Imaging Lens Research Articles

Strong gravitational lensing’s ‘external shear’ is not shear

ABSTRACT The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power-law plus ‘external shear’, which notionally accounts for neighbouring galaxies and cosmic shear along our line of sight. A small amount of external shear could come from these sources, but we show that the vast majority does not. Except in a handful of rare systems, the best-fitting values do not correlate with independent measurements of line-of-sight shear: from weak lensing in 45 Hubble Space Telescope images, or in 50 mock images of lenses with complex distributions of mass. Instead, the best-fit external shear is aligned with the major or minor axis of 88 per cent of lens galaxies; and the amplitude of the external shear increases if that galaxy is discy. We conclude that ‘external shear’ attached to a power-law model is not physically meaningful, but a fudge to compensate for lack of model complexity. Since it biases other model parameters that are interpreted as physically meaningful in several science analyses (e.g. measuring galaxy evolution, dark matter physics or cosmological parameters), we recommend that future studies of galaxy-scale strong lensing should employ more flexible mass models.

A multi-strategy improved rime optimization algorithm for three-dimensional USV path planning and global optimization

The RIME optimization algorithm (RIME) represents an advanced optimization technique. However, it suffers from issues such as slow convergence speed and susceptibility to falling into local optima. In response to these shortcomings, we propose a multi-strategy enhanced version known as the multi-strategy improved RIME optimization algorithm (MIRIME). Firstly, the Tent chaotic map is utilized to initialize the population, laying the groundwork for global optimization. Secondly, we introduce an adaptive update strategy based on leadership and the dynamic centroid, facilitating the swarm's exploitation in a more favorable direction. To address the problem of population scarcity in later iterations, the lens imaging opposition-based learning control strategy is introduced to enhance population diversity and ensure convergence accuracy. The proposed centroid boundary control strategy not only limits the search boundaries of individuals but also effectively enhances the algorithm's search focus and efficiency. Finally, to demonstrate the performance of MIRIME, we employ CEC 2017 and CEC 2022 test suites to compare it with 11 popular algorithms across different dimensions, verifying its effectiveness. Additionally, to assess the method's practical feasibility, we apply MIRIME to solve the three-dimensional path planning problem for unmanned surface vehicles. Experimental results indicate that MIRIME outperforms other competing algorithms in terms of solution quality and stability, highlighting its superior application potential.

Exit wave reconstruction of a focal series of images with structural changes in high-resolution transmission electron microscopy.

High-resolution transmission electron microscopy (HRTEM) images can capture the atomic-resolution details of the dynamically changing structure of nanomaterials. Here, we propose a new scheme and an improved reconstruction algorithm to reconstruct the exit wave function for each image in a focal series of HRTEM images to reveal structural changes. In this scheme, the wave reconstructed from the focal series of images is treated as the initial wave in the reconstruction process for each HRTEM image. Additionally, to suppress noise at the frequencies where the signal is weak due to the modulation of the lens transfer function, a weight factor is introduced in the improved reconstruction algorithm. The advantages of the new scheme and algorithms are validated by using the HRTEM images of a natural specimen and a single-layer molybdenum disulphide. This algorithm enables image resolution enhancement and lens aberration removal, while potentially allowing the visualisation of the structural evolution of nanostructures.

Extended-depth-of-field imaging with an ultra-thin folded lens

Optical systems with extended depth of field (EDOF) are crucial for observation and measurement applications, where achieving compactness and a substantial depth of field (DOF) presents a considerable challenge with conventional optical elements. In this paper, we propose an innovative solution for the miniaturization of EDOF imaging systems by introducing an ultra-thin annular folded lens (AFL). To validate the practical feasibility of the theory, we design an annular four-folded lens with an effective focal length of 80.91 mm and a total thickness of only 8.50 mm. Simulation results show that the proposed folded lens has a DOF of 380.55 m. We further developed an AFL-based test system exhibiting a resolution of 0.11 mrad across a wide wavelength range of 486–656 nm. Additionally, we present experimental results from a miniature compact prototype, which further highlights the promising potential of folded lenses for long-range EDOF imaging.

Optical-digital joint design of multi-order diffractive lenses for lightweight high-resolution computational imaging

Multi-order diffraction lenses can focus different wavelengths at the same focal point by utilizing various diffraction orders. However, due to material dispersion, the focal position shifts when the incident wavelength moves away from the primary wavelength, resulting in limited spectral bandwidth. This paper presents a computationally optimized multi-order diffractive lens design and a related image reconstruction algorithm, enabling broadband high-resolution imaging with a single element. We introduce a new type of lens, the Spectral Multi-Order Diffractive Lens (SMODLs), which redistributes the energy across different diffractive orders to achieve relatively high focusing performance within specified wavelength bands. Subsequently. The relatively sharp spectral images generated by SMODL within these specified bands serve as priors for reconstructing images across the full spectrum. A prototype lens with a 40 mm aperture and a 320 mm focal length was designed and fabricated. The prior images' wavebands were designated as 525 nm to 575 nm and 675 nm to 725 nm, with peak Strehl ratios of 0.47 and 0.35, respectively. Finally, grayscale images within the 500∼800 nm wavelength range were reconstructed. Experimental results confirm the effectiveness of our approach, achieving high-resolution imaging across a 300 nm bandwidth with a single diffractive element.

Multi-Strategy Improved Dung Beetle Optimization Algorithm and Its Applications.

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed "Mean Differential Variation", to enhance the algorithm's ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems.

Printing, Characterizing, and Assessing Transparent 3D Printed Lenses for Optical Imaging

AbstractHigh‐quality lens production has involved subtractive manufacturing methods for centuries. These methods demand specialist equipment and expertise that often render custom high‐grade glass optics inaccessible. A low‐cost, accessible, and reproducible method is developed to manufacture high‐quality three dimensional (3D) printed lenses using consumer‐grade technology. Various planoconvex lenses are produced using a consumer‐grade 3D printer and low‐cost spin coating setup, and printed lenses are compared to commercial glass counterparts. A range of mechanical and optical methods are introduced to determine the surface quality and curvature of 3D printed lenses. Amongst others, high‐resolution interference reflection microscopy methods are used to reconstruct the convex surface of printed lenses and quantify their radius of curvature. The optical throughput and performance of 3D printed lenses are assessed using optical transmissivity measurements and classical beam characterization methods. It is determined that 3D printed lenses have comparable curvature and performance to commercial glass lenses. Finally, the application of 3D printed lenses is demonstrated for brightfield transmission microscopy, resolving sub‐cellular structures over a 2.3 mm field‐of‐view. The high reproducibility and comparable performance of 3D printed lenses present great opportunities for additive manufacturing of bespoke optics for low‐cost rapid prototyping and improved accessibility to high‐quality optics in low‐resource settings.

Foveated pancake lens design for improved optical performance and eye rotation support.

We propose a novel, to our knowledge, approach to address the limitations of traditional pancake lenses for virtual reality headsets, such as low image contrast and poor performance when eyes rotate. The design leverages the foveated nature of human vision, achieving a superior modulation transfer function in the foveal area to enhance optical performance significantly. Furthermore, the pancake lens design is presented that considers the rotation of the user's pupil position, maintaining optimal image quality even when the user's eye rotates. The proposed method presents the parameters and optimization of a novel pancake lens that utilizes the characteristics of the human visual system and accounts for the rotation of the pupil position of the user, leading to improvements in image quality and user experience. The lens design and image simulation results are presented to demonstrate the effectiveness of the approach.

Grayscale two-photon 3D printed gradient-refractive-index metamaterial lens for dual-band mid-infrared imaging

Gradient refractive index (GRIN) metamaterial lenses can achieve multi-band fusion infrared imaging and has the characteristics of integration, light weight, and achromaticity, compared with existing curved refractive lenses group. Constructing a three-dimensional (3D) GRIN lens for dual-band (3.0–5.0 and 7.5–9.2 µm) mid-infrared imaging is challenging due to the difficulty of fabricating the desired 3D GRIN materials with continuously changing linewidths. Here, we present a 3D self-focusing GRIN lens with a cylindrical symmetry configuration in the mid-infrared band. Such a 3D GRIN lens is designed with gradient woodpile polymer metamaterials based on effective medium theory and fabricated with high fidelity by grayscale two-photon lithography. Simulated and experimental results simultaneously exhibit a 3D GRIN lens possessing dual-band, achromatic, near-diffraction-limit focusing on the wavelengths of 4.5 and 7.5 µm. The protocol for developing the 3D GRIN lens with dual-band fusion imaging would prompt potential applications in integrated light-coupled devices and lightweight infrared imaging devices.

Ghost image analysis for pancake virtual reality systems

Pancake optics (also known as polarization-based catadioptric system) has been widely used as the imaging lens for virtual reality (VR) and mixed reality (MR) headsets because of its compact formfactor and excellent image quality. However, such a folded pancake optics not only dramatically lowers the optical efficiency to 25% because of the utilization of a half mirror, but also suffers from ghost images due to the stray light from multiple surface reflections and imperfect polarization control inside the optical system. In this paper, the origins including the light paths of the ghost images are explored by experiment and then analyzed by simulation. The effect of different incident angles on the intensity of each ghost is also investigated.

Comparison of baseline cataract rates in AB and TL wildtype zebrafish strains

Zebrafish are an outstanding model for assessing the involvement of genes in paediatric cataracts. Gene discovery for cataracts is enhanced by manipulation of the genome of zebrafish embryos and comparing the phenotypes of mutant progeny with the wildtype embryos. However, wildtype laboratory fish can also develop cataracts, potentially confounding the results. In this study, we compared the baseline cataract rate between two commonly used wildtype laboratory strains, AB and TL, and also an outbred transgenic line with mCherry reporter. We assessed a total of 805 lens images of fish at 4 days post-fertilisation for cataracts and scored each cataract observed as mild, moderate or severe. We found that the AB strain had a cataract rate of 16.2%, TL had 8.9%, and mCherry had 0.7% and these rates were significantly different. We found that TL strain had a lower rate of mild cataracts than AB fish, however, the rate of moderate and severe phenotypes in the AB and the TL strain was similar. Overall, we showed that the baseline cataract rate varies significantly between the strains housed in a single facility and conclude that baseline rates of cataracts should be assessed when planning experiments to assess the genetic causes of cataracts.

Prediction of Physical and Mechanical Properties of Heat-Treated Wood Based on the Improved Beluga Whale Optimisation Back Propagation (IBWO-BP) Neural Network

The physical and mechanical properties of heat-treated wood are essential factors in assessing its appropriateness for different applications. While back-propagation (BP) neural networks are widely used for predicting wood properties, their accuracy often falls short of expectations. This paper introduces an improved Beluga Whale Optimisation (IBWO)-BP model as a solution to this challenge. We improved the standard Beluga Whale Optimisation (BWO) algorithm in three ways: (1) use Bernoulli chaos mapping to explore the entire search space during population initialization; (2) incorporate the position update formula of the Firefly Algorithm (FA) to improve the position update strategy and convergence speed; (3) apply the opposition-based learning based on the lens imaging (lensOBL) mechanism to the optimal individual, which prevents the algorithm from getting stuck in local optima during each iteration. Subsequently, we adjusted the weights and thresholds of the BP model, deploying the IBWO approach. Ultimately, we employ the IBWO-BP model to predict the swelling and shrinkage ratio of air-dry volume, as well as the modulus of elasticity (MOE) and bending strength (MOR) of heat-treated wood. The benefit of IBWO is demonstrated through comparison with other meta-heuristic algorithms (MHAs). When compared to earlier prediction models, the results revealed that the mean square error (MSE) decreased by 39.7%, the root mean square error (RMSE) by 22.4%, the mean absolute percentage error (MAPE) by 9.8%, the mean absolute error (MAE) by 31.5%, and the standard deviation (STD) by 18.9%. Therefore, this model has excellent generalisation ability and relatively good prediction accuracy.

Повесть И. С. Тургенева «Первая любовь»: на границах идиллии

The paper is dedicated to analysing Ivan Turgenev’s novella “First Love” (1860), which has not undergone detailed philological scrutiny before. The research aims to identify the border phenomena of the idyllic discourse and its specificity. The scientific novelty of the paper lies in examining the boundaries of the idyllic through the analysis of characters, chronotopes, and the motif system in the novella. The research findings revealed that in Turgenev’s work, all types of idyll – rural, familial, and romantic – are seemingly present, but they are only represented at the level of genre-specific features (beautiful nature, youthful age, first love). The novella represents a recollection, reflection, a turn to the “golden age” of the hero’s youth, his first infatuation, thus demonstrating elegiac traits. Through the lens of idyllic images, motifs, and details of the chronotope, their quasi-significance is seen. Semantic signs (the garden, linden trees, alleys) serve as substitutes for unrequited love. Details of “locus amoenus” are merely symbols linking the author’s work to the idyllic tradition, but in reality, they deviate from reader expectations and demonstrate the opposite of an idyllic world perception.

BCLA CLEAR Presbyopia: Evaluation and diagnosis

It is important to be able to measure the range of clear focus in clinical practice to advise on presbyopia correction techniques and to optimise the correction power. Both subjective and objective techniques are necessary: subjective techniques (such as patient reported outcome questionnaires and defocus curves) assess the impact of presbyopia on a patient and how the combination of residual objective accommodation and their natural DoF work for them; objective techniques (such as autorefraction, corneal topography and lens imaging) allow the clinician to understand how well a technique is working optically and whether it is the right choice or how adjustments can be made to optimise performance. Techniques to assess visual performance and adverse effects must be carefully conducted to gain a reliable end-point, considering the target size, contrast and illumination. Objective techniques are generally more reliable, can help to explain unexpected subjective results and imaging can be a powerful communication tool with patients. A clear diagnosis, excluding factors such as binocular vision issues or digital eye strain that can also cause similar symptoms, is critical for the patient to understand and adapt to presbyopia. Some corrective options are more permanent, such as implanted inlays / intraocular lenses or laser refractive surgery, so the optics can be trialled with contact lenses in advance (including differences between the eyes) to better communicate with the patient how the optics will work for them so they can make an informed choice.

The Influence of CG Technology on The Aesthetics of Chinese Magic Films Take The Candle in The Tomb Film Series for Example

This study aims to investigate the impact of computer-generated imagery (CG) on the aesthetic context and innovation of oriental gods and creatures in Chinese magical film footage. This study focuses on the analysis and research of CG technology in Chinese magical film lens images, as well as the aesthetic habits and aesthetic psychology of contemporary audiences towards oriental gods and creatures. This research employs a qualitative research approach because it is appropriate for examining the cultural background and aesthetic habits of Chinese magical film lens images created using CG technology, as well as the aesthetic emotions that the film evokes in its audience. This study specifically examines the aesthetic expression and breakthrough innovation of oriental gods and monsters in the CG screen effects of the film series Candle In The Tomb, as well as the operation process of Chinese magical film CG technology and its expression based on and the generative context and breakthrough innovation of oriental gods' aesthetic style. This study will provide a theory of the CG technology used to guide the visual aesthetics of Chinese fantasy films. It will benefit creators of Chinese magic films, researchers, academicians, students, and those interested in the subject's study and preservation.

Enhanced chimp hierarchy optimization algorithm with adaptive lens imaging for feature selection in data classification

Feature selection is a critical component of machine learning and data mining to remove redundant and irrelevant features from a dataset. The Chimp Optimization Algorithm (CHoA) is widely applicable to various optimization problems due to its low number of parameters and fast convergence rate. However, CHoA has a weak exploration capability and tends to fall into local optimal solutions in solving the feature selection process, leading to ineffective removal of irrelevant and redundant features. To solve this problem, this paper proposes the Enhanced Chimp Hierarchy Optimization Algorithm for adaptive lens imaging (ALI-CHoASH) for searching the optimal classification problems for the optimal subset of features. Specifically, to enhance the exploration and exploitation capability of CHoA, we designed a chimp social hierarchy. We employed a novel social class factor to label the class situation of each chimp, enabling effective modelling and optimization of the relationships among chimp individuals. Then, to parse chimps’ social and collaborative behaviours with different social classes, we introduce other attacking prey and autonomous search strategies to help chimp individuals approach the optimal solution faster. In addition, considering the poor diversity of chimp groups in the late iteration, we propose an adaptive lens imaging back-learning strategy to avoid the algorithm falling into a local optimum. Finally, we validate the improvement of ALI-CHoASH in exploration and exploitation capabilities using several high-dimensional datasets. We also compare ALI-CHoASH with eight state-of-the-art methods in classification accuracy, feature subset size, and computation time to demonstrate its superiority.

Electrically tunable virtual image Luneburg lens using graphene.

Virtual image lenses play essential roles in various optical devices and applications, including vision correction, photography, and scientific instruments. Here, we introduce an approach for creating virtual image Luneburg lenses (LL) on graphene. Remarkably, the graphene plasmonic lens (GPL) exhibits electrically tunable virtual focusing capabilities. The design principle of the tunability is based on the nonlinear relationship between surface plasmon polariton (SPP) wave mode index and chemical potential of graphene. By controlling the gate voltage of graphene, we can achieve continuous tuning of virtual focus. A ray-tracing technique is employed to determine the required gate voltages for various virtual focal lengths. The proposed GPL facilitates adjustable virtual focusing, promising advancements in highly adaptive and transformative nanophotonic devices.

Three Prenatal Developments in the Retina Allow for Cortico-Retinal Image Processing in Situ in the Eye

Image processing in the retina of the eye has thus far been mainly dealt with analogous to photographic ray optics i. e., imaging lens optics and photodiode arrays. However, it does not offer an answer to the questions that are crucial to human vision: WHAT a visible object invariantly represents conceptually (a house, a tree, etc.), WHERE it is located in relation to other objects in space or which RGB-colors and/or luminosities collaborate locally. For this purpose, ray optics needs to be supplemented by diffractive wave optics, which can be described as Fresnel near-field interference in cellular or spatial gratings. The fact that interference optics plays a decisive role in vision has already been proven by the fact that in binocular vision the image brightness is preserved when closing one eye. However, with the introduction of interference-wave-optics and especially with Fresnel Nearfield interference optics the cortico-retinal image processing now becomes possible in the eye, i.e. in the retina of the peripheral visual organ. Fresnel Nearfield interference optics especially allows multilayer proceeding and a better understanding of hierarchical imaging systems. It clearly becomes apparent in the di- and trichromatic proceeding and by the separation of color proceeding from invariant object form proceeding. Color - as an example - is not produced at the visual objects and also not in the cortex, but in the Fresnel space of the retina.

Dynamic constitutive identification of concrete based on improved dung beetle algorithm to optimize long short-term memory model

In order to improve the accuracy of concrete dynamic principal identification, a concrete dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) optimized Long Short-Term Memory (LSTM) network is proposed. Firstly, the apparent stress–strain curves of concrete containing damage evolution were measured by Split Hopkinson Pressure Bar (SHPB) test to decouple and separate the damage and rheology, and this system was modeled by using LSTM network. Secondly, for the problem of low convergence accuracy and easy to fall into local optimum of Dung Beetle Algorithm (DBO), the greedy lens imaging reverse learning initialization population strategy, the embedded curve adaptive weighting factor and the PID control optimal solution perturbation strategy are introduced, and the superiority of IDBO algorithm is proved through the comparison of optimization test with DBO, Harris Hawk Optimization Algorithm, Gray Wolf Algorithm, and Fruit Fly Algorithm and the combination of LSTM is built to construct the IDBO-LSTM dynamic homeostasis identification model. The final results show that the IDBO-LSTM model can recognize the concrete material damage without considering the damage; in the case of considering the damage, the IDBO-LSTM prediction curves basically match the SHPB test curves, which proves the feasibility and excellence of the proposed method.

Staring X-ray backscatter imaging based on ultra-high aspect ratio lobster eye lens.

In contrast to conventional X-ray imaging systems, the lobster eye lens, serving as a pivotal component for X-ray focusing, presents the potential for downsizing X-ray backscatter imaging systems. This study reports the successful implementation of a pioneering non-contact staring X-ray backscatter imaging experiment, with the target positioned 1.5 meters away from the system and employing a tube voltage of 60 kV for the X-ray light source. The system is built upon a novel high aspect ratio (500) meridian lobster eye lens, employing a laboratory low illuminance desktop light source and a commercial X-ray detector to achieve high-resolution focused imaging of hard X-rays. Point spread function testing and a series of imaging experiments were carried out to assess the resolution and optimal imaging photon energy of the proposed system. Furthermore, according to the characteristics of the point spread function of the cross image of the lobster eye lens, we proposed an image processing algorithm. The experimental results demonstrate that, after processing, the Structural Similarity (SSIM) Index of the backscatter image and the ground truth image can be improved from an average of 0.0526 to 0.5758. Our research significantly contributes to the advancement of a new generation of X-ray backscatter imaging systems.