this basis, the calibration of the laser emitter can improve the uniformity of the target, and the standard deviation is increased from 1.1818 to 0.0050. The proposed scheme can provide a reliable data source for target recognition, classification and feature extraction based on Gm-APD intensity image.

As a high-precision angular rate sensor, high-precision fiber optic gyroscope (HP-FOG) can be used for space positioning, strategic missile guidance and submarine navigation. With the further improvement of the demand for navigation accuracy under deep and open sea conditions and satellite rejection conditions, the goal is to manufacture FOG with higher accuracy and sensitivity. The noise of FOG has become the key to restrict its application in high-precision field. In this paper, the noise source of FOG is analyzed, and the method of using semiconductor optical amplifier to suppress relative intensity noise and feedback adjustment to reduce noise is given. In theory, we propose a scheme of FOG using three photon states as light source to improve the detection sensitivity. In theory, this scheme can realize three times super-resolution measurement.

Tolerance analysis and tolerance sensitivity optimization (desensitization) are important and necessary for manufacturability. However, compared to the optimization of optical performance, tolerance analysis is still time-consuming. A machine learning approach for the fast robustness estimation of lens systems is proposed. The results of the machine learning estimation and the other four different methods are compared with the results of the Monte Carlo analysis. The proposed model is added to the merit function in commercial software for optimization to reduce the sensitivity.

The paper proposes sigmoidal activation functions based on atomic functions. The properties of atomic functions are described, which allow them to satisfy the conditions for transfer functions in artificial neural networks. The applied problems of using the presented functions are considered on the example of problems of analysis of biophysical signals of cardiac activity. The results obtained using the constructed classifiers using various architectures of neural networks, including MLP, RNN, LSTM, GRU, CNN networks, are presented. The efficiency of using atomic functions in the constructed neural networks on the examples of the problem of automated diagnostics of pathologies based on seismocardiography data and biometric authentication by heart rate was determined using metrics of accuracy, recall, precision, sensitivity, specificity, and F-measure.

Bus detector layout is essential for detecting reactive transit signal priority (TSP) at an intersection, and a single-step detection concerned in practice difficultly takes into account the fluctuation of operating speed and the flexibility of adjusting the timing scheme. Therefore, synthetically considering the two factors, a multi-step detector layout algorithm, involving two types of detectors, is proposed and the corresponding detection mechanism is performed for TSP. Based on the constraint of four bus arrival conditions and two priority strategies, a preview detector layout algorithm is established with a low fail-priority rate, which satisfies the premise of adjusting the scheme with certain flexibility for the worst condition. Then, in the near position, a confirm detector is installed to modify the deviation of travel time caused by the speed fluctuation and correct the priority scheme. Moreover, an intersection simulation scenario with TSP is carried out based on VISSIM and VAP, and four cases are established for the sensitivity analysis of the detectors’ positions. As the distance of the preview detector increases, the fail-priority rate decreases stepwise, and the efficiency is better at 450m, in Case ①. When the confirm detector is set at 150 m, the adverse efficiency caused by speed fluctuation is effectively alleviated, with the average vehicle delay reduced to 5.1 s/veh, in Case ③. Thus, the simulation result shows that the optimal detector distances are 450m, and 150m respectively, which verifies that the bus detector layout algorithm could effectively improve the bus operation efficiency and reliability.

A core-offset hetero structured optical fiber was fabricated and proposed for surface plasmon resonance (SPR) sensor. The hetero structure was constituted by a multimode fiber (MMF), core-offset single mode fiber (SMF), and MMF, which are spliced together by a fusion splicer. The effect of the size of core-offset on the RI sensing performance was studied experimentally. The results show that compared with the traditional MMF-SMF-MMF structure, the sensitivity of the proposed structure can be improved, and the highest sensitivity can reach to 6760.17 nm/RIU when the core-offset is 9 μm. The sensor is easy to fabricate, simple structure.

A sensitive structure with built-in T-shaped beams was studied in the paper to achieve high fill-factor and high sensitivity for Micro-Optical-Electro-Mechanical-Systems (MOEMS) application. The silicon proof mass in the structure was supported by four identical T-shaped beams, which were distributed symmetrically and orthogonally in the plane to suppress the in-plane cross coupling. In particular, the T-shaped beam was composed of three parts: stress releasing structure, cantilever and flexible linking structure. The stress releasing structure was used to avoid torsion or warpage caused by residual stress and improve the sensitivity at the same time. The mechanical properties were studied systematically by finite element simulation. The stiffness in z-axis direction was much lower than the in-plane stiffness of the structure, indicating high z-axis sensitivity and small cross coupling error. The reason for high sensitivity of the sensitive structures was fully illustrated by comparing the displacement responses for different beams. The simulation results indicated that the sensitivity was improved more than twice because the stress releasing structure and flexible linking structure reduced the axial stress caused by deflection. Finally, the optical performances were also evaluated in terms of bandwidth and tuning range when used for MEMS Fabry Perot Optical Tunable Filter. The wavelength tuning range achieved about 1.8μm in long-wave infrared waveband by controlling the applied voltage.

A distributed flexible tactile sensor based on 2D fiber Bragg grating (FBG) sensing is designed and produced in this study to solve the error of the single FBG flexible tactile sensor in identifying any two pressure positions symmetrical to the z-axis with grating center as the origin. This study also aims to obtain accurate pressure information on the surface of the electronic skin. A new type of tactile sensing application scheme composed of multiple FBG sensing elements with high spatial resolution is determined by analyzing the characteristics of FBG flexible sensing and by using ANSYS software for dynamic simulation. Simulation and experimental results show that the flexible tactile sensor proposed in this study has high linearity and sensitivity. In addition, the spatial resolution of the proposed sensor is increased by 8 times compared with that of a single FBG sensor with the same length. Research results can be applied to the tactile detection of the flexible electronic skin for robots. This application, which provides a feasible solution to develop and promote flexible electronic skin, has a wide range of prospects.

This article proposes and demonstrates a kind of all fiber vector magnetic field sensor based on side-polished hollow-core fiber (SPHCF) coated with magnetic fluid. The magnetic field sensor is composed of a single mode fiber- SPHCF - single mode fiber structure coated with the magnetic fluid. Our designed sensor has good identification of magnetic field orientation. In the experiments, the maximum orientation sensitivity and the intensity sensitivity are 0.19dB/° and -769.05 pm/mT, respectively. Additionally, we found that the changes of the concentration of the magnetic fluid and the sidepolished depth will lead to the change of the higher-order modes involved in the interference as well as the sensitivity of the magnetic field sensor. The proposed vector magnetic field sensor has the advantages of all fiber, simple structure, cost-effective and easy to manufacture, and etc.

In demand for minute defect inspection, it is required to detect weak scattered light caused by small defects. Ghost imaging (GI) is known for its high sensitivity and high noise resistance method. However, it requires many measurements to obtain a high-quality image because GI is the correlation-based imaging method. Reducing the number of measurements, a method combined with deep learning has been proposed. In order to improve the estimation accuracy using CNN, we propose to parallelize the convolutional layers. Parallel convolutional layers can efficiently extract both local and global features, which contributes to the improvement of estimation accuracy. In this report, we show that parallel CNN is more accurate than conventional CNN by experiments.

Model-based Mask Process Correction (MPC) is an indispensable data processing step for producing masks for advanced wafer production nodes. Typically, calibration of an MPC model may require several thousands SEM measurements. However, due to metrology tool-time constraints, there is an increasing requirement to minimize the number of measurements for building an MPC model, without impacting the model quality significantly. This work presents the development of a down-sampling approach using a combination of sensitivity analysis and clustering to reduce a larger set of diverse measurement locations to a smaller subset according to the metrology budget of photomask engineers.

During the production of a new designed lens system, overweighted assembling and manufacturing errors can cause the degradation of the performance of the whole system. Therefore, optimizations to improve the assembling and manufacturing tolerances sensitivity are greatly required in lens design industry. Following the principle of Gaussian optics, there are some practical implications of the first order derivatives which are of great significance to analyse the sensitivity of a lens system with its structural parameters changing. It is demonstrated that manufacturing errors, such as tilting, decentering and so on, induce the real rays' height shifting on each surface of an imaging system, which subsequently induces the decline of image quality. Thus, we proposed a scheme to use the first order derivatives of the height of a real ray on the image surface in a lens system versus that on the pupil surface, which indicate the height variations of the real ray on the image surface of the lens system caused by the displacement of its corresponding height on the pupil surface, as a merit function to improve the tolerance sensitivity of the whole system. A test program using the ZPL language in Opticstudio has preliminarily confirmed the effectiveness of our proposed methods. And as it is aimed at controlling the real rays of a lens system to reduce its sensitivity according to assembling and manufacturing errors, our scheme is theoretically able to appropriate to all lens design systems.

It is very challenging to characterize surface/sub-surface defects for large-aperture optics. The first challenge is the conflict between high resolution and large field of view, namely how to reach a good balance between high resolution and high efficiency for detecting various defects with sub-micronover the meter-size surface of optics. The second challenge is how to classify defects accurately, which is very important for determining origin of defects and improving optics quality.In this paper, a multimodal inspection technique for surface/sub-surface defects of large-aperture optics is reported, in which a high speed laser scattering imaging with a sensitivity at 200-nm scale is used for defect discovery of large-aperture optics. The defect discovery provides a statistical result of defects of the optics. After that, a multifunctional microscopic method is used for local defect review. A photo thermal scanning microscopy is used for specific characterization of absorption defects, and a confocal microscopy is used for characterization of sub-surface defects. The defect review provides information for defect classification. Based on this multimodal technique, an inspection system is also developed and used for defect characterization of large optics.

Live cell microscopy technology, especially cell three-dimensional refractive-index reconstruction, is one of the important single-cell analysis methods, which can investigate subcellular organelles and biological mechanisms. Compared with the method of rotating the illumination light, rotating cells can obtain the complete internal structure information of the cell. However, cell rotation based reconstruction methods typically rotate cells in low operation throughput and image unstably in a low sensitivity. To bridge this gap, we demonstrate a combination strategy that uses acoustically oscillating bubble array based acoustofluidic device to simultaneously rotate cells in large-scale, and sets up a wDPM module to record cell quantitative phase maps with a high temporal and spatial phase sensitivity due to the common-path geometry and white light illumination. Result shows the phase accuracy of this system is less than 6.7%, the phase spatial consistency does not exceed 4%.

Optical coherence elastography (OCE) is a new biomedical optical elastic imaging technology. It inherits the advantage of optical coherence tomography (OCT) with high resolution, and it has sub-nanometer displacement measurement sensitivity. OCE uses OCT to detect the deformation of biological tissue along the depth direction under loading, so as to obtain the elastic information of tissue. Among the OCE forms with various loading strategies, compression OCE has attracted great interests for its ease of implementation. However, the quantitative measurement of the loading remains a challenge. Therefore, in this study, we developed a handheld OCE system based on compression OCE with a specially designed stress sensor for loading measurement. The OCE system is built based on swept-source OCT, and a handheld sampling probe was developed with a specially-designed pressure sensor for load measurement. The OCE probe with the stress sensor is evaluated on both artificial phantom and human skin. The results show that the OCE system has a good potential for elasticity measurement on biological tissues in vivo.

Pulse phase thermography (PPT), principal component thermography (PCT) method and Thermal signal reconstruction (TSR) analysis including Logarithmic First-Derivative (LFD) and Logarithmic Second-Derivative (LSD) method have been widely used to improve detection sensitivity and quantitative measurement accuracy in infrared thermal imaging. In this paper, the difference of pulsed thermography results of aluminum specimens with flat bottom holes (FBHs) under PPT method, PCT method and LFD and LSD method was compared. With the result of the above methods, the multi-image average method is proposed to further improve the signal-to-noise ratio at the defect of images. Finally, the difference between the original result and the improved result are compared.

Here we describe the evaluation and subsequent re-design of an optical, point of care parasite infection diagnostic instrument. The original optical system was resolution limited by the focusing objective which had an f5.6 numerical aperture with an effective 3Mega pixel performance giving a minimum resolution of 3.73μm. Changing the objective to an f2.4 lens and employing 12Mega pixel sensor, combined with illumination modelling and re-design, improved resolution to 1.46μm within the necessary 3mm field of view. This presents a simple case for change which leads to benefits in both instrument sensitivity and improved parasite identification and speciation.

The sensitivity of atom interferometers depends on the fidelity of the light pulses used as beamsplitters and mirrors. Atom interferometers typically employ pulses that affect π/2 and π fractional Rabi oscillations, the fidelities of which are reduced when there are variations in atomic velocity and laser intensity. We have previously demonstrated the application of optimal control theory to design pulses more robust to such errors; however, if these variations exhibit a time dependence over periods on the order of the interferometer duration then phase shifts can be introduced in the final fringe that potentially reduce the sensitivity. In this paper, we explain why care must be taken when optimising interferometer pulse sequences to ensure that phase shifts arising from inter-pulse variations are not significantly increased. We show that these phase shifts can in fact be minimised by choosing an appropriate measure of individual pulse fidelity.

Chaos theory, as an essential component of Modern nonlinear dynamical system theory, precisely presents regular control, provides a calculation method to encrypt images based on Henen mapping. This method produces random sequences by the specific key which utilized basic formula from Henon chaotic mapping. The random sequence is then excluded or calculated with original images to achieve the encrypted image and decoded by cipher keys. The simulation results and theoretical analysis we conducted prove the strength of this algorithm in terms of randomness, confidentiality, sensitivity, and efficiency.

Retinal blood vessels segmentation acts as an important part to the treatment of ocular disease. Lately, automatic segmentation based on deep learning can solves problems of low efficiency and strong subjectivity of manual segmentation, and attracts the attention of researchers. In this paper, a novel segmentation model called Residualpath-Res-Dense Net (RRD-Net) is proposed to achieve vessel segmentation. In RRD-Net, Res-block and Dense-block are used to help speeding up the convergence of the network and learning more intrinsic features. In addition, the introduction of Residual Path can cut down the semantic difference between the connected feature and eliminate the potential impact of semantic difference on segmentation accuracy. We apply benchmark datasets DRIVE and CHASE_DB1 to evaluate effectiveness of the proposed network. Accuracy, sensitivity and F1 score demonstrate the effectiveness of RRD-Net.

TN5nm HVM where EUVL was implemented on started in the middle of 2020, but EUV mask pattern inspection is still not ready in terms of fully satisfying customers' requirements. There are three tool candidates; optical, actinic, and e-beam inspection. The E-beam tools have high resolution and sensitivity, but have a low throughput. To better address market requirements, NuFlare has optimized its multi e-beam optics to inspect EUV masks, and apply D2DB method into the e-beam tool to achieve the throughput target. We describe the latest results of verification about main technologies to achieve throughput required for EUV mask inspection.

In recent years, more and more organizations and teams in the world are engaged in photoacoustic imaging research. Photoacoustic imaging is in a state of vigorous development. As an important branch of photoacoustic microscopy, optical resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, which has the advantages of high resolution, high contrast, high sensitivity and non-invasiveness. However, in order to obtain high resolution, it is often necessary to focus the laser beam, which will lead to small imaging depth of field and unable to obtain large-scale structural information. However, in clinical diagnosis, doctors want to obtain large-scale and high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. In order to expand the depth of field of photoacoustic microscopy imaging, this paper proposes a three-dimensional information fusion algorithm for photoacoustic microscopy imaging. Firstly, we obtain two sets of vascular data (except the focus position) by virtual photoacoustic microscopy. Then we take out the B scan data of two sets of three-dimensional data sets in turn, and use the fusion algorithm based on pyramid transform to fuse them. Finally, the maximum projection is used to restore the original data and the fused data. We compare the maximum projection before and after fusion. The experimental results show that the algorithm realizes the extension of the depth of field, and the fused data successfully displays more abundant vascular information in an image, and maintains the advantages of high contrast and high resolution of photoacoustic microscopy imaging.

Coherently Beam Combining System is sensitive to occurring in near-field disturbances: tilts, phase, amplitude, depolarization, defocusing and wavefront aberration. The analytical/numerical model for such purposes was developed. The tilts impact is determined mainly by angular diffraction size of emitter, whereas the size of lattice and number of emitters does not influence on result. The defocusing errors of endcaps in CBC combining optics resulting in the Guoy’s piston/phase errors in far-field must be mandatory compensated. Phase disturbance leading to Marechal formula shows that the lattice architecture and specific beam profile plays second order role. The requirements on tilt and phase compensation do not increase with the complexity of CBC systems (number of emitters), paving the way for designing effective CBC systems with several hundreds of emitters.

Optical monitoring is a go to method for complex filters deposition; however, it can be easily shown that filter performance is dependent on monitoring strategy. When a non-quarter wave design needs to be deposited, usually one or minimal number of monitoring wavelengths is selected. This allows to use correction algorithms based on swing that are compatible with level-cut monitoring to a great extent. This approach has a significant drawback that it is very difficult to find one or few wavelengths that can be used for all layers of a complex filter. We present a different approach that relies on the selection of the best monitoring wavelength for each layer using pre-defined criteria that secure minimized thickness errors for each individual layer. Wavelength selection process uses several important criteria, such as monitoring wavelength sensitivity to errors in previous layers, transmittance evolution speed versus layer thickness growth, noise of measurement setup… We show that an additional important criteria is spectral resolution of the optical monitoring system and its impact on filter’s spectral response after each layer. Last, to ensure stable deposition we show that some precautions must be made to avoid false turning point detections. Using a binary approach for each criteria (pass or fail), monitoring wavelengths then can be selected automatically based on criteria defined above. In this work we demonstrate that such an approach can be implemented on stable deposition technique such as plasma assisted reactive magnetron sputtering (Buhler HELIOS machine) for different types of filters with various complexities. We illustrate our results for example on an 8-layer beamsplitter, a 37 layer D65 compensation filter, or a 100 layer custom shape spectral filter that are all very sensitive even to small thickness errors. Similar or better spectral performances are achieved compared with classical optical monitoring approaches but with an automatically determined optical monitoring strategy.

Soil moisture content (SMC) is a key parameter of environmental processes. Remote sensing provides effective methods for mapping SMC at different spatial resolutions. Using UAS-borne hyperspectral observations enables a SMC retrieval at sub-meter scales. Radiative transfer models (RTMs) such as ProSAIL or Scope include a SMC specific input variable and are thus a potential tool to derive SMC and avoiding extensive reference SMC measurements. The inverse application of RTMs supplies information on SMC and plant traits. Scope and ProSAIL involve SMC data of the root zone and at the surface, respectively. The combined use of both models offers the possibility to derive SMC at two vertical depths. Moreover, SMC relevant vegetation proxies such as leaf water content can be retrieved and alternatively used as indicator for SMC. Such plant traits are highest correlated to SMC at depths of major water uptake. However, their response can have a significant time-lag. We analyze the derivation of SMC at the soil surface and at the root zone using the SMC parameters within existing RTMs. As a first step, we investigate on the sensitivity of ProSAIL and Scope to their soil moisture parameters. We apply these findings on UAS-borne hyperspectral and TIR imagery acquired over a pre-alpine TERENO grassland area. The site is equipped with a SoilNet that measures SMC at different depths. Using this data, we assess the vertical extent of both soil moisture content parameters. By inverse modelling of the vegetation parameters and the use of the temporally continuous SoilNet data at root zone level, we analyze the time-lag between changes in SMC and the corresponding plant trait response to optimize the retrieval of SMC.

A Proof of Concept (POC) demonstrator focusing on colour reproduction was designed to investigate the associated principles in the visible spectral range for adaptive camouflage. Consequently, this demonstrator was set up to deliver a fair replica of uniformly specified coloured backgrounds in various background light conditions using a controlled LEDmatrix- panel. For the panel adaption a camera monitors the predefined background colour whilst a regulator-circuit programme simultaneously processes this camera-signal to adjust the LED-colours. Extensive spectrometer measurements carefully quantify the colour replication accuracy. During these measurements the demonstrator and its regulator-circuit-programme were continually developed to handle the following three major concerns: RGB-channel-saturation, RGBchannel- cross-response and background-reflection-correction. The second (RGB-channel-cross-response) concern was mainly considered, which is caused by a mismatch between the spectral sensitivity of the measuring camera (CSS) and emitted spectral range of the LED-panel (SEP) and is relevant in darker environmental conditions. This disagreement causes a complex non-linear interaction behaviour between changes in the set RGB-values of the LED-panel and the camera measuring these changes for regulator circuit programme processing. So, changes in one RGB-component inadvertently affects other RGB-components. If not properly handled, this leads to an erroneous RGB-signal generation for the LED-matrix-panel and eventually to problematic colour-deviations between the panel and background. By spectrometer measurements investigating these emission and sensitivity components, specific white balance settings in the camera were determined to avoid such RGB-channel-cross-response. This replaces in a more elegant way the extensive characterization of the cross-response by response functions. The background was corrected by established standard procedures and worked correctly at the mainly considered darker surrounding illumination, where potential colour-deviations could be better examined. The application of such correction principles, especially with the here developed strategy for a careful chosen white balance setting (WB) wrt. the used regulation circuit method, allows a significantly improved colour-replication.

X-ray speckle-based imaging (SBI), one of them most recent phase-contrast imaging methods, has received growing interest in the last years. Its simplicity, cost-effectiveness and robustness combined with the high phase sensitivity and compatibility with laboratory X-ray sources make it an attractive method for visualising even minute density differences in samples. Since its first demonstration, SBI has seen rapid development and a range of applications have been identified. Among the various ways to perform SBI, the unified modulated pattern analysis (UMPA) offers a number of advantages. Here, we present an overview of the state of the art of SBI, including some of our work using UMPA in the recent years. We demonstrate the potential of UMPA for applications such as optics characterisation, biomedical and geological imaging and discuss its translation from large-scale synchrotron facilities to the laboratory.

We propose a structure that uses surface plasmon resonance (SPR) of two-dimensional (2D) materials to enhance the sensitivity of the biosensor. When the GH shift is used as an interrogation to the biosensor, since SPR can greatly enhance and control the Goos-Hanchen (GH) shift, the biosensor will have excellent sensitivity. Theoretical research results show that by adjusting the structural parameters, a huge GH shift and a sensitivity that is hundreds of times higher than that of ordinary biosensors can be obtained. This will help research in areas such as basic biology and environmental monitoring.

Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.

This paper covers the writing performance of our multi-beam mask writer, MBM-1000, which has been developed for the 5 nm technology node. It exposes low sensitivity resist faster than VSB writers and prints complex patterns with better fidelity. We will describe its writing performance and compare it with our VSB writer, EBM-9500 PLUS. MBM-1000 has pixel-level dose correction (PLDC). PLDC modulates dose profile at pixel level to improve pattern fidelity and patterning resolution. It is integrated with MBM-1000 data path and runs inline. We will also report functions and writing results of MBM-1000 with PLDC.

An off-axis, three-mirror anastigmat was optically aligned for minimum wavefront error using three different analysis methods to improve alignment efficiency. The three methods involved CODE V Automatic Design (AUT), CODE V Alignment Optimization (ALI), as well as a Zernike Sensitivity Analysis (SENS). Not all methods converged on the same solution during alignment, but all tools were used in unison to optimize the optical alignment process. During initial optical alignment, the AUT tool better estimated the proper magnitude of the required alignment. As alignment progressively became finer, the ALI and SENS tools both produced superior, more in-family alignment solutions. Conclusively, depending on the coarseness of the optical alignment required, all alignment strategies have their merits, but most importantly each tool provides a check against other alignment solutions. Therefore, all tools aid in directing the optical alignment towards a global minimum.

High-quality imaging is typically dependent upon well-focused optical systems; however, precise focusing can be difficult due to the non-linearity of defocus. This paper presents further development of the quad target method (QTM), an alignment technique to linearize defocus for structured light illumination (SLI) systems, by creating a method to simulate the alignment sensitivity. QTM’s sensitivity is the slope of the regression that linearizes defocus and is dependent upon the step height of the quad target and the frequency of the projected fringes. The presented simulation method utilizes the native optical design to faithfully model the residual aberrations and is able to predict the best focus location as a well as the linearized slope. The predicted slope and best focus were compared to experiment using a commercially-available SLI system. For a step height of 500 μm and projected fringe frequency of 6.8 cy/mm, the simulation method predicted the slope to within 5.4% and best focus to 17.7 μm of the measured values.

We explore the high contrast capabilities of large segmented telescopes with Active and Adaptive Optics, with particular focus on a system view, which includes use of approaches that are routine for current large ground-based telescopes. These approaches include continuous Wavefront Sensing and control (WFS&C), and proper partitioning of engineering challenges by optimizing the error budget allocations. We present a methodology to compute wavefront stability requirements in the presence of temporal variations of the observatory optical errors at all spatial scales: global low order aberrations, segment to segment misalignments and high spatial frequencies. We start by deriving the sensitivity of the starlight suppression of a coronagraph instrument (e.g. the relationship between contrast and wavefront variance) for each family of spatial modes. We then propagate open loop wavefronts variances, alongside with the actual photons carrying the information associated with these misalignments, through diffractive linear wavefront sensor models. We calculate the Fisher information of measurements using those. That quantity is then used in the context of a Cramer-Rao bound to evaluate closed loop residuals, which are then propagated through coronagraph models to yield contrast fundamental limits. Working under the assumption that such WFS&C systems will be limited by the information content bottleneck due to the finite magnitude of a natural guide star, we use results from these calculations to quantify observatory requirements for a variety of exoplanet imaging missions. We highlight the similarities and differences between monolithic and segmented architectures, and show that the often-cited need for picometer stability is no longer required for the latter across the full aperture, but rather within combinations of segments. We also consider both the case of batch and recursive wavefront estimators (that take into account the entire sensing history) and make the case for significantly less challenging observatory requirements when the latter class of algorithms is implemented.

Three-dimensional (3D) plasmonic sensors have been developed using the reversal nanoimprint technology. Using this technology, plasmonic sensors with additional levels of metals and asymmetrical profiles were optimized to achieve high sensitivity for biomolecule detection. Combining the unique designs of these 3D nanostructures, the plasmonic sensors have high performance as the devices combined the hybrid coupling effect of localized surface plasmon resonance, Fano resonance, and Fabry-Perot cavity modes to achieve sharp resonance peaks with large resonance peak shifts. Applications of these high performance nanoplasmonic sensors to biosensing will be presented.

Hyperspectral imaging with sufficient resolution and sensitivity for scientifically useful space-based mapping of trace gases has long required large and expensive satellite instruments. Miniaturizing this capability to a CubeSat configuration is a major challenge, but opens up more agile and far less expensive observing strategies. A major step in this direction is our development of NACHOS, an ultra-compact (1.5U instrument, 3U complete CubeSat) hyperspectral imager covering the 300-500nm spectral range in 400 channels. Here we describe laboratory and field performance characterization of this new instrument. Laboratory tests demonstrate spatial and spectral resolutions of

Recent years have witnessed significant interest in topological insulators (TIs), a new form of mater with low scattering states along their edges. This property can be useful for the design of passive or active devices, like defect-tolerant waveguides or lasers with robust extended lasing modes. In this talk we will discuss another interesting application of TIs, namely synchronization of oscillators. We will show that connecting oscillators along the edges of TIs allows their synchronization via the TI edge states with low sensitivity over the oscillator locations and perturbations of their parameters. We will present results for the nonlinear dynamics of such systems and outline potential applications in phased array antennas.

Quantum illumination is a technology that aims to improve the detection sensitivity of a target by utilizing quan- tum entangled state of light. We are studying quantum illumination using two-mode squeezed light. In quantum illumination, one light wave in a quantum entangled state is emitted toward a target during atmospheric disturbance. Therefore, it is extremely important to investigate the propagation characteristics of light waves under various atmospheric conditions toward the realization of quantum illumination. As an example of atmospheric disturbances, we have investigated the effect of uniform fog on light wave propagation in previous studies. It has been found that the effect of uniform fog on the propagation of laser light is mainly energy attenuation. Here we measure the propagation characteristics of single-mode squeezed light in a fog. We succeeded in observing the squeezed light that passed through the fog, and confirmed that the noise level of the squeezed light was degraded by the influence of the fog. It was found that the degradation of the noise level can be explained by considering that the influence of fog is mainly the attenuation of energy.

Thermographic fever-screening systems have been deployed widely for the non-contact detection of febrile temperatures during the COVID-19 pandemic. The standard for required performance (IEC 80601-2-59:2017) [1] of thermographic screening systems describe a specification-based requirement to assure the system is able to detect real febrile temperatures, but does not describe any clinical testing. Thermographic systems have been shown to be sensitive to febrile temperatures in controlled [2,3] and real-world conditions [4]. However, concerns have been raised about elements of these standards [5,6]. In a related report by the author [20], the size-of-source artifact was presented as a major confound in thermographic systems, causing surface temperatures to be altered by enough to make certain systems miss common fever thresholds, and this confound is not addressed by the standard. More concerningly is the recent observation of unacceptably strong bias-towards-normal algorithms in a selection of widely-deployed thermographic systems [7]. On the other hand, the standard covering non-contact body thermometry (IEC 80601-2-56:2017) [8] describes both laboratory and clinical testing to assure the system can detect febrile temperatures. Many single-pixel and at least one multi-pixel infrared thermometers are widely available with 510(k) marketing approval by the US FDA. In principle, clinical testing can give a greater certainty about real-world device performance. However, as we show in this report, many if not most of these devices also resort to unacceptably strong bias-to-normal algorithms, with parameters such that they would not be able to distinguish body temperatures ranging from 95F to 103F from normal, similar to the observations of [7]. A challenge for the clinical testing of thermometry and screening devices is the impracticality of finding a population of individuals having a sufficient distribution of elevated temperatures, rather than one group of normal and one group of severely febrile. In this report, we characterize the physiology of the core-to-surface skin temperature relationship, show how several approved devices deviate significantly from this relation and demonstrate a simple test protocol to assess the real-world sensitivity and specificity of an elevated body temperature system. The data we provide in this report show it is possible that many, if not most, non-contact thermometry and thermographic devices are inadequate for their intended uses and investigation is urgently needed. © 2021 SPIE. All rights reserved.

We investigate the exceptional points in a two-layer cylindrical waveguide structure consisting of absorbing and nonabsorbing dielectrics. We show that by tuning the parameters of the structure the complex effective indices of two waveguide modes can coalesce so that an exceptional point is formed. We show that the sensitivity of the effective index of the waveguide mode is enhanced at the exceptional point. We also investigate using phase-change materials in multilayer structures to switch between singular points. We show that in multilayer structures consisting of phasechange, lossless dielectric, lossy, and gain materials, absorbing or spectral singularities can be switched to exceptional points, and self-dual spectral singularities can be switched to unidirectional spectral singularities by switching the phasechange material from its crystalline to its amorphous phase. Our results could be important for developing new compact reconfigurable singularity-enhanced optical devices.