Intersatellite optical communication links will be crucial for the development of future global optical and quantum communication networks. Under the harsh space environment satellite optical terminals will suffer pointing jitter and wavefront errors. In this paper, the impact of the combination of these errors on the transmitter side is modeled. Combining the far-field diffraction patterns obtained through computational Fourier optics and the statistics of the pointing jitter, the received power statistics are derived numerically for different scenarios. The computational model is first used to evaluate the optimum nominal parameters of the transmitted beam. Then, several optical aberrations are added to the transmitted beam and their impact on the communication performance is evaluated through the average bit error rate.

Simulation of diode-pumped solid-state lasers (DPSSL) and amplifiers often do not account for the temperature and spectral dependencies of the absorption and emission cross sections of the gain medium. Typically, to track the pump absorption within the crystal, an average absorption coefficient is applied via a raytracing technique. The outcome, therefore, is an approximation of the pump absorption profile that is independent of the temperature profile within the gain medium. Here an iterative algorithm involving raytracing and Finite Element Analysis (FEA) is demonstrated in the simulation of neodymium(Nd) and ytterbium(Yb) doped yttrium aluminium garnet(YAG) single crystal fiber (SCF) gain media. The algorithm calculates the local temperature, associated absorption coefficient and hence temperature-dependent pump absorption. This allows for a more accurate determination of the distributions of the calculated population inversion and temperature in the crystal. The temperature dependence of the emission spectra can then be taken into account as well, which defines the achievable gain of the amplifying media. The resulting calculations’ influence on the simulated output beam quality and gain for these active media is presented.

Background: To enable the manufacturing of advanced semiconductor devices, EUV lithography has been continuously shrinking the lateral dimensions of the mask and features. Resulting complex diffraction, polarization, and oblique illumination effects require rigorous modeling of EUV light diffracted from the mask. Traditional electromagnetic field (EMF) solvers are inefficient for large field-of-view simulations, while deep neural networks rely on a huge amount of expensive rigorously simulated or measured data. [1] Aim: Building upon our prior research [2], which revealed the PINN’s potential and enabled sufficient aerial image simulation of small features, this study aims to broaden the scope of PINN’s applications. Specifically, we extend this work towards the investigation of polarization effects and variable illumination settings. Approach: The established PINN model [2] was employed for EUV mask simulations under various illumination directions to investigate the orientation dependence of lithographic patterning. Expressing the residual of 3D Maxwell’s equations, we effectively decoupled the transverse electric (TE) and transverse magnetic (TM) modes of EUV light. Employing a vectorial formulation of the wave equation, we investigated the ability of the PINN approach to predict the generation of additional electric field components resulting from the scattering at the absorber edges. Results: PINN accurately predicts the polarization effects that are relatively small, but still notable close to the absorber edges and inside the multilayer. The generalized PINN-based solver, adapted for arbitrary illumination settings, demonstrates the significant impact of the illumination direction and exposure wavelength on the reflected EUV light. PINN captures asymmetries in the near field caused by off-axis illumination and the significant drop in the intensity of the reflected light for larger incidence angles. Conclusions: By pushing the application limits of the existing PINN approach, we demonstrated its capability to accurately model oblique illumination effects, polychromatic effects, and even the weak polarization effects in the EUV spectral range. Different from numerical solvers, a universal PINN-based mask solver can simulate light scattering response in several milliseconds for arbitrary mask geometries and illumination settings without re-training.

In this work, we present a method for characterizing the transmission matrices of complex scattering media using a physics-informed, multi-plane neural network (MPNN) without the requirement of a known optical reference field. In contrast to previous techniques, our method is able to measure complete information about the transmission matrix, which is necessary for coherent control of light through a complex medium. Here, we design a neural network that describes the exact physical apparatus consisting of a trainable layer describing the unknown transmission matrix. We then employ randomized measurements to train the neural network which accurately recovers the transmission matrix of a commercial multi-mode fiber. We demonstrate how our method is significantly more accurate, and noise-robust than the standard method of phase-stepping holography and show how it can be generalized to characterize a cascade of transmission matrices. This work presents an essential tool for accurate light control through complex media, with applications ranging from classical optical networks, biomedical imaging, to quantum information processing.

Designing large-area meta-surfaces is a daunting numerical task. The sub-wavelength size of the individual meta-atoms requires a full-wave solver for Maxwell’s equations. Practical meta-surfaces need to have an active area on the order of 1 mm² or above. These sizes are orders of magnitude larger than what is feasible using known full-wave algorithms both in available memory and time requirements. Traditionally, approximations are made to design meta-surfaces of mm² size and above. Recently large area meta-surface fabrication has been shown. With this capability, the demand for large area meta-surface design (>1000 λ) continues to increase. In this paper we present overlapping domain analysis (ODA) as a novel approach to model large area meta-surfaces with higher accuracy than the local periodic approximation (LPA) but capable of larger areas than rigorous full-wave calculations. We compare the effect of the approximation chosen on the simulated performance of the lens for various numerical apertures.

Electromagnetic metasurfaces have shown immense potential for wave control in diverse frequency regimes ranging from radio frequencies to the visible. In visible frequencies, materials with low loss and the ability to tightly confine light (high-index dielectrics, plasmonic metals) become limited. Optical metasurfaces are additionally challenging from a practical point of view, since they require nanofabrication techniques with high resolution and precision. Here, we consider polymer-based optical metasurfaces to be fabricated with two-photon lithography, which is a fast, scalable and cost-effective nanofabrication technique. We focus on a beam steering scenario, which is the archetypical example of wavefront manipulation functionalities. The proposed design operates in transmission and the principle of operation is based on phase accumulation within short vertical waveguide segments. We start from idealized, perfectly-cylindrical meta-atom shapes, which are typically studied in the literature, and proceed to conical shapes which exhibit increased mechanical stability and smooth half-ellipsoid-like structures that are compatible with the voxels of the laser writing process. We show that the adopted realistic meta-atom shapes lead to only a small deterioration of the steering performance and by employing numerical optimization we are able to recover the performance obtained with the idealized meta-atom shapes. Our work aspires to enable high-performance, practical optical metasurfaces taking fabrication limitations and particularities thoroughly into account.

In recent years, metasurfaces have emerged as promising components for reducing the size and complexity of optical imaging systems. Nevertheless, their incorporation into these systems remains a challenge due to the difference between the numerical tools used in the design of conventional imaging systems (ray tracing) and the design of metasurfaces (full-wave solvers). In this paper, we describe a methodology that combines the local periodicity approximation and a free space propagation technique to rapidly compute the optical response of a large-scale metasurface. We then explain the coupling of this fast solver with a ray tracer to accurately simulate an optical system containing a metasurface.

Metasurfaces have become a key focus in research and are applied in numerous fields because of their exceptional capability to control electromagnetic waves across microwave to optical frequencies. These artificial sheet materials have the advantages of lightweight and ability to control wave propagation both on the surface and in the surrounding free space. The complexity of fabricating metasurfaces via two-photon lithography (TPL) is addressed through sophisticated modeling. Critical to the success of TPL is the ability to predict the effects of the fabrication process on the final product. This paper introduces three distinct modeling approaches that vary in complexity and predictive capabilities. We evaluate the performance and limitations of a simple threshold model, a compact model and a full model of polymerization. Through application examples, we demonstrate how these models can guide the fabrication of metasurfaces.

Diffractive neural networks (DNNs) are an emerging design method for systems of cascaded phase masks, where the optical system is treated as an all-optical neural network. In previous work, we have demonstrated how this method can be used to design highly flexible beam shaping systems. We have also shown that DNNs can be used to correct pixel crosstalk and direct reflection in a spatial light modulator based on liquid crystal on silicon. Here, we extend the correction of these effects to two cascaded spatial light modulators and demonstrate the resulting increase in accuracy of the three-dimensional beam shaping capabilities of DNNs.

Developing optical systems, particularly those consisting of spherical lenses, is relevant for various applications such as lithographic scanners and metrology equipment. The design process of an optical system typically involves the optimization of specific objectives to ensure the best performance. As a common example of such an objective, we consider the problem of determining the lens curvatures that result in a sufficiently small root mean square (RMS) spot size. Optimization algorithms are commonly employed to solve this problem by heuristically eliminating sub-optimal optical designs. This class of algorithms includes the damped least squares (DLS) widely applied in commercial software and advanced methods like Saddle Point Construction. However, within a restricted computational budget, these optimizers are limited in exploring potentially promising novel solutions since they heavily rely on the initial specific designs that must conform to complex or unknown requirements. In this work, we address the considered problem with a modified Hill-Valley Evolutionary Algorithm (HillVallEA), which proved itself as one of the best state-of-the-art metaheuristics for multimodal black-box optimization. We demonstrate that our algorithm locates a diverse set of high-quality optical designs with four lenses in a single run even when initialized with random starting curvatures. This is the first result in this domain when an optimization algorithm that does not take specific optical properties into account can still generate relevant and high-performing optical systems. Furthermore, we show the benefits of the proposed methodology for the diversity of the obtained set of solutions, while maintaining a solution of the same quality as the one found by the most prominent algorithm in the domain. We provide analyses of the obtained solutions according to: 1) tolerance to the alignment of lenses, 2) susceptibility to small variations of lens curvatures.

I discuss how light propagation, both wave and ray dual aspects, can be implemented and its origin within a Feynman path integral approach. This can be done for both scalar fields and the full vectorial field descriptions of classical electromagnetism as applied to imaging problems. A key part of this scheme is in generalising the standard optical path length integral from a scalar to a matrix quantity. Reparametrization invariance along rays allows a covariant formulation where propagation can take place along a general curve. The current programme then gives a practical realisation of both gauge invariance and differential geometry concepts. As a specific example, a general gradient index (GRIN) rod fiber background is used to demonstrate the scheme. Calculations such as the evaluation of the Gouy phase, and parallel transport of states of polarisation provide examples of applicability of the scheme. As a particular noteworthy example and application, I show how the current approach allows for the evaluation of observable effects in GRIN lens cascades where additionally there is a spatially varying birefringence. This is a prime candidate for a perturbative Feynman diagram evaluation since the birefringence is much smaller than the bulk refractive index.

In our work we develop an idea for the analytical treatment of discontinuities within the Fourier space methods for solving the electromagnetic diffraction problem, and demonstrate the reformulated Fourier Modal Method as applied to 1D and 2D periodic structures. The obtained formulations replace the need in the Li’s factorization rules to operate only on unknown Fourier vectors of continuous functions, and allow for the natural computations of the inner fields free from the Gibbs phenomenon for any number of harmonics. In addition, the new formulations appear to be free of intermediate matrix inversions paving the way for the application of modern powerful methods of numerical linear algebra.

Single-pixel imaging (SP) uses coded aperture (CA) elements to capture multiple spatially modulated versions of a scene in a single detector. In real SP implementations, spatial light modulator (SLM) devices are employed to generate the CA modulations. To obtain noiseless discrete images from the SP measurements, it is required to oversample the number of pixels in the objective image. Alternatively, by exploiting compressive sensing theory and designed CA patterns, the SLM-based SP system reduces the projections needed for quality reconstructions, where the CA patterns are established with the aim of emulating orthonormal bases that minimize the correlation between the shots. Nevertheless, in practice, the frame rate of the SP system is restricted by the SLM device, which limits real-time applications. To overcome this, the SLM-based patterns are replaced by etching CA structures over a circularly shifted mask (S-CA), which are introduced in the SP optical path for higher frame rate acquisition. Yet these S-CA patterns present correlated shift modulations and, in turn, yield inaccurate reconstructions. This work introduces an iterative strategy for designing the spatial S-CA pattern structure in SP imaging. The proposed method determines the spatial entries of the S-CA by minimizing the correlation between the pattern shifts, in which the quantity and step size of the S-CA displacements are restricted. Numerical simulations using the proposed design demonstrate an improvement in terms of peak signal-to-noise ratio (PSNR) of up to 2.5 dB, when compared to non-designed CA-S structures, in a compression ratio of 0.25.

In numerous applications within laser material processing and various other disciplines, achieving a specific irradiance distribution is a frequent objective. By optimizing the parameters of an optical system, light can be redirected to attain the desired irradiance distribution. In gradient descent-based approaches, a major challenge involves accurately and efficiently computing the objective function's gradient concerning these parameters. Algorithmic differentiable ray tracing provides a promising approach for this challenge. To calculate the gradient of the objective function, we derive a new mathematical expression that applies to a wide range of optical systems and can be evaluated using algorithmic differentiable ray tracing and automatic differentiation techniques. This novel methodology for calculating the gradient of the objective function is both computationally efficient and robust in its applicable domain. To validate our approach, we additionally provide numerical simulation results.

Temporal snapshot compressive imaging (SCI) allows high-dimensional temporal images to be reconstructed from a two-dimensional (2D) set of measurements. This is valuable for capturing color-polarized video data that can be used for robust material classification, considering that each material has a unique behavior in the way it polarizes the reflected light. In contrast to conventional commercial video cameras, which often compromise spatial, color, or polarization resolution to accommodate more information in the sensor, the SCI paradigm exploits optics, electronics and algorithms to produce high-resolution high-dimensional imaging from far fewer measurements. Commercial cameras can be adapted to capture additional information beyond their conventional sensing range when integrated with the SCI framework. This is achieved by incorporating an intensity modulation element that encodes and compress the data, and prevents incoherent sampling for nonlinear reconstruction based on compressive sensing principles. In this paper, an off-the-sheld camera is modified to compressively acquire and reconstruct high resolution spatio temporal polarization and color data from 2D measurements, leading to color-polarized video.The sensor camera uses a Bayer and a polarization filter superimposed on each other, aka RGB-P sensor. Then, a time-based designed coded aperture (CA) is incorporated into the optical path to temporally modulate each Bayer-polarized frame, where the modulated frames are integrated into a single measurement in the sensor. The CA is built with spatiotemporal block-unblock elements that encodes the information, in which its design restricts the distribution of those elements across the time dimension for reducing the temporal measurements redundancy, and, in turn, leading to better reconstructions. The compressed color-polarized video measurements are then recovered by using the alternating direction method of multipliers (ADMM) reconstruction algorithm. Numerical experiments show that temporal designed CA patterns outperforms random CA structures in terms of PSNR (Peak signal-to-noise ratio) and SSIM (structural similarity index measure), providing better-quality reconstructions of a color-polarized video from a dynamic scene.

LiDAR's shorter wavelength allows high-resolution imaging, making it preferable for environmental pollutant monitoring. By detecting and tracking aerosols and various pollutants in the air, sources of pollution and pollution levels can be determined in real-time. However, conventional optics based LiDAR systems face several challenges that result in LiDAR systems being very expansive. It is essential to overcome these challenges before widespread adoption can be achieved for large scale environmental monitoring using LiDAR. This review paper presents diffractive optical elements (DOEs) as a key enabler to overcome them. By manipulating laser beam characteristics and achieving tailored LiDAR beam profiles using DOEs, the sensitivity, the spatial resolution, and pollutant discrimination capability of LiDAR system is improved.

Augmented Reality (AR) and Virtual Reality (VR) display for STEM education integrate advanced optical technology with immersive learning experiences. Optical Ray Tracing software serves as the primary platform for designing these educational tools. These softwares help to assess system performance and correct optical distortions, enabling the creation of diverse STEM educational modules. Microlens Array (MLA) based AR/VR displays provide immersive, hands-on learning opportunities and foster deeper understanding. The precise selection of MLA parameters influences critical aspects such as image clarity and field of view. In this study, we have designed an MLA in Zemax Opticstudio for the sake of using in AR/VR displays. We have studied the physical properties like 2D and 3D layouts and surface profile of MLA. We have also analyzed the optical properties, including ray propagation, spot diagram, and illumination. Furthermore, a comparative analysis of the optical performance of 7 × 7 and 11 × 11 MLA arrays in a 5 × 5 mm² area is also incorporated.

Microscopes are an essential optical instrument for diagnostic purposes. Now, AI is included in these diagnostic processes with microscopes which has revolutionized this area of field. Diagnostic processes have become more accurate, efficient and less time consuming for pathologists and patients as well. This paper provides a detailed review of artificial intelligence (AI) enabled microscopy for diagnostic applications. Latest advancements in AI enabled microscopes are discussed, focusing on their applications in medical diagnostics. The review come up with a range of microscopy techniques and how AI algorithms help in real-time image analysis, recognition of abnormalities, and disease prediction. Moreover, challenges and opportunities associated with these smart microscopes are also determined. The purpose of this paper is to serve as a valuable resource for researchers, clinicians, and technologists who are working on AI-enabled microscope designs for diagnostic applications.

The article analyzes the tourism business in conditions of increased risk of emergencies of natural and artificial nature and the involvement of medical and preventive measures to maintain the population's health (flora, fauna) in critical situations. Exploring the Earth from space - remotely using Earth remote sensing (ERS) methods - objectively monitors the dynamics of changes in the resource potential of the tourism component of the country's modern economy. The purpose of the work is to use technologies for remote sensing of the Earth in recreational areas with subsequent socio-economic analysis to reduce the resource potential in the tourism business in conditions of deteriorating ecology of the territories, using the decoding of space images from the perspective of the synthesis of orthogonal systems with predetermined properties (calculation speed, order of transformation, etc.). The work uses the technique of discrete orthogonal transformations.

The article proposes a technology for operating an automatic space monitoring system for the presence of waste disposal sites. The technology is based on the ideas of stochastic geometry, as well as geometric probability and covariograms. The paper proposes an algorithm based on the trace transform using discrete orthogonal transforms to minimize the feature space. The problem of developing a trace matrix and selecting informative features using the stochastic geometry method for finding waste disposal sites from high-resolution satellite images is studied using the orthogonal transformations apparatus. The proposed methodology is tested using space images depicting waste disposal sites.

Optical wireless communication (OWC) or free space optical (FSO) communication systems transmit information through the atmosphere using light beams in the visible or near-infrared (NIR) spectrum. Since the radio frequency spectrum is overwhelmed and unable to meet the key performance indicators of FSO communication, high data rates can be provided by communicating over the visible or NIR spectrum. In this study, we have proposed a complementary metal-oxide semiconductor (CMOS) compatible all-silicon spin-encoded metalens that offers several key advantages for FSO communication applications. Firstly, it can be flawlessly merged with CMOS electronic devices, enabling the development of miniature-sized and cost-effective FSO communication systems. Secondly, due to silicon's high refractive index and all-silicon design, the proposed metalens offer effective light focusing and manipulation. Moreover, silicon is opted for because it is a transparent material for the visible and NIR spectrum, hence making it an appropriate choice for manufacturing a device for the application of efficient FSO communication. Furthermore, the all-silicon design of metalens makes it possible to be seamlessly integrated with other silicon-based photonic elements, including waveguides, modulators, and detectors. Our proposed CMOS, compatible with all silicon spin-encoded metalens, is an ultra-compact design that is capable of providing dual focal points simultaneously and transmitting different messages to different users at run time. We have designed and simulated a 60 µm × 60 µm all-silicon spin-encoded metalens and acquired two focal points by shining the linearly polarized light. Metalens inclusion within the FSO communication system opens new avenues for next-generation OWC, offering better focusing of light beams, enhancing the signal intensity, and escalating the overall communication range.