Light Lens Research Articles

Unveiling lens light complexity with a novel multi-Gaussian expansion approach for strong gravitational lensing

ABSTRACT In a strong gravitational lensing system, the distorted light from a source is analysed to infer the properties of the lens. However, light emitted by the lens itself can contaminate the image of the source, introducing systematic errors in the analysis. We present a simple and efficient lens light model based on the well-tested multi-Gaussian expansion (MGE) method for representing galaxy surface brightness profiles, which we combine with a semi-linear inversion scheme for pixelized source modelling. Testing it against realistic mock lensing images, we show that our scheme can fit the lensed images to the noise level, with relative differences between the true input and best-fitting lens light model remaining below 5 per cent. We apply the MGE lens light model to 38 lenses from the HST SLACS sample. We find that the new scheme provides a good fit for the majority of the sample with only 3 exceptions – these show clear asymmetric residuals in the lens light. We examine the radial dependence of the ellipticity and position angles and confirm that it is common for a typical lens galaxy to exhibit twisting non-elliptical isophotes and boxy / disky isophotes. Our MGE lens light model will be a valuable tool for understanding the hidden complexity of the lens mass distribution.

Applications of photodynamic therapy in keratitis.

Keratitis is corneal inflammatory disease which may be caused by several reason such as an injury, allergy, as well as a microbial infection. Besides these, overexposure to ultraviolet light and unhygienic practice of contact lenses are also associated with keratitis. Based on the cause of keratitis, different lines of treatments are recommended. Photodynamic therapy is a promising approach that utilizes light activated compounds to instigate either killing or healing mechanism to treat various diseases including both communicable and non-communicable diseases. This review focuses on clinically-important patent applications and the recent literature for the use of photodynamic therapy against keratitis.

Mass Reconstruction of Galaxy-scale Strong Gravitational Lenses Using a Broken Power-law Model

With mock strong gravitational lensing images, we investigate the performance of the broken power-law (BPL) model proposed by Du et al. () on the mass reconstruction of galaxy-scale lenses. An end-to-end test is carried out, including the creation of mock strong lensing images, the subtraction of lens light, and the reconstruction of lensed images, where the lenses are selected from the galaxies in the Illustris-1 simulation. We notice that, regardless of the adopted mass models (the BPL model or its special cases), the Einstein radius can be robustly determined from imaging data alone, and the median bias is typically less than 1%. Away from the Einstein radius, the lens mass distribution tends to be harder to measure, especially at radii where there are no lensed images detected. We find that, with rigid priors, the BPL model can clearly outperform the single power-law models by achieving <5% median bias on the radial convergence profile within the Einstein radius. As for the source light reconstructions, they are found to be sensitive to both lens light contamination and lens mass models, where the BPL model with rigid priors still performs best when there is no lens light contamination. We show that, by correcting for the projection effect, the BPL model can estimate the aperture and luminosity weighted line-of-sight velocity dispersions to an accuracy of ∼6% scatter. These results highlight the great potential of the BPL model in strong lensing related studies.

P‐57: Spatial Display System Based on Cylindrical Lens Technology

Compared with traditional two‐dimensional displays, three‐dimensional displays can bring users a more realistic visual experience. In recent years, with the development of naked eye 3D technology, users can completely get rid of the shackles of glasses and experience stereoscopic visual effects more freely. The 3D display technology based on the cylindrical lens is a vital technology branch in the field of stereoscopic display. The lens light splitting and eye tracking technology are used to ensure that the image taken into the human eye at any viewing angle has correct parallax, thus giving people a three‐dimensional feeling. BOE has accumulated numerous technologies in the display field, especially in the fields of high‐resolution display and new display. This paper focuses on the space reality display system independently developed by BOE.

Photometric redshift estimation of strongly lensed galaxies

Context.Around 105strongly lensed galaxies are expected to be discovered with upcoming wide-field surveys such asEuclidand the LSST. Utilising these large samples to study the inner structure of lens galaxies requires source redshifts, which are needed to turn lens models into mass measurements. However, obtaining spectroscopic source redshifts for large samples of strong lenses is prohibitive with the current capacity of spectroscopic facilities.Aims.As an alternative to spectroscopy, we study the possibility of obtaining source photometric redshifts (photo-zs) for large samples of strong lenses. We pay particular attention to the problem of blending between the lens and the source light.Methods.Our strategy consists of deblending the source and lens light by simultaneously modelling the lens galaxy and the background source in all available photometric bands, and then feeding the derived source colours to a template-fitting photo-zalgorithm. We describe the lens and the source light with a Sérsic profile, and the lens mass with a singular isothermal ellipsoid. We first test our approach on a simulated sample of lenses. Then, we apply it to 23 real systems with broad-band photometry from the Hyper Suprime-Cam survey.Results.We identify the deviations of the lens light from a Sérsic profile and the contrast between the lens and source image as the main drivers of the source colour measurement error. Although the former is challenging to measure directly for real lenses, we find the latter to be sufficient for evaluating the accuracy of a measured source colour. We split the real sample based on the ratio Λ of the lens to source surface brightness measured at the image locations. In the Λ &lt; 1 regime, the photo-zoutlier fraction is 20%, and the accuracy of photo-zestimation is limited by the performance of the template-fitting process. In the opposite regime, the photo-zoutlier fraction is 75%, and the errors from the source colour measurements dominate the photo-zuncertainty.Conclusions.Measuring source photo-zs for lenses with Λ &lt; 1 poses no particular challenges compared to the isolated galaxy case. For systems with significant lens light contamination, however, improvements in the description of the surface brightness distribution of the lens are required: a single Sérsic model is not sufficiently accurate.

Automated galaxy–galaxy strong lens modelling: No lens left behind

ABSTRACT The distribution of dark and luminous matter can be mapped around galaxies that gravitationally lens background objects into arcs or Einstein rings. New surveys will soon observe hundreds of thousands of galaxy lenses and current labour-intensive analysis methods will not scale up to this challenge. We develop an automatic Bayesian method, which we use to fit a sample of 59 lenses imaged by the Hubble Space Telescope. We set out to leave no lens behind and focus on ways in which automated fits fail in a small handful of lenses, describing adjustments to the pipeline that ultimately allows us to infer accurate lens models for all 59 lenses. A high-success rate is key to avoid catastrophic outliers that would bias large samples with small statistical errors. We establish the two most difficult steps to be subtracting foreground lens light and initializing a first approximate lens model. After that, increasing model complexity is straightforward. We put forward a likelihood cap method to avoid the underestimation of errors due to pixel discretization noise inherent to pixel-based methods. With this new approach to error estimation, we find a mean ∼1 per cent fractional uncertainty on the Einstein radius measurement, which does not degrade with redshift up to at least z = 0.7. This is in stark contrast to measurables from other techniques, like stellar dynamics and demonstrates the power of lensing for studies of galaxy evolution. Our PyAutoLens software is open source, and is installed in the Science Data Centres of the ESA Euclid mission.

INVESTIGATION OF GLOBOZOOSPERMIA’S MORPHOLOGICAL STRUCTURE AND DNA FRAGMENTATION IN OLIGOZOOSPERMIA CASES IN INFERTILE MALES

Total globozoospermia is diagnosed by the presence of 100% round-headed spermatozoa without acrosomes. It is still unclear whether patients whose ejaculate contains both normal and globozoospermic cells (partial globozoospermia) suffer from a variation of the same syndrome. Affected men may experience decreased fertility and even infertility. In some cases, an increased number of cells with DNA fragmentation has also been observed in patients with globozoospermia..In this study, standard semen analysis methods in accordance with WHO criteria were applied to infertile male patient groups consisting of 20 normozoospermic and 20 oligozoospermic individuals who were admitted to our clinic. Age, sperm parameters (volume, vitality, concentration, total motility and morphology) were determined and statistically analyzed in normozoospermic and oligozoospermic infertile men.Sperms were stained with the Eosin-Nigrosin method and were visualized under an immersion lens light microscope and evaluated for vitality. The slides were stained using sperm staining solutions with the Spermac technique and the sperms were evaluated morphologically. Sperm DNA fragmentation damage was evaluated by acridine orange staining method.Our results revealed that sperm morphological features (Kruger test) and sperm DNA fragmentation, obtained with various staining techniques, are important in the clinical approach to male infertility and ART methods, and should be used together.

Deep learning-based dental plaque detection on permanent teeth and the influenced factors

Objective: To develop an artificial intelligence system for detecting dental plaque on permanent teeth and find the influenced factors. Methods: Photos of the labial or buccal surfaces of the permanent teeth were taken by using an intraoral camera (1 280×960 pixels; TPC Ligang, Shenzhen, China) before and after applying the plaque-disclosing agent (Cimedical, Japan) in 25 volunteers [12 males, 13 femals, aged (23±3) years] recruided in accordance with the inclusion criteria from the students of Peking University School of Stomatology from October 2018 to June 2019. A total of 549 groups of photos were captured and then divided into a training dataset containing 440 groups of photos and a test dataset including 109 groups of photos. The scopes of teeth and dental plaque on photos were labeled using LabelMe (Windows 3.2.1, MIT, U S A). A DeepLab based deep learning system was designed for the intelligent detection of dental plaque on permanent teeth. The mean intersection over union (MIoU) was employed to indicate the detection accuracy. Matlab (Windows R2017a, MathWorks, U S A) was used to extract the plaque edge line of 109 groups of photos and to calculate the number of pixels for the measurement of the complexity of the plaque edge line. The percentage of dental plaque area was calculated. Multivariate linear regression was used to explore whether tooth site, plaque percentage, number of plaque edge line pixels and lens light spot location would influence the detection accuracy, of which P<0.05 was considered statistically significant. Results: The MIoU of the permanent tooth model was 0.700±0.191 when 440 photos were used for training and 109 photos were used for testing. In the regression model of significance test (P<0.05), the percentage of plaque and the number of pixels on the edge of plaque had significant influence on the accuracy of dental plaque detection. The standardized coefficient of the number of pixels of the plaque edge line is -0.289, and the standardized coefficient of the percentage of plaque is -0.551. Conclusions: In the present study, an artificial intelligence system was built to detect dental plaque area on tooth photos collected by family intraoral camera. The system showed the ability to detect the dental plaque of permanent teeth. The more complex the marginal line of dental plaque and higher the percentage of dental plaque are, the lower the accuracy of plaque recognition is.

Cataract Development by Exposure to Ultraviolet and Blue Visible Light in Porcine Lenses.

Background and Objectives: Cataract is still the leading cause of blindness. Its development is well researched for UV radiation. Modern light sources like LEDs and displays tend to emit blue light. The effect of blue light on the retina is called blue light hazard and is studied extensively. However, its impact on the lens is not investigated so far. Aim: Investigation of the impact of the blue visible light in porcine lens compared to UVA and UVB radiation. Materials and Methods: In this ex-vivo experiment, porcine lenses are irradiated with a dosage of 6 kJ/cm2 at wavelengths of 311 nm (UVB), 370 nm (UVA), and 460 nm (blue light). Lens transmission measurements before and after irradiation give insight into the impact of the radiation. Furthermore, dark field images are taken from every lens before and after irradiation. Cataract development is illustrated by histogram linearization as well as faults coloring of recorded dark field images. By segmenting the lens in the background’s original image, the lens condition before and after irradiation could be compared. Results: All lenses irradiated with a 6 kJ/cm2 reveal cataract development for radiation with 311 nm, 370 nm, and 460 nm. Both evaluations reveal that the 460 nm irradiation causes the most cataract. Conclusion: All investigated irradiation sources cause cataracts in porcine lenses—even blue visible light.

Development of a potent embryonic chick lens model for studying congenital cataracts in vivo

Congenital cataracts are associated with gene mutations, yet the underlying mechanism remains largely unknown. Here we reported an embryonic chick lens model that closely recapitulates the process of cataract formation. We adopted dominant-negative site mutations that cause congenital cataracts, connexin, Cx50E48K, aquaporin 0, AQP0R33C, αA-crystallin, CRYAA R12C and R54C. The recombinant retroviruses containing these mutants were microinjected into the occlusive lumen of chick lenses at early embryonic development. Cx50E48K expression developed cataracts associated with disorganized nuclei and enlarged extracellular spaces. Expression of AQP0R33C resulted in cortical cataracts, enlarged extracellular spaces and distorted fiber cell organization. αA crystallin mutations distorted lens light transmission and increased crystalline protein aggregation. Together, retroviral expression of congenital mutant genes in embryonic chick lenses closely mimics characteristics of human congenital cataracts. This model will provide an effective, reliable in vivo system to investigate the development and underlying mechanism of cataracts and other genetic diseases.

Investigation of Different Illumination Scenarios for the Evaluation of Thermally Cut Edges with Convolutional Neural Networks using a Mobile Device

In sheet metal production, the quality of a cut edge determines the quality of the cut itself. Quality criteria such as the roughness, the edge slope, and the burr height are of decisive importance for further application and quality determination. In order to be able to determine these criteria analytically, the depth information of the edge must be determined at great expense. The current methods for obtaining the depth information are very time-consuming, require laboratory environments and are therefore not suitable for a fast evaluation of the quality criteria. Preliminary work has shown that it is possible to make robust and accurate statements about the roughness of a cut edge based on images when using an industrial camera with a standard lens and diffuse incident light, if the model used for this purpose has been trained on appropriate images. In this work, the focus is on the illumination scenarios and their influence on the prediction quality of the models. Images of cut edges are taken under different defined illumination scenarios and it is investigated whether a comprehensive evaluation of the cut edges on the evaluation criteria defined in standards is possible under the given illumination conditions. The results of the obtained model predictions are compared with each other in order to make a statement about the importance of the illumination scenario. In order to investigate the possibility of a mobile low-cost evaluation of cut edges, cheap hardware components for illumination and a smartphone for image acquisition are used.

Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI)

Strong gravitationally lensed quasars provide a powerful means to study galaxy evolution and cosmology. We use CHITAH, which is an algorithm used to hunt for new lens systems, particularly lensed quasars, in the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP) S16A. We present 46 lens candidates, of which 3 are previously known. We select four high-grade candidates from CHITAH for spectroscopic follow-up observations, and include two additional lenses found by YATTALENS, an algorithm used to classify lensed galaxies. We obtain X-shooter spectra of these six promising candidates for lens confirmation and redshift measurements. We report new spectroscopic redshift measurements for both the lens and source galaxies in four lens systems. We apply the lens modeling software GLEE to model our six X-shooter lenses uniformly. Through our analysis of the HSC images, we find that HSCJ022622−042522, HSCJ115252+004733, and HSCJ141136−010216 have point-like lensed images, and that the lens light distribution is well aligned with the lens mass distribution within 6 deg. We estimate the fluxes of the lensed source emission lines using X-shooter spectra, and use line ratio as a diagnostic on the Baldwin-Phillips-Terlevich (BPT) diagram. As a result, we find that HSCJ022622−042522 has a probable quasar source based on the upper limit of the [N II] flux intensity. We also measure the FWHM of Lyα emission of HSCJ141136−010216 to be ∼233 km s−1, showing that it is a probable Lyman-α emitter.

The use of convolutional neural networks for modelling large optically-selected strong galaxy-lens samples

ABSTRACTWe explore the effectiveness of deep learning convolutional neural networks (CNNs) for estimating strong gravitational lens mass model parameters. We have investigated a number of practicalities faced when modelling real image data, such as how network performance depends on the inclusion of lens galaxy light, the addition of colour information, and varying signal-to-noise. Our CNN was trained and tested with strong galaxy–galaxy lens images simulated to match the imaging characteristics of the Large Synoptic Survey Telescope (LSST) and Euclid. For images including lens galaxy light, the CNN can recover the lens model parameters with an acceptable accuracy, although a 34 per cent average improvement in accuracy is obtained when lens light is removed. However, the inclusion of colour information can largely compensate for the drop in accuracy resulting from the presence of lens light. While our findings show similar accuracies for single epoch Euclid VIS and LSST r-band data sets, we find a 24 per cent increase in accuracy by adding g- and i-band images to the LSST r-band without lens light and a 20 per cent increase with lens light. The best network performance is obtained when it is trained and tested on images where lens light exactly follows the mass, but when orientation and ellipticity of the light are allowed to differ from those of the mass, the network performs most consistently when trained with a moderate amount of scatter in the difference between the mass and light profiles.

Sparse Lens Inversion Technique (SLIT): lens and source separability from linear inversion of the source reconstruction problem

Strong gravitational lensing offers a wealth of astrophysical information on the background source it affects, provided the lensed source can be reconstructed as if it was seen in the absence of lensing. In the present work, we illustrate how sparse optimisation can address the problem. As a first step towards a full free-form-lens-modelling technique, we consider linear inversion of the lensed source under sparse regularisation and joint deblending from the lens light profile. The method is based on morphological component analysis, assuming a known mass model. We show with numerical experiments that representing the lens and source light using an undecimated wavelet basis allows us to reconstruct the source and to separate it from the foreground lens at the same time. Both the source and lens light have a non-analytic form, allowing for the flexibility needed in the inversion to represent arbitrarily small and complex luminous structures in the lens and source. In addition, sparse regularisation avoids over-fitting the data and does not require the use of an adaptive mesh or pixel grid. As a consequence, our reconstructed sources can be represented on a grid of very small pixels. Sparse regularisation in the wavelet domain also allows for automated computation of the regularisation parameter, thus minimising the impact of the arbitrary choice of initial parameters. Our inversion technique for a fixed mass distribution can be incorporated into future lens-modelling techniques iterating over the lens mass parameters.

All-glass, lenticular lens light guide plate by mask and etch

All glass, lenticular lens array, light guide substrates were fabricated in a single mask and etch procedure enabling 1D local light-confinement from an edge-injected LED array. Lenticular structures of sufficient resolution (width & pitch: 100–200 µm) were etched along the length of the thin-slab glass surface, at depths in the range 40–90 µm using an etchant optimized for the alkali-borosilicate composition (Corning Iris Glass). These structures’ aspect ratio (W/H 80%) along the lenticular corridors. The all-glass and high-transmission nature of the iris glass composition enabled higher brightness operation and yielded negligible color-shift.

AutoLens: automated modeling of a strong lens’s light, mass, and source

This work presents AutoLens, the first entirely automated modeling suite for the analysis of galaxy-scale strong gravitational lenses. AutoLens simultaneously models the lens galaxy's light and mass whilst reconstructing the extended source galaxy on an adaptive pixel-grid. The method's approach to source-plane discretization is amorphous, adapting its clustering and regularization to the intrinsic properties of the lensed source. The lens's light is fitted using a superposition of Sersic functions, allowing AutoLens to cleanly deblend its light from the source. Single component mass models representing the lens's total mass density profile are demonstrated, which in conjunction with light modeling can detect central images using a centrally cored profile. Decomposed mass modeling is also shown, which can fully decouple a lens's light and dark matter and determine whether the two component are geometrically aligned. The complexity of the light and mass models are automatically chosen via Bayesian model comparison. These steps form AutoLens's automated analysis pipeline, such that all results in this work are generated without any user-intervention. This is rigorously tested on a large suite of simulated images, assessing its performance on a broad range of lens profiles, source morphologies and lensing geometries. The method's performance is excellent, with accurate light, mass and source profiles inferred for data sets representative of both existing Hubble imaging and future Euclid wide-field observations.

Fast automated analysis of strong gravitational lenses with convolutional neural networks.

Quantifying image distortions caused by strong gravitational lensing-the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures-and estimating the corresponding matter distribution of these structures (the 'gravitational lens') has primarily been performed using maximum likelihood modelling of observations. This procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. Here we report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the 'singular isothermal ellipsoid' density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

Modeling of the Autofluorescence Spectra of the Crystalline Lens with Cataract Taking into Account Light Scattering

The model of the autofluorescence spectrum formation of a crystalline lens taking into account light scattering was presented. Cross sections of extinction, scattering and absorption were obtained numerically for models of normal crystalline lens and cataract according to the Mie theory for polydisperse systems. To validate the model, data on the autofluorescence spectra of the normal lens and cataracts were obtained using an experimental ophthalmologic spectrofluorometer with excitation by UV light emitting diodes. In the framework of the model, the influence of the lens light scattering on the shape of the luminescence spectrum was estimated. It was found that the changes in the fluorescence spectrum of lenses with cataracts can be completely interpreted by the light scattering.

UVA Light-mediated Ascorbate Oxidation in Human Lenses.

Whether ascorbate oxidation is promoted by UVA light in human lenses and whether this process is influenced by age and GSH levels are not known. In this study, we used paired lenses from human donors. One lens of each pair was exposed to UVA light, whereas the other lens was kept in the dark for the same period of time as the control. Using LC-MS/MS analyses, we found that older lenses (41-73 years) were more susceptible to UVA-induced ascorbate oxidation than younger lenses (18-40 years). Approximately 36% of the ascorbate (relative to control) was oxidized in older lenses compared to ~16% in younger lenses. Furthermore, lenses with higher levels of GSH were less susceptible to UVA-induced ascorbate oxidation compared to those with lower levels, and this effect was not dependent on age. The oxidation of ascorbate led to elevated levels of reactive α-dicarbonyl compounds. In summary, our study showed that UVA light exposure leads to ascorbate oxidation in human lenses and that such oxidation is more pronounced in aged lenses and is inversely related to GSH levels. Our findings suggest that UVA light exposure could lead to protein aggregation through ascorbate oxidation in human lenses.

Microfabricated devices for single objective single plane illumination microscopy (SoSPIM).

Light sheet microscopy is a relatively new form of fluorescence microscopy that has been receiving a lot of attention recently. The strong points of the technique, such as high signal to noise ratio and its reduced photodamage of fluorescently labelled samples, come from its unique feature to illuminate only a thin plane in the sample that coincides with the focal plane of the detection lens. Typically this requires two closely positioned perpendicular objective lenses, one for detection and one for illumination. Apart from the fact that this special configuration of objective lenses is incompatible with standard microscope bodies, it is particularly problematic for high-resolution lenses which typically have a short working distance. To address these issues we developed sample holders with an integrated micromirror to perform single lens light sheet microscopy, also known as single objective single plane illumination microscopy (SoSPIM). The first design is based on a wet-etched silicon substrate, the second on a microfabricated polished polymer plug. We achieved an on-chip light sheet thickness of 2.3 μm (FWHM) at 638 nm with the polymer micromirror and of 1.7 μm (FWHM) at 638 nm with the silicon micromirror, comparable to reported light sheet thicknesses obtained on dedicated light sheet microscopes. A marked contrast improvement was obtained with both sample holders as compared to classic epi-fluorescence microscopy. In order to evaluate whether this technology could be made available on a larger scale, in a next step we evaluated the optical quality of inexpensive replicas from both types of master molds. We found that replicas from the polished polymer based mold have an optical quality close to that of the master component, while replicas from the silicon based mold were of slightly lower but still acceptable quality. The suitability of the replicated polymer based sample holder for single-lens light sheet microscopy was finally demonstrated by imaging breast cancer spheroids.