arXiv subjects

A. Galan

Publications and source records attributed to A. Galan.

At least 19 recordsLinked to original sources

arXiv2026

TDCOSMO XXVIII. The Hubble constant from the quadruply lensed quasar J1537$-$3010 with precise time delays

We present the first measurement of the Hubble constant ($H_0$) from the quadruply-lensed quasar J1537$-$3010, which has optically-measured time delays at $\sim2 \%$ precision. We combine these delays with multi-band imaging data from the Hubble Space Telescope (HST) and model the system with two independent software and teams. We adopt a mass profile that is maximally degenerate with $H_0$ to fully incorporate the mass-sheet degeneracy in the error budget, with nuisance parameters constrained by spatially resolved stellar kinematics from the Multi Unit Spectroscopic Explorer (MUSE) and a line-of-sight (LoS) analysis using the Euclid Flagship simulation. The entire analysis is performed blindly to $H_0$, distances and mass density slope of the main deflector. After unblinding, we measure $H_0 = 75.5^{+9.3}_{-5.8}\ {\rm km\,s^{-1}\,Mpc^{-1}}$, corresponding to a $10\%$ precision measurement from a single system. This precision is driven by conservative lens modeling assumptions including differences between lens modeling methods and the limited stellar kinematics constraints, from which we infer a total mass-sheet parameter $\lambda\equiv(1-\kappa_{\rm ext})\lambda_{\rm int} = 0.89^{+0.11}_{-0.06}$ ($\lambda_{\rm int}=0.89^{+0.09}_{-0.07}$) that is consistent with current results for elliptical galaxies ($\lambda \approx 1$). Our lensing constraints, stellar kinematic measurements and LoS characterization will be included in subsequent population-level measurements of $H_0$. Moreover, our lens models combined with future near-infrared spectroscopy and imaging from the James Webb Space Telescope will further reduce the uncertainties on $H_0$ from J1537$-$3010 alone, bringing it closer to the few percents precision of the time delays.

astro-ph.CO↗

arXiv2026

TDCOSMO. XXVII. JWST-based Lens Models and H$_0$ Measurement of WFI2033, HE0435, and PG1115

Time-delay cosmography offers a one-step, distance-ladder-independent route to the Hubble-Lemaitre constant, H_0. We present new cosmography-grade lens models of three quadruply imaged quasars based on JWST-NIRCam/F115W imaging (WFI2033-4723, HE0435-1223, PG1115+080). We use the STARRED modeling technique, introduced in our previous analysis of WFI2033-4723, to reconstruct the complex JWST-NIRCam Point Spread Function at high fidelity. We combine NIRCam-based lens models with improved external convergence estimates, published time delays, and aperture-integrated stellar velocity dispersions from JWST NIRSpec to infer H_0. The analysis was carried out blindly for HE0435-1223 and PG1115+080, while it was not blind for WFI2033-4723, as we build upon the previous published model. For comparison with previous HST-based work, we limit our analysis to the case of no internal mass-sheet degeneracy ($\lambda_{\rm int}=1$). We quantify the impact of improved imaging, single-aperture kinematics, and environment measurements on central values and uncertainties. Within flat $\Lambda$CDM, assuming a uniform prior on $\Omega_{\rm m}$, we find H_0 = 71.8$_{-7.0}^{+9.2}$ $\lambda_{\rm int}$ km s$^{-1}$ Mpc$^{-1}$ for PG1115+080, 74.2$_{-4.2}^{+4.2}$ $\lambda_{\rm int}$ km s$^{-1}$ Mpc$^{-1}$ for HE0435-1223, and 73.4$_{-4.4}^{+3.4}$ $\lambda_{\rm int}$ km s$^{-1}$ Mpc$^{-1}$ for WFI2033-4723. Combining the three lenses yields H_0 = 73.5$_{-2.8}^{+2.7}$ $\lambda_{\rm int}$ km s$^{-1}$ Mpc$^{-1}$, consistent with HST-based results (73.6$_{-2.6}^{+2.6}$ $\lambda_{\rm int}$ km s$^{-1}$ Mpc$^{-1}$), but with reduced scatter between the three systems. These models will be incorporated in the TDCOSMO-2026 milestone paper with free $\lambda_{\rm int}$ in a hierarchical fashion. We close by outlining how 16 forthcoming JWST NIRCam targets will further tighten uncertainties toward percent-level precision on H_0.

astro-ph.CO↗

arXiv2026

Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification

We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented to 1809) plus 2000 negatives to a colour dataset of 30,686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20,000 predictions, considering off-centred samples. Candidates span I$_E$ $\simeq$ 17--24 AB mag (median 21.3 AB mag) and are redder in Y$_E$--H$_E$ than the parent population, consistent with massive early-type deflectors. Each training iteration required a week for a small team, and the approach easily scales to future Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.

astro-ph.GA↗

arXiv2026

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong lens candidates compared to the previous search. In total, the catalogue includes 38 "grade A" (confident) and 34 "grade B" (probable) candidates. These lenses are identified through a combination of two independent searches for bright nearby objects: one based on machine-learning models followed by expert visual inspection, and the other based solely on expert visual inspection, targeting objects not included in the initial machine-learning selection (a limitation identified only after extensive visual inspection). With these additional strong lens candidates, we augment the expected number of high-confidence candidates in the Euclid Wide Survey from previous forecasts to 120000. Detailed semi-automated lens modelling confirms at least 41 systems out of 72, a fraction consistent with that found in SLDE A (315 out of 488). These include: multiple edge-on disc lenses; sources with arcs near the lens centre; "red sources"; and an edge-on disk galaxy lensing a galaxy merger, producing two sets of lensed features, an Einstein ring and a doubly imaged component. The median redshift of these systems is $\Delta$ z ~ 0.3 lower than that of the SLDE A sample.

astro-ph.GA↗

arXiv2026

HOLISMOKES XX. Lens models of binary lens galaxies with five images of Supernova Winny

Strongly lensed supernovae (SNe) provide a powerful way to study cosmology, SNe and galaxies. Modelling the lens system is key to extracting astrophysical and cosmological information. We present adaptive-optics-assisted high-resolution images of SN Winny (SN 2025wny) in the J and K filters obtained with the Large Binocular Telescope (LBT). The LBT imaging confirms the presence of a fifth point source, whose colour is consistent with that of the other SN images at similar phases, while lens modelling robustly supports its interpretation as an additional image of SN~Winny. We measure the positions of the five SN images with uncertainties varying between 1 and 14 milliarcseconds. We build the first mass models using lenstronomy and GLEE, and explore three classes of mass models for the two lens galaxies G1 and G2. The optimal model class of the three is a singular isothermal ellipsoid for G1, a singular isothermal sphere for G2, and an external shear. We infer the enclosed masses within the Einstein radius as 4.61^{+0.06}_{-0.04} \times 10^{11}\,M_\odot for G1 and 1.01\pm0.02 \times 10^{11}\,M_\odot for G2. The lensing configuration by the two lens galaxies can produce two additional magnified SN images beyond the five observed ones; the exclusion of such model configurations further constrains the lens model parameters. Our model fits to the observed image positions with an RMS of ~0.0012" - 0.0025", within the observed positional uncertainties. The predicted magnifications of the multiple images vary between ~1.6 (for the faintest fifth image E) to ~10 (for the brightest image A). The predicted relative lensing magnifications of the multiple images do not match that of the observed within 2\sigma uncertainties. The differences in the relative magnifications could be due to millilensing/microlensing. Our mass models form the basis for future analyses of this unique system. (abridged)

astro-ph.GA↗

arXiv2025

Strong Lensing Model and Dust Extinction Maps of the Host Galaxy of Type Ia Supernova H0pe

Strong gravitational lensing by massive galaxy clusters offers rare opportunities to observe multiple images of distant ($z \gtrsim 2$) Type Ia supernovae (SNe) and to resolve the properties of their host galaxies. A recent outstanding example is the Type Ia SN H0pe ($z = 1.78$), which the James Webb Space Telescope (JWST) discovered in NIRCam images, when the galaxy cluster PLCK G165.7+67.0 (G165, $z = 0.35$) still produced three images of it. In this work, we build a new strong lensing model of G165, first using only the positions of multiple images of background galaxies. We then significantly increase the number of constraints around the position of SN H0pe by modeling the extended surface brightness of the SN host galaxy. Including extended image information reduces the average uncertainty on mass model parameters by more than an order of magnitude. We also study the spatial distribution of dust in the arc to estimate the dust extinction at the position of SN H0pe. We find good statistical agreement of the extinction estimate, at $\lesssim 1\sigma$, with three fully independent methods based on spectral energy distribution fitting. Moreover, our extended-image lens model of G165 allows us to map the dust distribution of the host galaxy from the image plane to the source plane. Supernova H0pe exploded in a region with a relatively high extinction ($A_V \approx 0.9$ mag) at around $\sim 1$ kpc from its host center. This work shows that extended image modeling in lensing clusters simultaneously reduces the uncertainty on lens model parameters and enables spatially resolved analyses of lensed transients' host galaxies. Such modeling advances are expected to play an important role in future cosmological analyses using strongly lensed SNe.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue

We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg$^2$). In the initial 0.45\% of Euclid's surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid's resolution reveals rare lens configurations of scientific value including double-source-plane lenses, edge-on lenses, complete Einstein rings, and quadruply-imaged lenses. We resolve lenses with small Einstein radii ($\theta_{\rm E} < 1''$) in large numbers for the first time. These lenses are found through an initial sweep by deep learning models, followed by Space Warps citizen scientist inspection, expert vetting, and system-by-system modelling. Our search approach scales straightforwardly to Euclid Data Release 1 and, without changes, would yield approximately 7000 high-confidence (grade A or B) lens candidates by late 2026. Further extrapolating to the complete Euclid Wide Survey implies a likely yield of over 100000 high-confidence candidates, transforming strong lensing science.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 1

The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were applied to approximately one million images. This was followed by a citizen science inspection of a subset of around $100\,000$ images, of which $65\%$ received high network scores, with the remainder randomly selected. The top scoring outputs were inspected by experts to establish confident (grade A), likely (grade B), possible (grade C), and unlikely lenses. In this paper we combine the citizen science and machine learning classifiers into an ensemble, demonstrating that a combined approach can produce a purer and more complete sample than the original individual classifiers. Using the expert-graded subset as ground truth, we find that this ensemble can provide a purity of $52\pm2\%$ (grade A/B lenses) with $50\%$ completeness (for context, due to the rarity of lenses a random classifier would have a purity of $0.05\%$). We discuss future lessons for the first major Euclid data release (DR1), where the big-data challenges will become more significant and will require analysing more than $\sim300$ million galaxies, and thus time investment of both experts and citizens must be carefully managed.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters

We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

astro-ph.CO↗

arXiv2025

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine C: Finding lenses with machine learning

Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed so far. With a 0.16'' resolution covering a third of the sky, the Euclid telescope will revolutionise the identification of strong lenses, with 170 000 lenses forecasted to be discovered amongst the 1.5 billion galaxies it will observe. We present an analysis of the performance of five machine-learning models at finding strong gravitational lenses in the quick release of Euclid data (Q1) covering 63 deg2. The models have been validated by citizen scientists and expert visual inspection. We focus on the best-performing network: a fine-tuned version of the Zoobot pretrained model originally trained to classify galaxy morphologies in heterogeneous astronomical imaging surveys. Of the one million Q1 objects that Zoobot was tasked to find strong lenses within, the top 1000 ranked objects contain 122 grade A lenses (almost-certain lenses) and 41 grade B lenses (probable lenses). A deeper search with the five networks combined with visual inspection yielded 250 (247) grade A (B) lenses, of which 224 (182) are ranked in the top 20 000 by Zoobot. When extrapolated to the full Euclid survey, the highest ranked one million images will contain 75 000 grade A or B strong gravitational lenses.

astro-ph.GA↗

arXiv2025

Euclid: A complete Einstein ring in NGC 6505

We report the discovery of a complete Einstein ring around the elliptical galaxy NGC 6505, at $z=0.042$. This is the first strong gravitational lens discovered in Euclid and the first in an NGC object from any survey. The combination of the low redshift of the lens galaxy, the brightness of the source galaxy ($I_\mathrm{E}=18.1$ lensed, $I_\mathrm{E}=21.3$ unlensed), and the completeness of the ring make this an exceptionally rare strong lens, unidentified until its observation by Euclid. We present deep imaging data of the lens from the Euclid Visible Camera (VIS) and Near-Infrared Spectrometer and Photometer (NISP) instruments, as well as resolved spectroscopy from the Keck Cosmic Web Imager (KCWI). The Euclid imaging in particular presents one of the highest signal-to-noise ratio optical/near-infrared observations of a strong gravitational lens to date. From the KCWI data we measure a source redshift of $z=0.406$. Using data from the Dark Energy Spectroscopic Instrument (DESI) we measure a velocity dispersion for the lens galaxy of $\sigma_\star=303\pm15\,\mathrm{kms}^{-1}$. We model the lens galaxy light in detail, revealing angular structure that varies inside the Einstein ring. After subtracting this light model from the VIS observation, we model the strongly lensed images, finding an Einstein radius of 2.5 arcsec, corresponding to $2.1\,\mathrm{kpc}$ at the redshift of the lens. This is small compared to the effective radius of the galaxy, $R_\mathrm{eff}\sim 12.3\,\mathrm{arcsec}$. Combining the strong lensing measurements with analysis of the spectroscopic data we estimate a dark matter fraction inside the Einstein radius of $f_\mathrm{DM} = (11.1_{-3.5}^{+5.4})\%$ and a stellar initial mass-function (IMF) mismatch parameter of $\alpha_\mathrm{IMF} = 1.26_{-0.08}^{+0.05}$, indicating a heavier-than-Chabrier IMF in the centre of the galaxy.

astro-ph.GA↗

arXiv2024

Exploiting the diversity of modeling methods to probe systematic biases in strong lensing analyses

Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly increased, from purely analytical methods, to pixelated and non-parametric ones, or ones based on deep learning. We embraced this diversity by selecting different software packages and use them to blindly model independently simulated Hubble Space Telescope (HST) imaging data. To overcome the difficulties arising from using different codes and conventions, we used the COde-independent Organized LEns STandard (COOLEST) to store, compare, and release all models in a self-consistent and human-readable manner. From an ensemble of six modeling methods, we studied the recovery of the lens potential parameters and properties of the reconstructed source. We find that, overall, both lens and source properties are recovered reasonably well, but systematic biases arise in all methods. Interestingly, we do not observe that a single method is significantly more accurate than others, and the amount of bias largely depends on the specific lens or source property of interest. By combining posterior distributions from individual methods using equal weights, the maximal systematic biases on lens model parameters inferred from individual models are reduced by a factor of 5.4 on average. We investigated a selection of modeling effects that partly explain the observed biases, such as the cuspy nature of the background source and the accuracy of the point spread function. This work introduces, for the first time, a generic framework to compare and ease the combination of models obtained from different codes and methods, which will be key to retain accuracy in future strong lensing analyses.

astro-ph.CO↗

arXiv2024

Strong-lensing and kinematic analysis of CASSOWARY 31: can strong lensing constrain the masses of multi-plane lenses?

We present a mass measurement for the secondary lens along the line of sight (LoS) in the multi-plane strong lens modeling of the group-scale lens CASSOWARY 31 (CSWA 31). The secondary lens at redshift $z = 1.49$ is a spiral galaxy well aligned along the LoS with the main lens at $z = 0.683$. Using the MUSE integral-field spectroscopy of this spiral galaxy, we measure its rotation velocities and determine the mass from the gas kinematics. We compare the mass estimation of the secondary lens from the lensing models to the mass measurement from kinematics, finding that the predictions from strong lensing tend to be higher. By introducing an additional lens plane at $z = 1.36$ for an overdensity known to be present, we find a mass of $\simeq 10^{10}$ M$_\odot$ enclosed within 3.3 kpc from the centroid of the spiral galaxy, approaching the estimate from kinematics. This shows that secondary-lens mass measurements from multiple-plane modeling are affected by systematic uncertainties from the degeneracies between lens planes and the complex LoS structure. Conducting a detailed analysis of the LoS structures is therefore essential to improve the mass measurement of the secondary lens.

astro-ph.GA↗

arXiv2024

El Gordo needs El Anzuelo: Probing the structure of cluster members with multi-band extended arcs in JWST data

Gravitational lensing by galaxy clusters involves hundreds of galaxies over a large redshift range and increases the likelihood of rare phenomena (supernovae, dark substructures, etc.). We present the detailed analysis of \elanz, a prominent quintuply imaged dusty star-forming galaxy ($\zs=2.29$), mainly lensed by three members of the massive galaxy cluster ACT-CL\,J0102$-$4915, also known as \elgor ($z_{\rm d}=0.87$). We leverage JWST/NIRCam images, which contain lensing features that were unseen in previous HST images, using a Bayesian, multi-wavelength, differentiable and GPU-accelerated modeling framework that combines \herculens (lens modeling) and \nifty (field model and inference) software packages. For one of the deflectors, we complement lensing constraints with stellar kinematics measured from VLT/MUSE data. In our lens model, we explicitly include the mass distribution of the cluster, locally corrected by a constant shear field. We find that the two main deflectors (L1 and L2) have logarithmic mass density slopes steeper than isothermal, with $\gamma_{\rm L1} = 2.23\pm0.05$ and $\gamma_{\rm L2} = 2.21\pm0.04$. We argue that such steep density profiles can arise due to tidally truncated mass distributions, which we probe thanks to the cluster lensing boost and the strong asymmetry of the lensing configuration. Moreover, our three-dimensional source model captures most of the surface brightness of the lensed galaxy, revealing a clump with a maximum diameter of $400$ parsecs at the source redshift, visible at wavelengths $\lambda_{\rm rest}\gtrsim0.6$ $\mu$m. Finally, we caution on using point-like features within extended arcs to constrain galaxy-scale lens models before securing them with extended arc modeling.

astro-ph.GA↗

arXiv2023

SKA Science Data Challenge 2: analysis and results

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarise the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, `reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy -- which combined predictions from two independent machine learning techniques to yield a 20 percent improvement in overall performance -- underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets.

astro-ph.IM↗

arXiv2022

Gravitationally lensed quasars in Gaia -- IV. 150 new lenses, quasar pairs, and projected quasars

We report the spectroscopic follow-up of 175 lensed quasar candidates selected using Gaia Data Release 2 observations following Lemon et al. 2019. Systems include 86 confirmed lensed quasars and a further 17 likely lensed quasars based on imaging and/or similar spectra. We also confirm 11 projected quasar pairs and 11 physical quasar pairs, while 25 systems are left as unclassified quasar pairs -- pairs of quasars at the same redshift, which could be either distinct quasars or potential lensed quasars. Especially interesting objects include 8 quadruply imaged quasars of which two have BAL sources, an apparent triple, and a doubly lensed LoBaL quasar. The source redshifts and image separations of these new lenses range between 0.65 - 3.59 and 0.78 - 6.23 arcseconds respectively. We compare the known population of lensed quasars to an updated mock catalogue at image separations between 1 and 4 arcseconds, showing a very good match at z<1.5. At z>1.5, only 47% of the predicted number are known, with 56% of these missing lenses at image separations below 1.5 arcseconds. The missing higher-redshift, small-separation systems will have fainter lensing galaxies, and are partially explained by the unclassified quasar pairs and likely lenses presented in this work, which require deeper imaging. Of the 11 new reported projected quasar pairs, 5 have impact parameters below 10 kpc, almost tripling the number of such systems, which can probe the innermost regions of quasar host galaxies through absorption studies. We also report four new lensed galaxies discovered through our searches, with source redshifts ranging from 0.62 to 2.79.

astro-ph.GA↗

arXiv2022

TDCOSMO. IX. Systematic comparison between lens modelling software programs: time delay prediction for WGD 2038-4008

The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038-4008 from two teams using two different software programs: GLEE and LENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within $1.2\sigma$, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a $\sim$4$\sigma$ discrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within $\sim$0.6$\sigma$, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038-4008 and infer the Hubble constant based on our mass models.

astro-ph.CO↗

arXiv2021

Strong lens systems search in the Dark Energy Survey using Convolutional Neural Networks

We performed a search for strong lens galaxy-scale systems in the first data release of the Dark Energy Survey (DES), from a color-selected parent sample of 18~745~029 Luminous Red Galaxies (LRGs). Our search was based on a Convolutional Neural Network (CNN) to grade our LRG selection with values between 0 (non-lens) and 1 (lens). Our training set was data-driven, i.e. using lensed sources taken from HST COSMOS images and where the light distribution of the lens plane was taken directly from DES images of our LRGs. A total of 76~582 cutouts obtained a score above 0.9. These were visually inspected and resulted in two catalogs. The first one contains 405 lens candidates, where 90 present clear lensing features and counterparts, while the others 315 require more evidence, such as higher resolution images or spectra to be conclusive. A total of 186 candidates were totally new identified in this search. The second catalog includes 539 ring galaxy candidates that will be useful to train CNNs against this type of false positives. For the 90 best lens candidates we carried out color-based deblending of the lens and source light without fitting any analytical profile to the data. The method turned out to be very efficient in the deblending, even for very compact objects and for objects with very complex morphology. Finally, from the 90 best lens candidates we selected 52 systems having one single deflector, to test an automated modeling pipeline which successfully modeled 79\% of the sample within an acceptable amount of computing time.

astro-ph.GA↗