Optical Principles Research Articles

The optical throughput of near-infrared static wind imaging interferometer

The basic principle of the near-infrared static wind imaging interferometer (NIR-SWINDII) is expounded. The instrument can simultaneously detect the atmospheric wind speed, temperature, and ozone concentration in the middle and lower thermosphere (25–110 km). According to the optical transmission principle, the exact expression of the ideal and actual optical throughput of the NIR-SWINDII is obtained. To analyze and discuss the influence of the field of view, wavelength, and refractive index systematically, we select a high refractive index and a low refractive index glass matching schemes according to the “full compensation” principle of the wide-field Michelson interferometer, the simulation of NIR-SWINDII’s optical throughput is carried out. For the high refractive index matching scheme, the results show that when the field of view is within 3 degrees, the transmittance of the NIR-SWINDII can reach 23.38%, and the optical throughput of the entire system is about 0.1024 cm2⋅sr. Comparing with the parameters of other instruments, it is found that our instrument’s optical throughput performance is comparable to other instruments. This research provides the theoretical basis and practical guidance for the throughput optimization of the NIR-SWINDII.

A phase differential heterodyne interferometer for simultaneous measurement of straightness error and displacement

A phase differential heterodyne interferometer for simultaneous measurement of straightness error and displacement is proposed. In this interferometer, a modified mobile sensor composed of a Wollaston prism and a semi-reflective plane mirror is adopted to obtain the straightness error and displacement information simultaneously. A phase differential measurement is utilized to obtain phase differential signals for straightness error and displacement measurement, respectively, by using phase retarder and polarizing beam-splitter. Based on the relationship of π phase difference between the nonlinear errors of phase differential signals, the periodic nonlinear error of measurement results can be compensated. Benefiting from this design, the proposed interferometer can not only obtain the straightness error and displacement simultaneously, but also reduce the nonlinearity of measurement and the influence of the measured object’s rotation. The optical configuration and measurement principle are described in detail. The influence of Wollaston prism’s roll error is also discussed. And three verification experiments are presented at last.

Reflective fiber fault detection and characterization using long short-term memory

To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and with high accuracy. With the rapid advancement of telemetry technology and data analysis techniques, data-driven approaches leveraging telemetry data to tackle the fault diagnosis problem have been gaining popularity due to their quick implementation and deployment. In this paper, we propose a novel multitask learning model based on long short-term memory to detect, locate, and estimate the reflectance of fiber reflective faults (events) including the connectors and the mechanical splices by extracting insights from monitored data obtained by the optical time-domain reflectometry principle commonly used for troubleshooting of fiber optic cables or links. The experimental results prove that the proposed method (i) achieves a good detection capability and high localization accuracy within a short measurement time even for low SNR values and (ii) outperforms conventionally employed techniques.

Piston Error Measurement for Segmented Telescopes with an Artificial Neural Network.

A piston error detection method is proposed based on the broadband intensity distribution on the image plane using a back-propagation (BP) artificial neural network. By setting a mask with a sparse circular clear multi-subaperture configuration in the exit pupil plane of a segmented telescope to fragment the pupil, the relation between the piston error of segments and amplitude of the modulation transfer function (MTF) sidelobes is strictly derived according to the Fourier optics principle. Then the BP artificial neural network is utilized to establish the mapping relation between them, where the amplitudes of the MTF sidelobes directly calculated from theoretical relationship and the introduced piston errors are used as inputs and outputs respectively to train the network. With the well trained-network, the piston errors are measured to a good precision using one in-focused broadband image without defocus division as input, and the capture range achieving the coherence length of the broadband light is available. Adequate simulations demonstrate the effectiveness and accuracy of the proposed method; the results show that the trained network has high measurement accuracy, wide detection range, quite good noise immunity and generalization ability. This method provides a feasible and easily implemented way to measure piston error and can simultaneously detect the multiple piston errors of the entire aperture of the segmented telescope.

Optical correction principles of accommodative esotropia

Accommodative esotropia is the most common type of esotropia in children. The patients often need to wear hyperopic glasses to correct eye positions and improve vision and binocular function. However, the course of accommodative esotropia is usually long, so it is necessary to monitor the refractive changes for a long time. Maintaining full hyperopic correction will interfere with the emmetropia development of the eyeball, and undercorrection of hyperopia will lead to the risk of esotropia decompensation. These often bring confusion when clinicians prescribe glasses. The benefits of accommodative esotropia with a high accommodation convergence/accommodation ratio from fitting bifocal lenses and the effect of prisms on residual esotropia have also been controversial topics in this field. In this article, we combine the research status and clinical practice to present some points of view for the peer reference. (Chin J Ophthalmol, 2021, 57: 331-335).

Optical Prior-Based Underwater Object Detection with Active Imaging

Underwater object detection plays an important role in research and practice, as it provides condensed and informative content that represents underwater objects. However, detecting objects from underwater images is challenging because underwater environments significantly degenerate image quality and distort the contrast between the object and background. To address this problem, this paper proposes an optical prior-based underwater object detection approach that takes advantage of optical principles to identify optical collimation over underwater images, providing valuable guidance for extracting object features. Unlike data-driven knowledge, the prior in our method is independent of training samples. The fundamental novelty of our approach lies in the integration of an image prior and the object detection task. This novelty is fundamental to the satisfying performance of our approach in underwater environments, which is demonstrated through comparisons with state-of-the-art object detection methods.

DbOBS: dual buffered switch for variable optical bursts in future datacenters

Modern data-driven applications pose stringent requirements of high bandwidth, ultra-low-latency, low-powered, and scalable interconnections among switches and routers in data-centers. To address these demands, electronic switching is not a viable choice due to bandwidth and computing bottlenecks. Thus, researchers explored effective optical switch design principles for next-generation data-centers. In optical switches, data aggregates in the form of optical bursts (OB) at ultra-high speeds. In the case of OB contention, solutions are proposed by researchers to store OB as recirculating patterns in fiber delay lines (FDL) with induced optical delay. However, due to variable burst length, it is not possible to measure slot delay length, thus storage of contending bursts is not possible at intermediate core switches. Motivated from the aforementioned discussions, in this paper, we propose a switch design DbOBS, that is capable to store variable OB during contention slots. DbOBS estimates mean burst length, and possible deviation from mean length to minimize burst loss. The considered switch design is validated through parameters like-burst length estimation, over-reservation, and waiting time. For network-layer simulations, poison arrivals of data bursts are considered as packetized units. The packets are sent through Monte-Carlo arrivals and burst loss probability (BLP) is estimated at various input load conditions and buffer sizes. DbOBS achieves a BLP in order of $$10^{-4}$$ at load $$\approx$$ 0.8, and buffer-size of 50, and burst length of $$L=5$$ , that outperforms the traditional switch designs.

Methods, principles and applications of optical detection of metal ios

• The optical detection methods of 12 common metal ions are reviewed. • The main principles and experimental phenomena of optical detection are summarized. • The development and advantages of optical detection methods are summarized. • The applications of optical detection method are summarized. • The future development and main challenges of optical detection are discussed. Heavy metal elements were widely used in alloy manufacturing, medical treatment, food additive, military industry and other fields, which were harmful to human body. Optical detection was a non-contact nondestructive detection method, which had the advantages of high selectivity, high sensitivity and low cost, and had important applications and prospects in environmental monitoring and biological science. In this paper, the optical detection methods, detection principles and detection methods of 12 kinds of metal ions (Ag + , Al 3+ , Cd 2+ , Co 2+ , Cr 3+ , Cu 2+ , Fe 2+ , Fe 3+ ,Hg 2+ ,Pb 2+ , Pd 2+ ,Zn 2+ ) were reviewed. Fluorescence, colorimetry and spectral change were the main detection methods. Fluorescence detection methods mainly included fluorescence quenching, fluorescence enhancement and fluorescence spectrum changes; The colorimetric method included the change of color and the change of ultraviolet absorption spectrum; The spectral changes mainly included circular dichroism, phosphorescence and surface enhanced Raman scattering, etc. Photoinduced electron transfer, intramolecular charge transfer and fluorescence resonance energy transfer were the primary principles of optical detection. The application prospect and main challenges of optical detection were discussed.

Scanless optical feedback imaging principle by single-pixel compressed sensing.

Optical feedback in lasers is being used for unconventional imaging of fluid dynamics, pressure fields, material properties, and free-carrier distribution, especially in spectral regions where two-dimensional detectors are not yet available. As this technique requires scanning the laser spot across the target, the resulting image contrast is often hampered by the speckle effect. Compressed sensing is becoming a workhorse technique for signal analysis, allowing the reconstruction of complex images from a relatively small number of integrated (single-pixel) measurements, and is being efficiently adapted to a number of single-pixel detector cameras. We applied compressed sensing algorithms to the inherently single-pixel optical feedback in a semiconductor diode laser, demonstrating for the first time, to the best of our knowledge, scanless and detectorless speckle-free imaging of a simple binary object.

Detection of Scots Pine Single Seed in Optoelectronic System of Mobile Grader: Mathematical Modeling

The development of mobile optoelectronic graders for separating viable seeds by spectrometric properties with high detection accuracy represents a very relevant direction of development for seed handling operations. Here, the main parameters of the radiation source and receiver for detecting a single seed in the diagnostic system of a mobile grader were modeled based on the principles of technical optics using Scots pine (Pinus sylvestris L.) seeds as a case study. Among the pine seeds in the seed batch, there are fossilized and empty seeds that are exactly the same in geometric and gravitational parameters as live seeds. For their separation from the seed batch, data from spectrometric studies in the near-infrared (980 nm) region can be used. To substantiate the parameters of the light source, a geometric optical model of optical beam formation was considered, while the energy model of optical beam formation was considered to substantiate the parameters of the light detector. The results of this study show that the signal value depended on the orientation of a single seed relative to the recording window. The beam angle from the radiation source should be within 45 degrees. The difference between the optical streams should be 50 microns, which made it possible to clearly detect the signal at a standard noise level of 15 microns and signal-to-noise detection accuracy ratio of 56.3 dB. This study expands theoretical knowledge in the field of the spectrometric properties of a single seed, considering the cases of its orientation relative to the optical beam, which affected the effective area of detection of the seed. The obtained data on the location of the main elements of the diagnostic system will speed up the design of mobile optoelectronic graders, and the development of a contemporary protocol for improving Scots pine seed quality.

Generation of anomalous vector Bessel beams with varying polarization order along the propagation direction

Vector Bessel beams (VBBs) contain non-uniform polarization distributions on the cross-section and non-diffraction characteristics, have been widely used in many fields, including optical trapping, optical microscope, optical communication, etc. Here, we propose a theoretical model to obtain anomalous-VBBs with polarization order dependent on propagation distance. Based on geometrical optics principle, the designed spiral slit allows the introduction of a continuous phase delay, which is used to generate two Bessel vortex beams with opposite chirality and topological charges. Then, by coherently superimposing these two Bessel vortex beams, an anomalous-VBB is generated and shows the polarization order dependent on the propagation distance. Arbitrary polarization orders including integers and fractions can be generated by manipulating the propagation distance. The simulation results show that the local polarization distribution measured at different distances is in good agreement with the polarization distribution of theoretical VBBs, and the local polarization order of anomalous-VBBs is inversely proportional to the propagation distance. The characteristic of this anomalous beam may intrigue the applications of VBBs in light-matter interaction, microscopy and quantum information.

Experimental test of the geometric model of image formation in bright-field microscopy.

In the geometric optics approximation, an image formed by an objective lens replicates the distribution of intensity at the front focal plane of the objective. Although this fact represents a fundamental optical principle, its application to analysis of bright-field microscopic images was developed only recently and has not been tested experimentally. In this paper, we applied simple ray tracing to compute an image of a glass cylinder at various positions of the objective and to compare it to the experiment. We obtained a close match between theory and observation, except for a slight underestimation of the intensity in the middle part of the cylinder. The likely reason for this minor difference was constructive interference due to lens-like properties of a cylinder, which could not be accounted for by geometric approximation. We expect that such artefacts would be negligible in imaging of live cells, and the geometric approach would successfully complement the existing quantitative phase methods.

Pinhole-imaging-based learning butterfly optimization algorithm for global optimization and feature selection

Butterfly optimization algorithm (BOA), as a recently proposed meta-heuristic optimization technique, performs competitively in solving numerical optimization problems as well as real-world applications. However, BOA has low precision, slow convergence and may be prone to local optimum, when solving complex or high-dimensional optimization problems. To overcome these defects, a modified BOA (called PIL-BOA) with adaptive gbest-guided search strategy and pinhole-imaging-based learning is proposed. Firstly, a modified position updated equation by introducing the global best (gbest) solution and the inertia weight is designed to efficiently improve the exploitation capability and the solution precision. Secondly, a novel pinhole-imaging learning strategy based on the principle of optics is presented to effectively search the unknown regions and avoid premature convergence. 23 classical problems and 60 complex optimization tasks from CEC 2014 and CEC 2017 are used to further investigate the effectiveness of PIL-BOA. The comparison results demonstrate that PIL-BOA has better performance than most compared algorithms on benchmark test functions. Finally, PIL-BOA is applied to solve feature selection problems and fault diagnosis in real-world wind turbine. The results show that PIL-BOA is superior to other competitors in term of classification accuracy.

Optical Screening Methods for Pesticide Residue Detection in Food Matrices: Advances and Emerging Analytical Trends.

Pesticides have been extensively used in agriculture to protect crops and enhance their yields, indicating the need to monitor for their toxic residues in foodstuff. To achieve that, chromatographic methods coupled to mass spectrometry is the common analytical approach, combining low limits of detection, wide linear ranges, and high accuracy. However, these methods are also quite expensive, time-consuming, and require highly skilled personnel, indicating the need to seek for alternatives providing simple, low-cost, rapid, and on-site results. In this study, we critically review the available screening methods for pesticide residues on the basis of optical detection during the period 2016–2020. Optical biosensors are commonly miniaturized analytical platforms introducing the point-of-care (POC) era in the field. Various optical detection principles have been utilized, namely, colorimetry, fluorescence (FL), surface plasmon resonance (SPR), and surface enhanced Raman spectroscopy (SERS). Nanomaterials can significantly enhance optical detection performance and handheld platforms, for example, handheld SERS devices can revolutionize testing. The hyphenation of optical assays to smartphones is also underlined as it enables unprecedented features such as one-click results using smartphone apps or online result communication. All in all, despite being in an early stage facing several challenges, i.e., long sample preparation protocols or interphone variation results, such POC diagnostics pave a new road into the food safety field in which analysis cost will be reduced and a more intensive testing will be achieved.

Optical Remote Sensing of Oil Spills in the Ocean: What Is Really Possible?

Optical remote sensing (ORS) of reflected sun light has been used to assess oil spills in the ocean for several decades. While most applications are toward simple presence/absence detections based on the spatial contrast between oiled water and oil-free water, recent advances indicate the possibility of classifying oil types and quantifying oil volumes based on their spectral contrasts with oil-free water. However, a review of the current literature suggests that there is still confusion on whether this is possible and, if so, how. Here, based on the recent findings from numerical models, laboratory measurements, and applications to satellite or airborne imagery, we attempt to clarify this situation by summarizing (1) the optics behind oil spill remote sensing, and in turn, (2) how to interpret optical remote sensing imagery based on optical principles. In the end, we discuss the existing limitations and challenges as well as pathways forward to advance ORS of oil spills.

Microwave hologram reconstruction for cylindrical geometry

Microwave imaging is a technique for evaluation of hidden or embedded objects in an optically opaque structure (or media) using electromagnetic waves in microwave regime. The result of the study is a microwave image of the internal structure of the investigated object, which is built by reconstructing the electromagnetic field scattered by the object (microwave hologram), recorded using some radar system at some aperture. Along with the widespread flat aperture, a cylindrical aperture is often used in personnel screening systems, microwave system for automated body measurement for apparel fitting, and medical tomographic scanners. Cylindrical geometry requires special holograms reconstruction methods. The work is dedicated to comparison of three hologram reconstruction methods: №1 – back projection, №2 – back propagation and №3 – Gauss–Newton, and identifying the advantages and disadvantages of each method. All methods were adopted to cylindrical geometry, software implemented using Python programming language and compared. Comparison was performed by reconstruction of microwave holograms of the same objects. Microwave holograms for comparison were calculated in accordance with the principles of physical optics for point scatterers and using the computational electromagnetics software product FEKO for solid objects. Comparison criteria were: speed of calculations, quality of obtained microwave images, required random access memory (RAM) of the computer. Based on the results of numerical experiments, the following conclusions can be made. For both point and solid objects, all methods have showed a similar quality of the obtained microwave images, the difference turned out to be minimal both in visual and numerical estimation. The advantage of method №1 is the simplicity of its software implementation. In addition, using the first method, you can easily do reconstruction for any area (line, surface, volume), the position of which can be arbitrary in relation to the positions of the samples of the radar signal. Method №2 is the fastest method. With the parameters considered in the article, it is two orders of magnitude faster than method №1, and its performance can be easily increased by parallelizing calculations for different radii. Among the shortcomings, one can note the complexity of its software implementation and the dependence of the position and size of the reconstructed area on the location and number of samples of the radar signal. A significant drawback of method №3 is its high requirements to the RAM of the computer, as well as low speed of calculations. When processing microwave holograms with a large number of samples, calculations may require more memory than is installed in the computer, and the calculation time will increase many times due to the continuous exchange of data with the hard disk, or it will be impossible to do the calculations at all.

Comparison of areal and profile surface measurement methods for evaluating surface properties of machined components

The surface properties of machined components not only affect their optical but also functional behaviour, which makes information about waviness and roughness an important basis for optimization approaches. Therefore the still often used tactile measurement principles in industrial applications are continuously replaced by non-destructive optical measurement principles enabling faster and more flexible measuring. This paper discusses the comparability of different surface parameters, which were generated by profile or areal measurement using both the tactile and the stripe light projection principle. Based on the results the validity of the investigated parameters for different applications and materials can be increased.

Review of micromachined optical accelerometers: from m<i>g</i> to sub-μ<i>g</i>

Micro-Opto-Electro-Mechanical Systems (MOEMS) accelerometer is a new type of accelerometer which combines the merits of optical measurement and Micro-Electro-Mechanical Systems (MEMS) to enable high precision, small volume and anti-electromagnetic disturbance measurement of acceleration. In recent years, with the in-depth research and development of MOEMS accelerometers, the community is flourishing with the possible applications in seismic monitoring, inertial navigation, aerospace and other industrial and military fields. There have been a variety of schemes of MOEMS accelerometers, whereas the performances differ greatly due to different measurement principles and corresponding application requirements. This paper aims to address the pressing issue of the current lack of systematic review of MOEMS accelerometers. According to the optical measurement principle, we divide the MOEMS accelerometers into three categories: the geometric optics based, the wave optics based, and the new optomechanical accelerometers. Regarding the most widely studied category, the wave optics based accelerometers are further divided into four sub-categories, which is based on grating interferometric cavity, Fiber Bragg Grating (FBG), Fabry-Perot cavity, and photonic crystal, respectively. Following a brief introduction to the measurement principles, the typical performances, advantages and disadvantages as well as the potential application scenarios of all kinds of MOEMS accelerometers are discussed on the basis of typical demonstrations. This paper also presents the status and development tendency of MOEMS accelerometers to meet the ever-increasing demand for high-precision acceleration measurement.

Best Practices for Germicidal Ultraviolet-C Dose Measurement for N95 Respirator Decontamination.

Ultraviolet-C (UV-C) decontamination holds promise in combating the coronavirus disease 2019 pandemic, particularly with its potential to mitigate the N95 respirator shortage. Safe, effective, and reproducible decontamination depends critically on UV-C dose, yet dose is frequently measured and reported incorrectly, which results in misleading and potentially harmful protocols. Understanding best practices in UV-C dose measurement for N95 respirator decontamination is essential to the safety of medical professionals, researchers, and the public. Here, we outline the fundamental optical principles governing UV-C irradiation and detection, as well as the key metrics of UV-C wavelength and dose. In particular, we discuss the technical and regulatory distinctions between UV-C N95 respirator decontamination and other applications of germicidal UV-C, and we highlight the unique considerations required for UV-C N95 respirator decontamination. Together, this discussion will inform best practices for UV-C dose measurement for N95 respirator decontamination during crisis-capacity conditions.

Comparison of central corneal thickness measurements with three different optical devices.

Purpose:The purpose of this study was to compare and evaluate the agreement of central corneal thickness (CCT) values obtained with three different devices working according to optical principle in healthy eyes.Methods:60 eyes of 60 individuals (30 men and 30 women) were enrolled in this study. CCT measurements performed with Scheimpflug–Placido topographer (Sirius), spectral-domain optical coherence tomography (RTVue) with an anterior segment module, and optical biometer (AL-Scan) were compared. Bland–Altman analysis was used to demonstrate agreement between methods.Results:The mean age was 30.07 ± 7.313 years (range, 18–47 years). The mean CCT values obtained by RTVue, Sirius, and AL-Scan were 518.25 ± 36.38 µm, 526.08 ± 36.33 µm, and 513.50 ± 39.09 µm, respectively. The mean differences in CCT were 7.83 ± 14.15 µm between Sirius and RTVue, 12.58 ± 11.87 µm between Sirius and AL-Scan, and 4.75 ± 4.50 µm between RTVue and AL-Scan. The mean CCT was statistically different among the three groups (p < 0.05). All three modalities of CCT measurements correlated closely with each other, with Pearson’s correlation coefficients ranging from 0.924 to 0.961. The 95% limits of agreement were −19.90 to 35.56 µm between Sirius and RTVue, −10.69 to 35.85 µm between Sirius and AL-Scan, and −4.07 to 13.58 µm between RTVue and AL-Scan.Conclusion:Different results could be obtained through different noncontact devices in CCT measurements. Although the measurement values obtained by these devices show a high level of correlation, it would be a more correct approach to not use them directly interchangeably in clinical practice. Evaluation and follow-up of CCT should be performed using the same device.