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NASA NTRS1989

Conceptual design study of a 5 kilowatt solar dynamic Brayton power system using a dome Fresnel lens solar concentrator

The primary project objective was to generate a conceptual design for a nominal 5 kW solar dynamic space power system, which uses a unique, patented, transmittance-optimized, dome-shaped, point-focus Fresnel lens as the optical concentrator. Compared to reflective concentrators, the dome lens allows 200 times larger slope errors for the same image displacement. Additionally, the dome lens allows the energy receiver, the power conversion unit (PCU), and the heat rejection radiator to be independently optimized in configuration and orientation, since none of these elements causes any aperture blockage. Based on optical and thermal trade studies, a 6.6 m diameter lens with a focal length of 7.2 m was selected. This lens should provide 87 percent net optical efficienty at 800X geometric concentration ratio. The large lens is comprised of 24 gores, which compactly stow together during launch, and automatically deploy on orbit. The total mass of the microglass lens panels, the graphite/epoxy support structure, and miscellaneous hardware is about 1.2 kg per square meter of aperture. The key problem for the dome lens approach relates to the selection of a space-durable lens material. For the first time, all-glass Fresnel lens samples were successfully made by a sol-gel casting process.

Oneill, Mark J.↗

DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗

NASA NTRS2004

Modeling of a Variable Focal Length Flat Lens Using Left Handed Metamaterials

Left Handed Metamaterials (LHM) were originally purposed by Victor Veselago in1968. These substances would allow a flat structure to focus electromagnetic (EM) waves because they have a negative index of refraction. A similar structure made from conventional materials, those with a positive index of refraction, would disperse the waves. But until recently, these structures have been purely theoretical because substances with both a negative permittivity and negative permeability, material properties necessary for a negative index of refraction, do not naturally exist, Recent developments have produced a structure composed of an array of thin wires and split ring resonators that shows a negative index of refraction. area smaller than a square wavelength. How small the area is can be determined by how perfectly the lens is polished and how pure the substance is that composes the lens. These lenses must also be curved for focusing to occur. The focal length is determined by the curvature of the lens and the material. On the other hand, a flat structure made from LHM would focus light because of the effect of a negative index of refraction in Snell s law. The focal length could also be varied by simply adjusting the distance of the lens from the source of radiation. This could create many devices that are adjustable to different situations in fields such as biomedical imaging and communication. the software package XFDTD which solves Maxwell s equations in the frequency domain as well as the time domain. The program used Drude models of materials to simulate the effect of negative permittivity and negative permeability. Because of this, a LHM can be simulated as a solid block of material instead of an array of wires and split ring resonators. After a flat lens is formed, I am to examine the focusing effect of the lens and determine if a higher resolution flat lens can be developed. Traditional lenses made from conventional materials cannot focus an EM wave onto an My goal was to model LHMs and create a flat lens from them. This was to be done using

Reinert, Jason↗

NASA NTRS2011

Integrated Lens Antennas for Multi-Pixel Receivers

Future astrophysics and planetary experiments are expected to require large focal plane arrays with thousands of detectors. Feedhorns have excellent performance, but their mass, size, fabrication challenges, and expense become prohibitive for very large focal plane arrays. Most planar antenna designs produce broad beam patterns, and therefore require additional elements for efficient coupling to the telescope optics, such as substrate lenses or micromachined horns. An antenna array with integrated silicon microlenses that can be fabricated photolithographically effectively addresses these issues. This approach eliminates manual assembly of arrays of lenses and reduces assembly errors and tolerances. Moreover, an antenna array without metallic horns will reduce mass of any planetary instrument significantly. The design has a monolithic array of lens-coupled, leaky-wave antennas operating in the millimeter- and submillimeter-wave frequencies. Electromagnetic simulations show that the electromagnetic fields in such lens-coupled antennas are mostly confined in approximately 12 15 . This means that one needs to design a small-angle sector lens that is much easier to fabricate using standard lithographic techniques, instead of a full hyper-hemispherical lens. Moreover, this small-angle sector lens can be easily integrated with the antennas in an array for multi-pixel imager and receiver implementation. The leaky antenna is designed using double-slot irises and fed with TE10 waveguide mode. The lens implementation starts with a silicon substrate. Photoresist with appropriate thickness (optimized for the lens size) is spun on the substrate and then reflowed to get the desired lens structure. An antenna array integrated with individual lenses for higher directivity and excellent beam profile will go a long way in realizing multi-pixel arrays and imagers. This technology will enable a new generation of compact, low-mass, and highly efficient antenna arrays for use in multi-pixel receivers and imagers for future planetary and astronomical instruments. These antenna arrays can also be used in radars and imagers for contraband detection at stand-off distances. This will be enabling technology for future balloon-borne, smaller explorer class mission (SMEX), and other missions, and for a wide range of proposed planetary sounders and radars for planetary bodies.

Lee, Choonsup↗

NASA NTRS2012

Qualification of a Null Lens Using Image-Based Phase Retrieval

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

Bolcar, Matthew R.↗

DOE OSTI2022

Search of strong lens systems in the Dark Energy Survey using convolutional neural networks

We present our search for strong lens, galaxy-scale systems in the first data release of the Dark Energy Survey (DES), based on a color-selected parent sample of 18 745 029 luminous red galaxies (LRGs). We used a convolutional neural network (CNN) to grade this LRG sample with values between 0 (non-lens) and 1 (lens). Our training set of mock lenses is data-driven, that is, it uses lensed sources taken from HST-COSMOS images and lensing galaxies from DES images of our LRG sample. A total of 76 582 cutouts were obtained with a score above 0.9, which were then visually inspected and classified into two catalogs. The first one contains 405 lens candidates, of which 90 present clear lensing features and counterparts, while the other 315 require more evidence, such as higher resolution imaging or spectra, to be conclusive. A total of 186 candidates are newly identified by our search, of which 16 are among the 90 most promising (best) candidates. The second catalog includes 539 ring galaxy candidates. This catalog will be a useful false positive sample for training future CNNs. For the 90 best lens candidates we carry out color-based deblending of the lens and source light without fitting any analytical profile to the data. This method is shown to be very efficient in the deblending, even for very compact objects and for objects with a complex morphology. Finally, from the 90 best lens candidates, we selected 52 systems with one single deflector to test an automated modeling pipeline that has the capacity to successfully model 79% of the sample within an acceptable computing runtime.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Galaxy and Mass Assembly: A Comparison between Galaxy–Galaxy Lens Searches in KiDS/GAMA

Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies—such as mixed spectroscopy of multiple galaxies along the line of sight, machine-learning algorithms, and citizen science—have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine-learning, and citizen-science identification of galaxy–galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the Galaxy and Mass Assembly survey. In these, we have the opportunity to compare high completeness spectroscopic identifications against high-fidelity imaging from the Kilo Degree Survey used for both machine-learning and citizen-science lens searches. We find that the three methods—spectroscopy, machine learning, and citizen science—identify 47, 47, and 13 candidates, respectively, in the 180 square degrees surveyed. These identifications barely overlap, with only two identified by both citizen science and machine learning. We have traced this discrepancy to inherent differences in the selection functions of each of the three methods, either within their parent samples (i.e., citizen science focuses on low redshift) or inherent to the method (i.e., machine learning is limited by its training sample and prefers well-separated features, while spectroscopy requires sufficient flux from lensed features to lie within the fiber). These differences manifest as separate samples in estimated Einstein radius, lens stellar mass, and lens redshift. The combined sample implies a lens candidate sky density of ∼0.59 deg{sup −2} and can inform the construction of a training set spanning a wider mass–redshift space. A combined approach and refinement of automated searches would result in a more complete sample of galaxy–galaxy lens candidates for future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2007

Finite Element Analysis of the LOLA Receiver Telescope Lens

This paper presents the finite element stress and distortion analysis completed on the Receiver Telescope lens of the Lunar Orbiter Laser Altimeter (LOLA). LOLA is one of six instruments on the Lunar Reconnaissance Orbiter (LRO), scheduled to launch in 2008. LOLA's main objective is to produce a high-resolution global lunar topographic model to aid in safe landings and enhance surface mobility in future exploration missions. The Receiver Telescope captures the laser pulses transmitted through a diffractive optical element (DOE) and reflected off the lunar surface. The largest lens of the Receiver Telescope, Lens 1, is a 150 mm diameter aspheric lens originally designed to be made of BK7 glass. The finite element model of the Receiver Telescope Lens 1 is comprised of solid elements and constrained in a manner consistent with the behavior of the mounting configuration of the Receiver Telescope tube. Twenty-one temperature load cases were mapped to the nodes based on thermal analysis completed by LOLA's lead thermal analyst, and loads were applied to simulate the preload applied from the ring flexure. The thermal environment of the baseline design (uncoated BK7 lens with no baffle) produces large radial and axial gradients in the lens. These large gradients create internal stresses that may lead to part failure, as well as significant bending that degrades optical performance. The high stresses and large distortions shown in the analysis precipitated a design change from BK7 glass to sapphire.

Matzinger, Elizabeth↗

NASA NTRS2015

System and Method for Null-Lens Wavefront Sensing

A method of measuring aberrations in a null-lens including assembly and alignment aberrations. The null-lens may be used for measuring aberrations in an aspheric optic with the null-lens. Light propagates from the aspheric optic location through the null-lens, while sweeping a detector through the null-lens focal plane. Image data being is collected at locations about said focal plane. Light is simulated propagating to the collection locations for each collected image. Null-lens aberrations may extracted, e.g., applying image-based wavefront-sensing to collected images and simulation results. The null-lens aberrations improve accuracy in measuring aspheric optic aberrations.

Hill, Peter C.↗

NASA NTRS2019

OGLE-2016-BLG-0156: Microlensing Event with Pronounced Microlens-parallax Effects Yielding a Precise Lens Mass Measurement

We analyze the gravitational binary-lensing event OGLE-2016-BLG-0156, for which the lensing light curve displays pronounced deviations induced by microlens-parallax effects. The light curve exhibits three distinctive widely separated peaks and we find that the multiple-peak feature provides a very tight constraint on the microlens-parallax effect, enabling us to precisely measure the microlens parallax . All the peaks are densely and continuously covered from high-cadence survey observations using globally located telescopes and the analysis of the peaks leads to the precise measurement of the angular Einstein radius . From the combination of the measured and , we determine the physical parameters of the lens. It is found that the lens is a binary composed of two M dwarfs with masses M(1) = 0.18 ± 0.01 M(⊙) and M(2) = 0.16 ± 0.01 M(⊙) located at a distance D(L) = 1.35 ± 0.09 kpc. According to the estimated lens mass and distance, the flux from the lens comprises an important fraction, ~25%, of the blended flux. The bright nature of the lens combined with the high relative lens-source motion, μ = 6.94 ± 0.50 mas/yr, suggests that the lens can be directly observed from future high-resolution follow-up observations.

Youn Kil Jung↗

NASA NTRS2001

Quantitative molecular characterization of bovine vitreous and lens with non-invasive dynamic light scattering

The non-invasive technique of dynamic light scattering (DLS) was used to quantitatively characterize vitreous and lens structure on a molecular level by measuring the sizes of the predominant particles and mapping the three-dimensional topographic distribution of these structural macromolecules in three spatial dimensions. The results of DLS measurements in five fresh adult bovine eyes were compared to DLS measurements in model solutions of hyaluronan (HA) and collagen (Coll). In the bovine eyes DLS measurements were obtained from excised samples of gel and liquid vitreous and compared to the model solutions. Measurements in whole vitreous were obtained at multiple points posterior to the lens to generate a three-dimensional 'map' of molecular structure. The macromolecule distribution in bovine lens was similarly characterized.In each bovine vitreous (Bo Vit) specimen, DLS predominantly detected two distinct particles, which differed in diffusion properties and hence size. Comparisons with model vitreous solutions demonstrated that these most likely corresponded to the Coll and HA components of vitreous. Three-dimensional mapping of Bo Vit found heterogeneity throughout the vitreous body, with different particle size distributions for Coll and HA at different loci. In contrast, the three-dimensional distribution of lens macromolecules was more homogeneous. Thus, the non-invasive DLS technique can quantitate the average sizes of vitreous and lens macromolecules and map their three-dimensional distribution. This method to assess quantitatively the macromolecular structure of vitreous and lens should be useful for clinical as well as experimental applications in health and disease. Copyright 2001 Academic Press.

Models, Molecular↗

DOE OSTI2023

Copper Reductase Activity and Free Radical Chemistry by Cataract-Associated Human Lens γ-Crystallins

Cataracts are caused by high-molecular weight aggregates of human eye lens proteins that scatter light, causing lens opacity. Metal ions have emerged as important potential players in the etiology of cataract disease, as human lens γ-crystallins are susceptible to metal-induced aggregation. Here, the interaction of Cu 2+ ions with γD-, γC-, and γS- crystallins, the three most abundant γ-crystallins in the lens, has been evaluated. Cu 2+ ions induced non-amyloid aggregation in all three proteins. Solution turbidimetry, SDS-PAGE, circular dichroism and differential scanning calorimetry showed that the mechanism for Cu-induced aggregation involves: i) loss of beta-sheet structure in the N-terminal domain; ii) decreased thermal and kinetic stability; iii) formation of metal-bridged species; and iv) formation of disulfide-bridged dimers. Electron paramagnetic resonance (EPR) revealed two distinct Cu 2+ binding sites in each protein. Spin quantitation demonstrated reduction of γ-crystallin-bound Cu 2+ ions to Cu + under aerobic conditions, while X-ray absorption spectroscopy (XAS) confirmed the presence of linear or trigonal Cu + binding sites in γ-crystallins. Our EPR and XAS studies revealed that γ-crystallins’ Cu 2+ reductase activity yields a protein-based free radical that is likely a Tyr-based species in human γD-crystallin. This unique free radical chemistry carried out by distinct redox-active Cu sites in human lens γ-crystallins likely contributes to the mechanism of copper-induced aggregation. Finally, in the context of an aging human lens, γ-crystallins could be acting, not only as structural proteins, but also as key players for metal and redox homeostasis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

SDSS-IV MaNGA: a catalogue of spectroscopically detected strong galaxy–galaxy lens candidates

ABSTRACT We spectroscopically detected candidate emission-lines of 8 likely, 17 probable, and 69 possible strong galaxy–galaxy gravitational lens candidates found within the spectra of $\approx 10\, 000$ galaxy targets contained within the completed Mapping of Nearby Galaxies at Apache Point Observatory survey. This search is based upon the methodology of the Spectroscopic Identification of Lensing Objects project, which extends the spectroscopic detection methods of the BOSS Emission-Line Lensing Survey and the Sloan Lens ACS Survey. We scanned the co-added residuals that we constructed from stacks of foreground subtracted row-stacked-spectra so a sigma-clipping method can be used to reject cosmic rays and other forms of transients that impact only a small fraction of the combined exposures. We also constructed narrow-band images from the signal to noise of the co-added residuals to observe signs of lensed source images. We also use several methods to compute the probable strong lensing regime for each candidate lens to determine which candidate background galaxies may reside sufficiently near the galaxy centre for strong lensing to occur. We present the spectroscopic redshifts within a value-added catalogue (VAC) for data release 17 (DR17) of SDSS-IV. We also present the lens candidates, spectroscopic data, and narrow-band images within a VAC for DR17. High resolution follow-up imaging of these lens candidates are expected to yield a sample of confirmed grade-A lenses with sufficient angular size to probe possible discrepancies between the mass derived from a best-fitting lens model, and the dynamical mass derived from the observed stellar velocities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Survey of gravitationally lensed objects in HSC imaging (SuGOHI) – X. Strong lens finding in the HSC-SSP using convolutional neural networks

ABSTRACT We apply a novel model based on convolutional neural networks (CNN) to identify gravitationally lensed galaxies in multiband imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. The trained CNN assigns a score from 0 to 1, with 1 representing lenses and 0 representing non-lenses. Initially, the CNN selects a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1522 cutouts after removing definite non-lenses for further visual inspection. We discover 43 grade A (definite) and 269 grade B (probable) strong lens candidates, of which 97 are completely new. In addition, we also discover 880 grade C (possible) lens candidates, 289 of which are known systems in the literature. We identify 143 candidates from the known systems of grade C that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems are not included in the training, a sample of 32 SuGOHI-c (i.e. group/cluster-scale systems) lens candidates is retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling.

Jaelani, Anton T. (ORCID:0000000162825778)↗

DOE OSTI2024

A Bayesian approach to strong lens finding in the era of wide-area surveys

ABSTRACT The arrival of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide-area sensitive surveys will herald a new era in strong lens science in which the number of strong lenses known is expected to rise from $\mathcal {O}(10^3)$ to $\mathcal {O}(10^5)$. However, current lens-finding methods still require time-consuming follow-up visual inspection by strong lens experts to remove false positives which is only set to increase with these surveys. In this work, we demonstrate a range of methods to produce calibrated probabilities to help determine the veracity of any given lens candidate. To do this we use the classifications from citizen science and multiple neural networks for galaxies selected from the Hyper Suprime-Cam survey. Our methodology is not restricted to particular classifier types and could be applied to any strong lens classifier which produces quantitative scores. Using these calibrated probabilities, we generate an ensemble classifier, combining citizen science, and neural network lens finders. We find such an ensemble can provide improved classification over the individual classifiers. We find a false-positive rate of 10−3 can be achieved with a completeness of 46 per cent, compared to 34 per cent for the best individual classifier. Given the large number of galaxy–galaxy strong lenses anticipated in LSST, such improvement would still produce significant numbers of false positives, in which case using calibrated probabilities will be essential for population analysis of large populations of lenses and to help prioritize candidates for follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

OSL1 Delivery Lens Design Update [Slides]

By changing 2 surfaces (1 new lens) OSL1 can deliver a 2cm spot size and up to 28 J/cm 2 . This new lens does not have any deleterious first-order ghosts. Further work could allow placement of a relay plane at the sample plane by adjusting an additional parameter (inter-lens spacing, changing a third lens etc.) and changing between configurations by pure lens translation (no lens swapping).

42 ENGINEERING↗

DOE OSTI2021

KMT-2019-BLG-1715: Planetary Microlensing Event with Three Lens Masses and Two Source Stars

We investigate the gravitational microlensing event KMT-2019-BLG-1715, the light curve of which shows two short-term anomalies from a caustic-crossing binary-lensing light curve: one with a large deviation and the other with a small deviation. We identify five pairs of solutions, in which the anomalies are explained by adding an extra lens or source component in addition to the base binary-lens model. We resolve the degeneracies by applying a method in which the measured flux ratio between the first and second source stars is compared with the flux ratio deduced from the ratio of the source radii. Applying this method leaves a single pair of viable solutions, in both of which the major anomaly is generated by a planetary-mass third body of the lens, and the minor anomaly is generated by a faint second source. A Bayesian analysis indicates that the lens comprises three masses: a planet-mass object with ∼2.6 M {sub J} and binary stars of K and M dwarfs lying in the galactic disk. We point out the possibility that the lens is the blend, and this can be verified by conducting high-resolution follow-up imaging for the resolution of the lens from the source.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Lens Modeling of STRIDES Strongly Lensed Quasars Using Neural Posterior Estimation

Strongly lensed quasars can be used to constrain cosmological parameters through time-delay cosmography. Models of the lens masses are a necessary component of this analysis. To enable time-delay cosmography from a sample of $\mathcal{O}(10^3)$ lenses, which will soon become available from surveys like the Rubin Observatory’s Legacy Survey of Space and Time and the Euclid Wide Survey, we require fast and standardizable modeling techniques. To address this need, we apply neural posterior estimation (NPE) for modeling galaxy-scale strongly lensed quasars from the Strong Lensing Insights into the Dark Energy Survey (STRIDES) sample. NPE brings two advantages: speed and the ability to implicitly marginalize over nuisance parameters. We extend this method by employing sequential NPE to increase precision of mass model posteriors. We then fold individual lens models into a hierarchical Bayesian inference to recover the population distribution of lens mass parameters, accounting for out-of-distribution shift. After verifying our method using simulated analogs of the STRIDES lens sample, we apply our method to 14 Hubble Space Telescope single-filter observations. We find the population mean of the power-law elliptical mass distribution slope, γ lens , to be $\mathcal{M}_γ$ lens = 2.13 ± 0.06. Our result represents the first population-level constraint for these systems. This population-level inference from fully automated modeling is an important stepping stone toward cosmological inference with large samples of strongly lensed quasars.

79 ASTRONOMY AND ASTROPHYSICS↗