Strong Lens Candidates Research Articles

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 multi-band imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2 350 061 galaxies selected from the ∼ 800 deg2 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 1 522 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.

The Carousel Lens: A Well-modeled Strong Lens with Multiple Sources Spectroscopically Confirmed by VLT/MUSE

Over the past few years alone, the lensing community has discovered thousands of strong lens candidates, and spectroscopically confirmed hundreds of them. In this time of abundance, it becomes pragmatic to focus our time and resources on the few extraordinary systems, in order to most efficiently study the Universe. In this paper, we present such a system: DESI-090.9854-35.9683, a cluster-scale lens at z l = 0.49, with seven observed lensed sources around the core, and additional lensed sources further out in the cluster. From the number and the textbook configuration of the lensed images, a tight constraint on the mass potential of the lens is possible. This would allow for detailed analysis on the dark and luminous matter content within galaxy clusters, as well as a probe into dark energy and high-redshift galaxies. We present our spatially resolved kinematic measurements of this system from the Very Large Telescope Multi Unit Spectroscopic Explorer, which confirm five of these source galaxies (in ascending order, at z s = 0.962, 0.962, 1.166, 1.432, and 1.432). With previous Hubble Space Telescope imaging in the F140W and F200LP bands, we also present a simple flux-based lens model consisting of two power-law profiles that, for a cluster lens, well models the five lensed arc families with redshifts. We determine the mass to be M(< θ E) = 4.78 × 1013 M ⊙ for the primary mass potential. From the model, we extrapolate the redshift of one of the two source galaxies not yet spectroscopically confirmed to be at zs=4.52−0.71+1.03 .

Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

Abstract We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ∼520 million astronomical sources covering ∼4000 deg2 of the southern sky to a 5σ point–source depth of g = 24.3, r = 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ∼11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b &gt; 10 deg) and southern celestial hemisphere (decl. &lt; 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

Mining for Strong Gravitational Lenses with Self-supervised Learning

We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys’ Data Release 9. Targeting the identification of new strong gravitational lens candidates, we first create a rapid similarity search tool to discover new strong lenses given only a single labeled example. We then show how training a simple linear classifier on the self-supervised representations, requiring only a few minutes on a CPU, can automatically classify strong lenses with great efficiency. We present 1192 new strong lens candidates that we identified through a brief visual identification campaign and release an interactive web-based similarity search tool and the top network predictions to facilitate crowd-sourcing rapid discovery of additional strong gravitational lenses and other rare objects: github.com/georgestein/ssl-legacysurvey.

HOLISMOKES

We carry out a search for strong-lens systems containing high-redshift lens galaxies with the goal of extending strong-lensing-assisted galaxy evolutionary studies to earlier cosmic time. Two strong-lens classifiers are constructed from a deep residual network and trained with datasets of different lens-redshift and brightness distributions. We classify a sample of 5 356 628 pre-selected objects from the Wide-layer fields in the second public data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) by applying the two classifiers to their HSCgri-filter cutouts. Cutting off at thresholds that correspond to a false positive rate of 10−3on our test set, the two classifiers identify 5468 and 6119 strong-lens candidates. Visually inspecting the cutouts of those candidates results in 735 grade-A or B strong-lens candidates in total, of which 277 candidates are discovered for the first time. This is the single largest set of galaxy-scale strong-lens candidates discovered with HSC data to date, and nearly half of it (331/735) contains lens galaxies with photometric redshifts above 0.6. Our discoveries will serve as a valuable target list for ongoing and scheduled spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, the Subaru Prime Focus Spectrograph project, and the Maunakea Spectroscopic Explorer.

The Dark Energy Survey Bright Arcs Survey: Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey 5000 Square Degree Footprint

Abstract We report the combined results of eight searches for strong gravitational lens systems in the full 5000 square degrees of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in five filters (grizY), with an i-band limiting magnitude (at 10σ) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color–coadd tiles created from the full DES six-season data set. A short list of the most promising strong-lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong-lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported systems. This catalog will be of use for selecting interesting systems for detailed follow up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong-lens searches.

High-quality Strong Lens Candidates in the Final Kilo-Degree Survey Footprint

Abstract We present 97 new high-quality strong lensing candidates found in the final ∼350 deg2 that complete the full ∼1350 deg2 area of the Kilo-Degree Survey (KiDS). Together with our previous findings, the final list of high-quality candidates from KiDS sums up to 268 systems. The new sample is assembled using a new convolutional neural network (CNN) classifier applied to r-band (best-seeing) and g, r, and i color-composited images separately. This optimizes the complementarity of the morphology and color information on the identification of strong lensing candidates. We apply the new classifiers to a sample of luminous red galaxies (LRGs) and a sample of bright galaxies (BGs) and select candidates that received a high probability to be a lens from the CNN (P CNN). In particular, setting P CNN &gt; 0.8 for the LRGs, the one-band CNN predicts 1213 candidates, while the three-band classifier yields 1299 candidates, with only ∼30% overlap. For the BGs, in order to minimize the false positives, we adopt a more conservative threshold, P CNN &gt; 0.9, for both CNN classifiers. This results in 3740 newly selected objects. The candidates from the two samples are visually inspected by seven coauthors to finally select 97 “high-quality” lens candidates which received mean scores larger than 6 (on a scale from 0 to 10). We finally discuss the effect of the seeing on the accuracy of CNN classification and possible avenues to increase the efficiency of multiband classifiers, in preparation of next-generation surveys from ground and space.

Discovering New Strong Gravitational Lenses in the DESI Legacy Imaging Surveys

Abstract We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys’ Data Release 8. We use deep residual neural networks, building on previous work presented by Huang et al. These surveys together cover approximately one-third of the sky visible from the Northern Hemisphere, reaching a z-band AB magnitude of ∼22.5. We compile a training sample that consists of known lensing systems as well as non-lenses in the Legacy Surveys and the Dark Energy Survey. After applying our trained neural networks to the survey data, we visually inspect and rank images with probabilities above a threshold. Here we present 1210 new strong lens candidates.

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: a catalogue of strong galaxy–galaxy lens candidates

ABSTRACT We spectroscopically detected 838 likely, 448 probable, and 265 possible strong lens candidates within ≈2 million galaxy spectra contained within the extended Baryon Oscillation Spectroscopic Survey (eBOSS) from the sixteenth data release (DR16) of the Sloan Digital Sky Survey (SDSS). We apply the spectroscopic detection method of the Baryon Oscillation Spectroscopic Survey (BOSS) Emission-Line Lens Survey (BELLS) and add Gaussian fit information, grading, additional inspection observables, and additional inspection methods to improve our selection method. We observed 477 candidates with lensing evidence within low-resolution images from both the Legacy survey of SDSS-I/II and the DESI Legacy survey, which is $12{{\ \rm per\ cent}}$ higher than the percentage of BELLS candidates observed with similar lensing evidence. Our search within the latest and improved reductions of the BOSS survey yielded a $20{{\ \rm per\ cent}}$ increase in the number of lens candidates expected from searching all BOSS and eBOSS galaxies. The distribution of target and background redshifts of our candidates is similar to the candidates and confirmed lenses within the BELLS observations. We present our Spectroscopic Identification of Lensing Object candidates in a value-added catalogue in SDSS DR16. The examination of these lens candidates in follow-up high-resolution imaging may yield more than twice the lenses found in previous spectroscopic detection surveys within SDSS, which would extend the results of previous lens surveys within SDSS to higher redshifts, constrain models of mass structures in spiral galaxies, and test if including the identification of possible lensing features within low-resolution images has merit to spectroscopic detection programmes.

New High-quality Strong Lens Candidates with Deep Learning in the Kilo-Degree Survey

Abstract We report new high-quality galaxy-scale strong lens candidates found in the Kilo-Degree Survey data release 4 using machine learning. We have developed a new convolutional neural network (CNN) classifier to search for gravitational arcs, following the prescription by Petrillo et al. and using only r-band images. We have applied the CNN to two “predictive samples”: a luminous red galaxy (LRG) and a “bright galaxy” (BG) sample (r &lt; 21). We have found 286 new high-probability candidates, 133 from the LRG sample and 153 from the BG sample. We have ranked these candidates based on a value that combines the CNN likelihood of being a lens and the human score resulting from visual inspection (P-value), and here we present the highest 82 ranked candidates with P-values ≥0.5. All of these high-quality candidates have obvious arc or pointlike features around the central red defector. Moreover, we define the best 26 objects, all with P-values ≥0.7, as a “golden sample” of candidates. This sample is expected to contain very few false positives; thus, it is suitable for follow-up observations. The new lens candidates come partially from the more extended footprint adopted here with respect to the previous analyses and partially from a larger predictive sample (also including the BG sample). These results show that machine-learning tools are very promising for finding strong lenses in large surveys and more candidates can be found by enlarging the predictive samples beyond the standard assumption of LRGs. In the future, we plan to apply our CNN to the data from next-generation surveys such as the Large Synoptic Survey Telescope, Euclid, and the Chinese Space Station Optical Survey.

Finding high-redshift strong lenses in DES using convolutional neural networks

We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250,000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 < g - i < 5, 0.6 < g -r < 3, r_mag > 19, g_mag > 20 and i_mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7,301 galaxies. During visual inspection we rate 84 as "probably" or "definitely" lenses. Four of these are previously known lenses or lens candidates. We inspect a further 9,428 candidates with a different score threshold, and identify four new candidates. We present 84 new strong lens candidates, selected after a few hours of visual inspection by astronomers. This catalogue contains a comparable number of high-redshift lenses to that predicted by simulations. Based on simulations we estimate our sample to contain most discoverable lenses in this imaging and at this redshift range.

LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks

We present a new sample of galaxy-scale strong gravitational-lens candidates, selected from 904 square degrees of Data Release 4 of the Kilo-Degree Survey (KiDS), i.e., the "Lenses in the Kilo-Degree Survey" (LinKS) sample. We apply two Convolutional Neural Networks (ConvNets) to $\sim88\,000$ colour-magnitude selected luminous red galaxies yielding a list of 3500 strong-lens candidates. This list is further down-selected via human inspection. The resulting LinKS sample is composed of 1983 rank-ordered targets classified as "potential lens candidates" by at least one inspector. Of these, a high-grade subsample of 89 targets is identified with potential strong lenses by all inspectors. Additionally, we present a collection of another 200 strong lens candidates discovered serendipitously from various previous ConvNet runs. A straightforward application of our procedure to future Euclid or LSST data can select a sample of $\sim3000$ lens candidates with less than 10 per cent expected false positives and requiring minimal human intervention.

The Sloan Lens ACS Survey. XIII. Discovery of 40 New Galaxy-scale Strong Lenses∗

Abstract We present the full sample of 118 galaxy-scale strong-lens candidates in the Sloan Lens ACS (SLACS) Survey for the Masses (S4TM) Survey, which are spectroscopically selected from the final data release of the Sloan Digital Sky Survey. Follow-up Hubble Space Telescope (HST) imaging observations confirm that 40 candidates are definite strong lenses with multiple lensed images. The foreground-lens galaxies are found to be early-type galaxies (ETGs) at redshifts 0.06–0.44, and background sources are emission-line galaxies at redshifts 0.22–1.29. As an extension of the SLACS Survey, the S4TM Survey is the first attempt to preferentially search for strong-lens systems with relatively lower lens masses than those in the pre-existing strong-lens samples. By fitting HST data with a singular isothermal ellipsoid model, we find that the total projected mass within the Einstein radius of the S4TM strong-lens sample ranges from 3 × 1010 M ⊙ to 2 × 1011 M ⊙. In Shu et al., we have derived the total stellar mass of the S4TM lenses to be 5 × 1010 M ⊙ to 1 × 1012 M ⊙. Both the total enclosed mass and stellar mass of the S4TM lenses are on average almost a factor of 2 smaller than those of the SLACS lenses, which also represent the typical mass scales of the current strong-lens samples. The extended mass coverage provided by the S4TM sample can enable a direct test, with the aid of strong lensing, for transitions in scaling relations, kinematic properties, mass structure, and dark-matter content trends of ETGs at intermediate-mass scales as noted in previous studies.

Finding strong gravitational lenses in the Kilo Degree Survey with Convolutional Neural Networks

The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources. Indeed, this is the case for the search for strong gravitational lenses, where the population of the detectable lensed sources is only a very small fraction of the full source population. We apply for the first time a morphological classification method based on a Convolutional Neural Network (CNN) for recognizing strong gravitational lenses in $255$ square degrees of the Kilo Degree Survey (KiDS), one of the current-generation optical wide surveys. The CNN is currently optimized to recognize lenses with Einstein radii $\gtrsim 1.4$ arcsec, about twice the $r$-band seeing in KiDS. In a sample of $21789$ colour-magnitude selected Luminous Red Galaxies (LRG), of which three are known lenses, the CNN retrieves 761 strong-lens candidates and correctly classifies two out of three of the known lenses. The misclassified lens has an Einstein radius below the range on which the algorithm is trained. We down-select the most reliable 56 candidates by a joint visual inspection. This final sample is presented and discussed. A conservative estimate based on our results shows that with our proposed method it should be possible to find $\sim100$ massive LRG-galaxy lenses at $z\lsim 0.4$ in KiDS when completed. In the most optimistic scenario this number can grow considerably (to maximally $\sim$2400 lenses), when widening the colour-magnitude selection and training the CNN to recognize smaller image-separation lens systems.

RINGFINDER: AUTOMATED DETECTION OF GALAXY-SCALE GRAVITATIONAL LENSES IN GROUND-BASED MULTI-FILTER IMAGING DATA

We present RingFinder, a tool for finding galaxy-scale strong gravitational lenses in multiband imaging data. By construction, the method is sensitive to configurations involving a massive foreground early-type galaxy and a faint, background, blue source. RingFinder detects the presence of blue residuals embedded in an otherwise smooth red light distribution by difference imaging in two bands. The method is automated for efficient application to current and future surveys, having originally been designed for the 150-deg2 Canada France Hawaii Telescope Legacy Survey (CFHTLS). We describe each of the steps of RingFinder. We then carry out extensive simulations to assess completeness and purity. For sources with magnification mu>4, RingFinder reaches 42% (resp. 25%) completeness and 29% (resp. 86%) purity before (resp. after) visual inspection. The completeness of RingFinder is substantially improved in the particular range of Einstein radii 0.8 < REin < 2. and lensed images brighter than g = 22.5, where it can be as high as 70%. RingFinder does not introduce any significant bias in the source or deflector population. We conclude by presenting the final catalog of RingFinder CFHTLS galaxy-scale strong lens candidates. Additional information obtained with Hubble Space Telescope and Keck Adaptive Optics high resolution imaging, and with Keck and Very Large Telescope spectroscopy, is used to assess the validity of our classification, and measure the redshift of the foreground and the background objects. From an initial sample of 640,000 early type galaxies, RingFinder returns 2500 candidates, which we further reduce by visual inspection to 330 candidates. We confirm 33 new gravitational lenses from the main sample of candidates, plus an additional 16 systems taken from earlier versions of RingFinder. First applications are presented in the SL2S galaxy-scale Lens Sample paper series.

GRAVITATIONAL LENS MODELS BASED ON SUBMILLIMETER ARRAY IMAGING OFHERSCHEL-SELECTED STRONGLY LENSED SUB-MILLIMETER GALAXIES ATz&gt; 1.5

Strong gravitational lenses are now being routinely discovered in wide-field surveys at (sub)millimeter wavelengths. We present Submillimeter Array (SMA) high-spatial resolution imaging and Gemini-South and Multiple Mirror Telescope optical spectroscopy of strong lens candidates discovered in the two widest extragalactic surveys conducted by the Herschel Space Observatory: the Herschel-Astrophysical Terahertz Large Area Survey (H-ATLAS) and the Herschel Multi-tiered Extragalactic Survey (HerMES). From a sample of 30 Herschel sources with S_500>100 mJy, 21 are strongly lensed (multiply imaged), 4 are moderately lensed (singly imaged), and the remainder require additional data to determine their lensing status. We apply a visibility-plane lens modeling technique to the SMA data to recover information about the masses of the lenses as well as the intrinsic (i.e., unlensed) sizes (r_half) and far-infrared luminosities (L_FIR) of the lensed submillimeter galaxies (SMGs). The sample of lenses comprises primarily isolated massive galaxies, but includes some groups and clusters as well. Several of the lenses are located at z_lens>0.7, a redshift regime that is inaccessible to lens searches based on Sloan Digital Sky Survey spectroscopy. The lensed SMGs are amplified by factors that are significantly below statistical model predictions given the 500um flux densities of our sample. We speculate that this may reflect a deficiency in our understanding of the intrinsic sizes and luminosities of the brightest SMGs. The lensed SMGs span nearly one decade in L_FIR (median L_FIR=7.9x10^12 L_sun) and two decades in FIR luminosity surface density (median Sigma_FIR=6.0x10^11 L_sun kpc^-2). The strong lenses in this sample and others identified via (sub-)mm surveys will provide a wealth of information regarding the astrophysics of galaxy formation and evolution over a wide range in redshift.

SARCS strong-lensing galaxy groups

We present the weak lensing and optical analysis of the SL2S-ARCS (SARCS) sample of strong lens candidates. The sample is based on the Strong Lensing Legacy Survey (SL2S), a systematic search of strong lensing systems in the photometric Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). The SARCS sample focuses on arc-like features and is designed to contain mostly galaxy groups. We briefly present the weak lensing methodology that we use to estimate the mass of the SARCS objects. Among 126 candidates, we obtain a weak lensing detection for 89 objects with velocity dispersions of the Singular Isothermal Sphere mass model ranging from 350 to 1000 km/s with an average value of 600km/s, corresponding to a rich galaxy group (or poor cluster). From the galaxies belonging to the bright end of the group's red sequence (M_i<-21), we derive the optical properties of the SARCS candidates. We obtain typical richnesses of N=5-15 galaxies and optical luminosities of L=0.5-1.5e+12 Lsol (within a radius of 0.5 Mpc). We use these galaxies to compute luminosity density maps, from which a morphological classification reveals that a large fraction of the sample are groups with a complex light distribution, either elliptical or multimodal, suggesting that these objects are dynamically young structures. We finally combine the lensing and optical analyses to draw a sample of 80 most secure group candidates, i.e. weak lensing detection and over-density at the lens position in the luminosity map, to remove false detections and galaxy-scale systems from the initial sample. We use this reduced sample to probe the optical scaling relations in combination with a sample of massive galaxy clusters. We detect the expected correlations over the probed range in mass with a typical scatter of 25% in the SIS velocity dispersion at a given richness or luminosity, making these scaling laws interesting mass proxies

On the evolution of environmental and mass properties of strong lens galaxies in COSMOS

Among the 100 strong lens candidates found in the COSMOS field, 20 with redshifts in the range [0.34,1.13], feature multiple images of background sources. Using the multi-wavelength coverage of the field and its spectroscopic follow-up, we characterize the evolution with redshift of the environment and of the dark-matter (DM) fraction of the lens galaxies. We present new redshift of the strong lens candidates. The lens environment is characterized by the projected 10 closest galaxies around each lens and by the number of galaxies with a projected distance less than 1Mpc at the lens galaxy redshift. In both cases, we perform similar measurements on a control sample of twin non-lens early type galaxies (ETGs). In addition, we identify group members and field galaxies in the X-ray and optical catalogs of galaxy groups. From those catalogs, we measure the external shear contribution at the lens galaxy positions. The systems are then modeled using a SIE plus the external shear due to the groups. We observe that the average stellar mass of lens galaxies increases with z and that the environment of lens galaxies is compatible with that of the twins. During the lens modeling, we notice that, when let free, the external shear points in a direction which is the mean direction of the external shear due to groups and of the closest galaxy to the lens. We notice that the DM fraction of the lens galaxies within the Einstein radius decreases as the redshift increases. Given these, we conclude that, while the environment of lens galaxies is compatible with that of non-lens ETGS, their mass properties evolves significantly with redshift: it is still not clear whether this advocates in favor of a stronger lensing bias toward massive objects at high redshift or is simply representative of the high proportion of massive and high stellar density galaxies at high redshift.

COSMOS 5921+0638: characterization and analysis of a new strong gravitationally lensed AGN

Context. Strong lens candidates have been newly identified within the COSMOS field. We present VLT/FORS1 spectroscopic followup observations and HST/WFPC2 imaging of the system COSMOS 5921+0638, which exhibits quadruply lensed images and a perfect Einstein ring. Aims. We investigate the nature of COSMOS 5921+0638 by studying its photometric, spectroscopic and physical properties. Methods. By analyzing our VLT/FORS1 spectroscopy and Subaru/CFHT/HST imaging of COSMOS 5921+0638, we completed both an environmental analysis and detailed analytical and grid-based mass modeling to determine it properties. Results. We measured the redshifts of the lensing galaxy in COSMOS 5921+0638 (zl = 0.551 ± 0.001) and 9 additional galaxies in the field (5 of them at z ∼ 0.35). The redshift of the lensed source was inferred by identifying a candidate Lyα line at zs = 3.14 ± 0.05. The mass modeling reveals the requirement of a small external shear (γ = 0.038), which is slightly larger than the lensing contribution expected by galaxy groups along the line-of-sight obtained from the zCOSMOS optical group catalog (κgroups ∼ 0.01 and γgroups ∼ 0.005). The estimated time-delays between the different images are of the order of hours to half a week and the total magnification of the background source is μ ≈ 150. The measured mass-to-light ratio of the lensing galaxy within the Einstein ring is M/LB ≈ 8.5 ± 1.6. Anomalies are observed between the measured and expected flux ratios of the images of the background AGN. Conclusions. Our analysis indicates that the ring and point-like structures in COSMOS 5921+0638 consist of a lensed high redshift galaxy hosting a low luminosity AGN (LLAGN). The observed flux ratio anomalies are probably due to microlensing by stars in the lensing galaxy and/or a combination of static phenomena. Multi-epoch, multi-band space-based observations would allow us to differentiate between the possible causes of these anomalies, since static and/or dynamic variations could be identified. Because of its short time-delays and the possibility of microlensing, COSMOS 5921+0638 is a promising laboratory for future studies of LLAGNs.

First Catalog of Strong Lens Candidates in the COSMOS Field

We present the first catalog of 67 strong galaxy-galaxy lens candidates discovered in the 1.64 square degree Hubble Space Telescope COSMOS survey. Twenty of these systems display multiple images or strongly curved large arcs. Our initial search is performed by visual inspection of the data and is restricted, for practical considerations, to massive early-type lens galaxies with arcs found at radii smaller than ~5''. Simple mass models are constructed for the best lens candidates and our results are compared to the strong lensing catalogs of the SLACS survey and the CASTLES database. These new strong galaxy-galaxy lensing systems constitute a valuable sample to study the mass distribution of early-type galaxies and their associated dark matter halos. We further expect this sample to play an important role in the testing of software algorithms designed to automatically search for strong gravitational lenses. From our analysis a robust lower limit is derived for the expected occurrence of strong galaxy-galaxy systems in current and future space-based wide-field imaging surveys. We expect that such surveys should uncover a large number of strong lensing systems (more than 10 systems per square degree), which will allow for a detailed statistical analysis of galaxy properties and will likely lead to constraints on models of gravitational structure formation and cosmology. The sample of strong lenses is available here: http://cosmosstronglensing.uni-hd.de/