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We investigate the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we perform a systematic visual inspection of the $0.7\,\rm{deg}^2$ Euclid ERO data towards the Perseus cluster using both the high-resolution VIS $I_{\scriptscriptstyle\rm E}$ band, and the lower resolution NISP bands. We inspect every extended source brighter than magnitude $23$ in $I_{\scriptscriptstyle\rm E}$ with $41$ expert human classifiers. This amounts to $12\,086$ stamps of $10^{\prime\prime}\,\times\,10^{\prime\prime}$. We find $3$ grade A and $13$ grade B candidates. We assess the validity of these $16$ candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full $14\,000\,{\rm deg}^2$ of the Euclid Wide Survey should contain $100\,000^{+70\,000}_{-30\,000}$ galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of $170\,000$ discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range $0.\!\!^{\prime\prime}68\,<\,\theta_\mathrm{E}\,<1.\!\!^{\prime\prime}24$, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small Einstein radius systems. Whilst it is implausible to visually inspect the full Euclid data set, our results corroborate the promise that Euclid will ultimately deliver a sample of around $10^5$ galaxy-scale lenses., Comment: 21 pages, 20 figures, submitted to A&A

The Hubble tension is one of the most relevant unsolved problems in cosmology today. Strongly gravitationally lensed transient objects, such as strongly lensed supernovae, are an independent and competitive probe that can be used to determine the Hubble constant. In this context, the time delay between different images of lensed supernovae is a key ingredient. We present a method, to retrieve time delays and the amount of differential dust extinction between multiple images of lensed type IIP supernovae through their color curves, which display a kink in the time evolution. With multiple realistic mock color curves based on an observed unlensed supernova from the Carnegie Supernova Project, we demonstrate that we can retrieve the time delay with uncertainties of $\pm$1.0 days for light curves with 2-day cadence and 35% missing data due to weather losses. The differential dust extinction is more susceptible to uncertainties, because it depends on imposing the correct extinction law. Further we also investigate the kink structure in the color curves for different rest-frame wavelength bands, particularly rest-frame UV light curves from SWIFT, finding sufficiently strong kinks for our method to work for typical lensed SN redshifts that would redshift the kink feature to optical wavelengths. With the upcoming Rubin Observatory Legacy Survey of Space and Time, hundreds of strongly lensed supernovae will be detected and our new method for lensed SN IIP is readily applicable to provide delays., Comment: 16 pages, 19 figures; submitted to A&A

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

We present new VLT/MUSE observations of the Hubble Frontier Field (HFF) galaxy cluster MACS J1149.5+2223, lensing the well-known supernova "Refsdal" into multiple images, which enabled the first cosmological applications with a strongly lensed supernova. Thanks to these data, targeting a northern region of the cluster and thus complementing our previous MUSE program on the cluster core, we release a new catalog containing 162 secure spectroscopic redshifts. We confirm 22 cluster members, which were previously only photometrically selected, and detect ten additional ones, resulting in a total of 308 secure members, of which 63% are spectroscopically confirmed. We further identify 17 new spectroscopic multiple images belonging to 6 different background sources. By exploiting MUSE data, in combination with the deep HFF images, we develop an improved total mass model of MACS J1149.5+2223. This model includes 308 total mass components for the member galaxies and requires four additional mass profiles, one of which is associated with a cluster galaxy overdensity identified in the North, representing the DM mass distribution on larger scales. The values of the resulting 34 free parameters are optimized based on the observed positions of 106 multiple images from 34 different families, that cover the redshift range between 1.240 and 5.983. Our final model has a multiple image position rms value of 0.39", which is well in agreement with that of other cluster lens models. With this refined mass model, we pave the way towards even better strong-lensing analyses that will exploit the deep and high resolution observations with HST and JWST on a pixel level in the region of the supernova Refsdal host. This will increase the number of observables by around two orders of magnitudes, thus offering us the opportunity of carrying out more precise and accurate cosmographic measurements., Comment: 14 pages, 7 figures, 4+1 tables, published with A&A

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., Comment: 8 pages, 9 figures, 1 table, accepted for publication in Astronomy & Astrophysics. We welcome the comments from readers

A bright ($m_{\rm F150W,AB}$=24 mag), $z=1.95$ supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply-imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called "Requiem", and therefore the new SN is named "Encore". This makes the MACS J0138.0$-$2155 cluster the first known system to produce more than one multiply-imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a $\sim10$ year window to be $\approx3\%$. These observations have the potential to yield a Hubble Constant ($H_0$) measurement with $\sim10\%$ precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of $\sim2030$, providing an unprecedented baseline for time-delay cosmography., Comment: Accepted, ApJL

Supernova (SN) H0pe is a gravitationally lensed, triply-imaged, Type Ia SN (SN Ia) discovered in James Webb Space Telescope imaging of the PLCK G165.7+67.0 cluster of galaxies. Well-observed multiply-imaged SNe provide a rare opportunity to constrain the Hubble constant ($H_0$), by measuring the relative time delay between the images and modeling the foreground mass distribution. SN H0pe is located at $z=1.783$, and is the first SN Ia with sufficient light curve sampling and long enough time delays for an $H_0$ inference. Here we present photometric time-delay measurements and SN properties of SN H0pe. Using JWST/NIRCam photometry we measure time delays of $\Delta t_{ab}=-116.6^{+10.8}_{-9.3}$ and $\Delta t_{cb}=-48.6^{+3.6}_{-4.0}$ observer-frame days relative to the last image to arrive (image 2b; all uncertainties are $1\sigma$), which corresponds to a $\sim5.6\%$ uncertainty contribution for $H_0$ assuming $70 \rm{km s^{-1} Mpc^{-1}}$. We also constrain the absolute magnification of each image to $\mu_{a}=4.3^{+1.6}_{-1.8}$, $\mu_{b}=7.6^{+3.6}_{-2.6}$, $\mu_{c}=6.4^{+1.6}_{-1.5}$ by comparing the observed peak near-IR magnitude of SN H0pe to the non-lensed population of SNe Ia., Comment: Accepted in ApJ

Strongly lensed Type Ia supernovae (LSNe Ia) are a promising probe to measure the Hubble constant ($H_0$) directly. To use LSNe Ia for cosmography, a time-delay measurement between the multiple images, a lens-mass model, and a mass reconstruction along the line of sight are required. In this work, we present the machine learning network LSTM-FCNN which is a combination of a Long Short-Term Memory Network (LSTM) and a fully-connected neural network (FCNN). The LSTM-FCNN is designed to measure time delays on a sample of LSNe Ia spanning a broad range of properties, which we expect to find with the upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) and for which follow-up observations are planned. With follow-up observations in $i$ band (cadence of one to three days with a single-epoch $5\sigma$ depth of 24.5 mag), we reach a bias-free delay measurement with a precision around 0.7 days over a large sample of LSNe Ia. The LSTM-FCNN is far more general than previous machine learning approaches such as the Random Forest (RF), where a RF has to be trained for each observational pattern separately, and yet the LSTM-FCNN outperforms the RF by a factor of roughly three. Therefore, the LSTM-FCNN is a very promising approach to achieve robust time delays in LSNe Ia, which is important for a precise and accurate constraint on $H_0$, Comment: 14 pages, 13 figures; submitted to A&A

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., Comment: 27 pages, published in Astronomy & Astrophysics (September 2024)

Tidal disruption events (TDEs) are multi-messenger transients in which a star is tidally destroyed by a supermassive black hole at the center of galaxies. The Rubin Observatory Legacy Survey of Space and Time (LSST) is anticipated to annually detect hundreds to thousands of TDEs, such that the first gravitationally lensed TDE may be observed in the coming years. Using Monte-Carlo simulations, we quantify the rate of both unlensed and lensed TDEs as a function of limiting magnitudes in four different optical bands ($u$, $g$, $r$, and $i$) for a range of TDE temperatures that match observations. Dependent on the temperature and luminosity model, we find that $g$ and $r$ bands are the most promising bands with unlensed TDE detections that can be as high as ${\sim}10^{4}$ annually. By populating a cosmic volume with realistic distributions of TDEs and galaxies that can act as gravitational lenses, we estimate that a few lensed TDEs (depending on the TDE luminosity model) can be detected annually in $g$ or $r$ bands in the LSST survey, with TDE redshifts in the range of ${\sim}0.5$ to ${\sim}2$. The ratio of lensed to unlensed detections indicates that we may detect ${\sim}1$ lensed event for every $10^{4}$ unlensed events, which is independent of the luminosity model. The number of lensed TDEs decreases as a function of the image separations and time delays, and most of the lensed TDE systems are expected to have image separations below ${\sim}3"$ and time delays within ${\sim}30$ days. At fainter limiting magnitudes, the $i$ band becomes notably more successful. These results suggest that strongly lensed TDEs are likely to be observed within the coming years and such detections will enable us to study the demographics of black holes at higher redshifts through the lensing magnifications., Comment: 15 pages, 16 figures, 6 tables, submitted to A&A, comments welcome

We present new measurements of the values of the Hubble constant, matter density, dark energy density, and dark energy density equation-of-state parameters from a full strong lensing analysis of the observed positions of 89 multiple images and 4 measured time delays of SN Refsdal multiple images in the Hubble Frontier Fields galaxy cluster MACS J1149.5+2223. By strictly following the identical modelling methodology as in our previous work, that was done before the time delays were available, our cosmographic measurements here are essentially blind based on the frozen procedure. Without using any priors from other cosmological experiments, in an open $w$CDM cosmological model, through our reference cluster mass model, we measure the following values: $H_0 = 65.1^{+3.5}_{-3.4}$ km s$^{-1}$ Mpc$^{-1}$, $\Omega_{\rm DE}=0.76^{+0.15}_{-0.10}$, and $w=-0.92^{+0.15}_{-0.21}$ (at the 68.3% confidence level). No other single cosmological probe is able to measure simultaneously all these parameters. Remarkably, our estimated values of the cosmological parameters, particularly $H_0$, are very robust and do not depend significantly on the assumed cosmological model and the cluster mass modelling details. The latter introduce systematic uncertainties on the values of $H_0$ and $w$ which are found largely subdominant compared to the statistical errors. The results of this study show that time delays in lens galaxy clusters, combined with extensive photometric and spectroscopic information, offers a novel and competitive cosmological tool., Comment: 7 pages, 6 figures, accepted by Astronomy & Astrophysics

We present a novel approach to measuring the expansion rate and the geometry of the Universe, which combine time-delay cosmography in lens galaxy clusters with pure samples of 'cosmic chronometers' (CCs) by probing the member galaxies. The former makes use of the measured time delays between the multiple images of time-varying sources strongly lensed by galaxy clusters, while the latter exploits the most massive and passive cluster member galaxies to measure the differential time evolution of the Universe. We applied two different statistical techniques, adopting realistic errors on the measured quantities, to assess the accuracy and the gain in precision on the values of the cosmological parameters. We demonstrate that the proposed combined method allows for a robust and accurate measurement of the value of the Hubble constant. In addition, this provides valuable information on the other cosmological parameters thanks to the complementarity between the two different probes in breaking parameter degeneracies. Finally, we showcase the immediate observational feasibility of the proposed joint method by taking advantage of the existing high-quality spectro-photometric data for several lens galaxy clusters., Comment: 6 pages, 2 figures. Accepted for publication in A&A Letters

We present a simple and promising new method to measure the expansion rate and the geometry of the universe that combines observations related to the time delays between the multiple images of time-varying sources, strongly lensed by galaxy clusters, and Type Ia supernovae, exploding in galaxies belonging to the same lens clusters. By means of two different statistical techniques that adopt realistic errors on the relevant quantities, we quantify the accuracy of the inferred cosmological parameter values. We show that the estimate of the Hubble constant is robust and competitive, and depends only mildly on the chosen cosmological model. Remarkably, the two probes separately produce confidence regions on the cosmological parameter planes that are oriented in complementary ways, thus providing in combination valuable information on the values of the other cosmological parameters. We conclude by illustrating the immediate observational feasibility of the proposed joint method in a well-studied lens galaxy cluster, with a relatively small investment of telescope time for monitoring from a 2 to 3m class ground-based telescope., Comment: 6 pages, 2 figures, 1 table. Published in A&A Letters

Strongly lensed systems with peculiar configurations allow us to probe the local properties of the deflecting lens mass while simultaneously testing general profile assumptions. The quasar HE0230$-$2130 is lensed by two galaxies at similar redshifts ($\Delta z \sim 0.003$) into four observed images. Using modeled quasar positions from fitting the brightness of the quasar images in ground-based imaging data from the Magellan telescope, we find that lens-mass models where each of these two galaxies is parametrized with a singular power-law (PL) profile predict five quasar images. To interpret the quad configuration of the system, we tested 12 different profile assumptions with the aim of obtaining lens-mass models that correctly predict only four observed images. We tested the effects of adopting: cored profiles for the lensing galaxies; external shear; and additional profiles to represent a dark matter clump. We find that half of our model classes can produce the correct image multiplicity. By comparing the Bayesian evidence of different model parametrizations, we favor two model classes: (i) one that incorporates two singular PL profiles for the lensing galaxies and a cored isothermal sphere in the region of the previously predicted fifth image (rNIS profile), and (ii) one with a bigger lensing galaxy parametrized by a singular PL profile and the smaller galaxy by a cored PL profile with external shear. We estimated the mass of the rNIS clump for each candidate model of our final Markov chain Monte Carlo sample, and find that only 2\% are in the range of $10^6 M_{\odot} \leq M_{\rm rNIS}\leq 10^9 M_{\odot}$, which is the predicted mass range of dark matter subhalos in cold dark matter simulations, or the mass of dark-matter-dominated and low-surface-brightness galaxies. We therefore favor the models with a cored mass distribution for the lens galaxy close to the predicted fifth image., Comment: 22 pages, 13 figures, 7 tables; accepted by A&A

While supervised neural networks have become state of the art for identifying the rare strong gravitational lenses from large imaging data sets, their selection remains significantly affected by the large number and diversity of nonlens contaminants. This work evaluates and compares systematically the performance of neural networks in order to move towards a rapid selection of galaxy-scale strong lenses with minimal human input in the era of deep, wide-scale surveys. We used multiband images from PDR2 of the HSC Wide survey to build test sets mimicking an actual classification experiment, with 189 strong lenses previously found over the HSC footprint and 70,910 nonlens galaxies in COSMOS. Multiple networks were trained on different sets of realistic strong-lens simulations and nonlens galaxies, with various architectures and data pre-processing. The overall performances strongly depend on the construction of the ground-truth training data and they typically, but not systematically, improve using our baseline residual network architecture. Improvements are found when applying random shifts to the image centroids and square root stretches to the pixel values, adding z band, or using random viewpoints of the original images, but not when adding difference images to subtract emission from the central galaxy. The most significant gain is obtained with committees of networks trained on different data sets, and showing a moderate overlap between populations of false positives. Nearly-perfect invariance to image quality can be achieved by training networks either with large number of bands, or jointly with the PSF and science frames. Overall, we show the possibility to reach a TPR0 as high as 60% for the test sets under consideration, which opens promising perspectives for pure selection of strong lenses without human input using the Rubin Observatory and other forthcoming ground-based surveys., Comment: 21 pages, 10 figures, submitted to A&A, comments are welcome

We study the total and baryonic mass distributions of the deflector SDSS J0100+1818 through a full strong lensing analysis. The system is composed by an ultra-massive early-type galaxy at $z=0.581$, with total stellar mass of $(1.5 \pm 0.3) 10^{12}$ M$_\odot$ and stellar velocity dispersion of ($450 \pm 40$) km s$^{-1}$, surrounded by ten multiple images of three background sources, two of which spectroscopically confirmed at $z=1.880$. We take advantage of high-resolution HST photometry and VLT/X-shooter spectroscopy to measure the positions of the multiple images and perform a strong lensing study with the software GLEE. We test different total mass profiles for the lens and model the background sources first as point-like and then as extended objects. We successfully predict the positions of the observed multiple images and reconstruct over approximately 7200 HST pixels the complex surface brightness distributions of the sources. We measure the cumulative total mass profile of the lens and find a total mass value of $(9.1 \pm 0.1) 10^{12}$ M$_\odot$, within the Einstein radius of approximately 42 kpc, and stellar-over-total mass fractions ranging from ($49 \pm 12$)%, at the half-light radius ($R_e = 9.3$ kpc) of the lens galaxy, to ($10 \pm 2$)%, in the outer regions ($R = 70$kpc). These results suggest that the baryonic mass component of SDSS J0100+1818 is very concentrated in its core and that the lens early-type galaxy/group is immersed in a massive dark matter halo. This is consistent with what found in other ultra-high mass candidates at intermediate redshift. We measure also the physical sizes of the distant sources, resolving them down to a few hundreds of parsec. Finally, we quantify and discuss a relevant source of systematic uncertainties on the reconstructed sizes of background galaxies, associated to the adopted lens total mass model., Comment: 19 pages, 16 figures

Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply-imaged Type Ia SN 2022qmx (aka, "SN Zwicky") at $z=0.3544$. SN Zwicky was discovered by the Zwicky Transient Facility (ZTF) in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multi-cycle "LensWatch" program. We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, F814W) but unresolved with WFC3/IR~F160W, and present an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between lens model predicted time delays ($\lesssim1$ day), and delays estimated with the single epoch of HST colors ($\lesssim3.5$ days), including the uncertainty from chromatic microlensing ($\sim1$-$1.5$ days). Our lens models converge to an Einstein radius of $\theta_E=(0.168^{+0.009}_{-0.005})\prime\prime$, the smallest yet seen in a lensed SN system. The "standard candle" nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter than predicted by $\sim1.7^{+0.8}_{-0.6}$mag and $\sim0.9^{+0.8}_{-0.6}$mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

Multiply imaged time-variable sources can be used to measure absolute distances as a function of redshifts and thus determine cosmological parameters, chiefly the Hubble Constant H$_0$. In the two decades up to 2020, through a number of observational and conceptual breakthroughs, this so-called time-delay cosmography has reached a precision sufficient to be an important independent voice in the current ``Hubble tension'' debate between early- and late-universe determinations of H$_0$. The 2020s promise to deliver major advances in time-delay cosmography, owing to the large number of lenses to be discovered by new and upcoming surveys and the vastly improved capabilities for follow-up and analysis. In this review -- after a brief summary of the foundations of the method and recent advances -- we outline the opportunities for the decade and the challenges that will need to be overcome in order to meet the goal of the determination of H$_0$ from time-delay cosmography with 1\% precision and accuracy., Comment: The Astronomy and Astrophysics Review, in press

Multiply lensed sources experience a relative time delay in the arrival of photons. This effect can be used to measure absolute distances and the Hubble constant ($H_0$) and is known as time-delay cosmography. The methodology is independent of the local distance ladder and early-universe physics and provides a precise and competitive measurement of $H_0$. With upcoming observatories, time-delay cosmography can provide a 1% precision measurement of $H_0$ and can decisively shed light on the current reported 'Hubble tension'. This paper presents the theoretical background and the current techniques applied for time-delay cosmographic studies and the measurement of the Hubble constant. The paper describes the challenges and systematics in the different components of the analysis and strategies to mitigate them. The current measurements are discussed in context and the opportunities with the anticipated data sets in the future are laid out., Comment: 30 pages, 11 figures, accepted to Space Science Reviews, Topical Collection 'Strong Gravitational Lensing', eds. J. Wambsganss et al

To use strong gravitational lenses as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for uniform modeling of strongly lensed quasars with GLEE, a lens modeling software, for high-resolution multi-band data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the lensed quasar host galaxy, we obtain a model of the mass distribution of the lens galaxy. We apply this uniform modeling pipeline to a sample of nine strongly lensed quasars with HST WFC 3 images. The models show in most cases well reconstructed light components and a good alignment between mass and light centroids. We find that the automated modeling code significantly reduces the user input time during the modeling process. The preparation time of required input files is reduced significantly. This automated modeling pipeline can efficiently produce uniform models of extensive lens system samples which can be used for further cosmological analysis. A blind test through a comparison with the results of an independent automated modeling pipeline based on the modeling software Lenstronomy reveals important lessons. Quantities such as Einstein radius, astrometry, mass flattening and position angle are generally robustly determined. Other quantities depend crucially on the quality of the data and the accuracy of the PSF reconstruction. Better data and/or more detailed analysis will be necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up monitoring and further modeling, significantly speeding up the construction of cosmography-grade models. This is an important step forward to take advantage of the orders of magnitude increase in the number of lenses expected in the coming decade., Comment: 37 pages, 14 figures, published in A&A

Modeling of strongly gravitationally lensed galaxies is often required in order to use them as astrophysical or cosmological probes. With current and upcoming wide-field imaging surveys, the number of detected lenses is increasing significantly such that automated and fast modeling procedures for ground-based data are urgently needed. This is especially pertinent to short-lived lensed transients in order to plan follow-up observations. Therefore, we present in a companion paper (submitted) a neural network predicting the parameter values with corresponding uncertainties of a Singular Isothermal Ellipsoid (SIE) mass profile with external shear. In this work, we present a newly-developed pipeline glee_auto.py to model consistently any galaxy-scale lensing system. In contrast to previous automated modeling pipelines that require high-resolution images, glee_auto.py is optimized for ground-based images such as those from the Hyper-Suprime-Cam (HSC) or the upcoming Rubin Observatory Legacy Survey of Space and Time. We further present glee_tools.py, a flexible automation code for individual modeling that has no direct decisions and assumptions implemented. Both pipelines, in addition to our modeling network, minimize the user input time drastically and thus are important for future modeling efforts. We apply the network to 31 real galaxy-scale lenses of HSC and compare the results to the traditional models. In the direct comparison, we find a very good match for the Einstein radius especially for systems with $\theta_E \gtrsim 2$". The lens mass center and ellipticity show reasonable agreement. The main discrepancies are on the external shear as expected from our tests on mock systems. In general, our study demonstrates that neural networks are a viable and ultra fast approach for measuring the lens-galaxy masses from ground-based data in the upcoming era with $\sim10^5$ lenses expected., Comment: 15+45 pages, 7+31 figures, 1+6 tables, published with A&A

We present our lens mass model of SMACS J0723, the first strong gravitational lens observed by the James Webb Space Telescope (JWST). We use data from the Hubble Space Telescope and Multi Unit Spectroscopic Explorer (MUSE) to build our 'pre-JWST' lens model, and refine it with newly available JWST near-infrared imaging in our JWST model. To reproduce the positions of all multiple lensed images with good accuracy, the adopted mass parameterization consists of one cluster-scale component, accounting mainly for the dark matter distribution, the galaxy cluster members and an external shear component. The pre-JWST model has, as constraints, 19 multiple images from six background sources, of which four have secure spectroscopic redshift measurements from this work. The JWST model has more than twice the number of constraints, 30 additional multiple images from another eleven lensed sources. Both models can reproduce very well the multiple image positions with a $\delta_{rms}$ of $0.39''$ and $0.51''$, for the pre-JWST and JWST models, respectively. The total mass estimates within a radius of 128~kpc (~ the Einstein radius) are $7.9_{-0.2}^{+0.3}\times 10^{13}\rm M_{\odot}$ and $8.7_{-0.2}^{+0.2}\times 10^{13}\rm M_{\odot}$, for the pre-JWST and JWST models, respectively. We predict with our mass models the redshifts of the newly detected JWST sources, which are crucial information for systems without spectroscopic measurements for further studies and follow-up observations. Interestingly, one family detected with JWST is found to be at a very high redshift, $z>7.5$ (68% confidence level) and with one image having lensing magnification of $|\mu|=9.5_{-0.8}^{+0.9}$, making it an interesting case for future studies. The lens models, including magnification maps and redshifts estimated from the model are made publicly available, along with the full spectroscopic redshift catalogue from MUSE., Comment: 5 pages, 2 figures, 1 table, plus appendix. Published in A&A Letters. Lens model and redshift catalogue available at: http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/666/L9

Modeling of strong gravitational lenses is a necessity for further applications in astrophysics and cosmology. Especially with the large number of detections in current and upcoming surveys such as the Rubin Legacy Survey of Space and Time (LSST), it is timely to investigate in automated and fast analysis techniques beyond the traditional and time consuming Markov chain Monte Carlo sampling methods. Building upon our convolutional neural network (CNN) presented in Schuldt et al. (2021b), we present here another CNN, specifically a residual neural network (ResNet), that predicts the five mass parameters of a Singular Isothermal Ellipsoid (SIE) profile (lens center $x$ and $y$, ellipticity $e_x$ and $e_y$, Einstein radius $\theta_E$) and the external shear ($\gamma_{ext,1}$, $\gamma_{ext,2}$) from ground-based imaging data. In contrast to our CNN, this ResNet further predicts a 1$\sigma$ uncertainty for each parameter. To train our network, we use our improved pipeline from Schuldt et al. (2021b) to simulate lens images using real images of galaxies from the Hyper Suprime-Cam Survey (HSC) and from the Hubble Ultra Deep Field as lens galaxies and background sources, respectively. We find overall very good recoveries for the SIE parameters, while differences remain in predicting the external shear. From our tests, most likely the low image resolution is the limiting factor for predicting the external shear. Given the run time of milli-seconds per system, our network is perfectly suited to predict the next appearing image and time delays of lensed transients in time. Therefore, we also present the performance of the network on these quantities in comparison to our simulations. Our ResNet is able to predict the SIE and shear parameter values in fractions of a second on a single CPU such that we are able to process efficiently the huge amount of expected galaxy-scale lenses in the near future., Comment: 17 pages, including 11 figures, published with A&A

Gravitational time delays provide a powerful one step measurement of $H_0$, independent of all other probes. One key ingredient in time delay cosmography are high accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (10$^{5-6}$ CPU hours and $\sim$ 0.5-1 year, respectively). Major improvements in modeling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, building on the work by Shajib et al. (2019), we develop an automated modeling pipeline and apply it to a sample of 30 quadruply imaged quasars and one lensed compact galaxy, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in Fermat potential (proportional to time delay) w.r.t. modeling choices. We find that for 10/30 lenses our models are cosmography or nearly cosmography grade (<3% and 3-5% variations). For 6/30 lenses the models are close to cosmography grade (5-10%). These results are based on informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modeling sequence and options. In conclusion, we show that uniform cosmography grade modeling of large strong lens samples is within reach., Comment: 40 pages, 24 figures, 11 tables. Submitted to MNRAS

We study the inner structure of the group-scale lens CASSOWARY 31 (CSWA 31) by adopting both strong lensing and dynamical modeling. CSWA 31 is a peculiar lens system. The brightest group galaxy (BGG) is an ultra-massive elliptical galaxy at z = 0.683 with a weighted mean velocity dispersion of $\sigma = 432 \pm 31$ km s$^{-1}$. It is surrounded by group members and several lensed arcs probing up to ~150 kpc in projection. Our results significantly improve previous analyses of CSWA 31 thanks to the new HST imaging and MUSE integral-field spectroscopy. From the secure identification of five sets of multiple images and measurements of the spatially-resolved stellar kinematics of the BGG, we conduct a detailed analysis of the multi-scale mass distribution using various modeling approaches, both in the single and multiple lens-plane scenarios. Our best-fit mass models reproduce the positions of multiple images and provide robust reconstructions for two background galaxies at z = 1.4869 and z = 2.763. The relative contributions from the BGG and group-scale halo are remarkably consistent in our three reference models, demonstrating the self-consistency between strong lensing analyses based on image position and extended image modeling. We find that the ultra-massive BGG dominates the projected total mass profiles within 20 kpc, while the group-scale halo dominates at larger radii. The total projected mass enclosed within $R_{eff}$ = 27.2 kpc is $1.10_{-0.04}^{+0.02} \times 10^{13}$ M$_\odot$. We find that CSWA 31 is a peculiar fossil group, strongly dark-matter dominated towards the central region, and with a projected total mass profile similar to higher-mass cluster-scale halos. The total mass-density slope within the effective radius is shallower than isothermal, consistent with previous analyses of early-type galaxies in overdense environments., Comment: 22 pages, 12 figures, 5 tables, submitted to Astronomy & Astrophysics. We welcome the comments from readers

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., Comment: Accepted version by A&A. 34 pages, 26 figures, 3 tables

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX. The three components, optimization using multi-start gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs). We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance. The average time to model a single system on four Nvidia A100 GPUs is 105 seconds. The robustness, speed, and scalability offered by this framework make it possible to model the large number of strong lenses found in current surveys and present a very promising prospect for the modeling of $\mathcal{O}(10^5)$ lensing systems expected to be discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope., Comment: 23 pages, 13 figures, 2 tables. Submitted to ApJ

We present a search for galaxy-scale strong gravitational lenses in the initial 2 500 square degrees of the Canada-France Imaging Survey (CFIS). We designed a convolutional neural network (CNN) committee that we applied to a selection of 2 344 002 exquisite-seeing $r$-band images of color-selected luminous red galaxies (LRGs). Our classification uses a realistic training set where the lensing galaxies and the lensed sources are both taken from real data, namely the CFIS $r$-band images themselves and the Hubble Space Telescope (HST). A total of 9 460 candidates obtain a score above 0.5 with the CNN committee. After a visual inspection of the candidates, we find a total of 133 lens candidates, of which 104 are completely new. The set of false positives mainly contains ring, spiral, and merger galaxies, and to a lesser extent galaxies with nearby companions. We classify 32 of the lens candidates as secure lenses and 101 as maybe lenses. For the 32 highest quality lenses, we also fit a singular isothermal ellipsoid mass profile with external shear along with an elliptical Sersic profile for the lens and source light. This automated modeling step provides distributions of properties for both sources and lenses that have Einstein radii in the range $0.5\arcsec<\theta_E<2.5\arcsec$. Finally, we introduce a new lens and/or source single-band deblending algorithm based on auto-encoder representation of our candidates. This is the first time an end-to-end lens-finding and modeling pipeline is assembled together, in view of future lens searches in a single band, as will be possible with Euclid., Comment: 29 pages, 21 figures, accepted by A&A, in press

Cluster strong lensing cosmography is a promising probe of the background geometry of the Universe and several studies have emerged, thanks to the increased quality of observations using space and ground-based telescopes. For the first time, we use a sample of five cluster strong lenses to measure the values of cosmological parameters and combine them with those from classical probes. In order to assess the degeneracies and the effectiveness of strong-lensing cosmography in constraining the background geometry of the Universe, we adopt four cosmological scenarios. We find good constraining power on the total matter density of the Universe ($\Omega_{\rm m}$) and the equation of state of the dark energy parameter $w$. For a flat $w$CDM cosmology, we find $\Omega_{\rm m} = 0.30_{-0.11}^{+0.09}$ and $w=-1.12_{-0.32}^{+0.17}$ from strong lensing only. Interestingly, we show that the constraints from the Cosmic Microwave Background (CMB) are improved by factors of 2.5 and 4.0 on $\Omega_{\rm m}$ and $w$, respectively, when combined with our posterior distributions in this cosmological model. In a scenario where the equation of state of dark energy evolves with redshift, the strong lensing constraints are compatible with a cosmological constant (i.e. $w=-1$). In a curved cosmology, our strong lensing analyses can accommodate a large range of values for the curvature of the Universe of $\Omega_{\rm k}=0.28_{-0.21}^{+0.16}$. In all cosmological scenarios, we show that our strong lensing constraints are complementary and in good agreement with measurements from the CMB, baryon acoustic oscillations and Type Ia supernovae. Our results show that cluster strong lensing cosmography is a potentially powerful probe to be included in the cosmological analyses of future surveys., Comment: 10 pages, 4 figures, 3 tables, submitted to A&A

Time-delay strong lensing (TDSL) is a powerful probe of the current expansion rate of the Universe. However, in light of the discrepancies between early and late-time cosmological studies, efforts revolve around the characterisation of systematic uncertainties in the methods. Here, we focus on the mass-sheet degeneracy (MSD), which is considered a significant source of systematics in TDSL, and aim to assess the constraining power provided by IFU stellar kinematics. We approximate the MSD with a cored, two-parameter extension to the lensing mass profiles (with core radius $r_{\rm c}$ and mass-sheet parameter $\lambda_{\rm int}$). In addition, we utilise mock IFU stellar kinematics of time-delay strong lenses, given the prospects of obtaining such data with JWST. We construct joint strong lensing and stellar dynamical models, where the time delays, mock imaging and IFU observations are used to constrain the mass profile of lens galaxies, and yield joint constraints on the time-delay distance ($D_{\Delta t}$) and angular diameter distance ($D_{\rm d}$) to the lens. We find that mock JWST-like stellar kinematics constrain the internal mass sheet and limit its contribution to the uncertainties of $D_{\Delta t}$ and $D_{\rm d}$, each at the < 4% level, without assumptions on the background cosmological model. These distance constraints would translate to a < 4% precision measurement on $H_{\rm 0}$ in flat $\Lambda CDM$ for a single lens. Our study shows that IFU stellar kinematics of time-delay strong lenses will be key in lifting the MSD on a per lens basis, assuming reasonable core sizes. However, even in the limit of infinite $r_{\rm c}$, where $D_{\Delta t}$ is degenerate with $\lambda_{\rm int}$, stellar kinematics of the deflector, time delays and imaging data will provide powerful constraints on $D_{\rm d}$, which becomes the dominant source of information in the cosmological inference., Comment: submitted to A&A

The Hubble constant ($H_0$) is one of the fundamental parameters in cosmology, but there is a heated debate around the $>$4$\sigma$ tension between the local Cepheid distance ladder and the early Universe measurements. Strongly lensed Type Ia supernovae (LSNe Ia) are an independent and direct way to measure $H_0$, where a time-delay measurement between the multiple supernova (SN) images is required. In this work, we present two machine learning approaches for measuring time delays in LSNe Ia, namely, a fully connected neural network (FCNN) and a random forest (RF). For the training of the FCNN and the RF, we simulate mock LSNe Ia from theoretical SN Ia models that include observational noise and microlensing. We test the generalizability of the machine learning models by using a final test set based on empirical LSN Ia light curves not used in the training process, and we find that only the RF provides a low enough bias to achieve precision cosmology; as such, RF is therefore preferred over our FCNN approach for applications to real systems. For the RF with single-band photometry in the $i$ band, we obtain an accuracy better than 1\% in all investigated cases for time delays longer than 15 days, assuming follow-up observations with a 5$\sigma$ point-source depth of 24.7, a two day cadence with a few random gaps, and a detection of the LSNe Ia 8 to 10 days before peak in the observer frame. In terms of precision, we can achieve an approximately 1.5-day uncertainty for a typical source redshift of $\sim$0.8 on the $i$ band under the same assumptions. To improve the measurement, we find that using three bands, where we train a RF for each band separately and combine them afterward, helps to reduce the uncertainty to $\sim$1.0 day. We have publicly released the microlensed spectra and light curves used in this work., Comment: 25 pages, 28 figures; accepted for publication in A&A

We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens simulations, deep neural network classification, and visual inspection, is aimed at efficiently selecting systems with wide image separations (Einstein radii ~1.0-3.0"), intermediate redshift lenses (z ~ 0.4-0.7), and bright arcs for galaxy evolution and cosmology. We classified gri images of all 62.5 million galaxies in HSC Wide with i-band Kron radius >0.8" to avoid strict pre-selections and to prepare for the upcoming era of deep, wide-scale imaging surveys with Euclid and Rubin Observatory. We obtained 206 newly-discovered candidates classified as definite or probable lenses with either spatially-resolved multiple images or extended, distorted arcs. In addition, we found 88 high-quality candidates that were assigned lower confidence in previous HSC searches, and we recovered 173 known systems in the literature. These results demonstrate that, aided by limited human input, deep learning pipelines with false positive rates as low as ~0.01% can be very powerful tools for identifying the rare strong lenses from large catalogs, and can also largely extend the samples found by traditional algorithms. We provide a ranked list of candidates for future spectroscopic confirmation., Comment: 5 pages and 4 figures (plus appendix), version published in A&A

We investigate strongly gravitationally lensed type II supernovae (LSNe II) for time-delay cosmography incorporating microlensing effects, which expands on previous microlensing studies of type Ia supernovae (SNe Ia). We use the radiative-transfer code ${\rm \small TARDIS}$ to recreate five spectra of the prototypical SN 1999em at different times within the plateau phase of the light curve. The microlensing-induced deformations of the spectra and light curves are calculated by placing the SN into magnification maps generated with the code ${\rm \small GERLUMPH}$. We study the impact of microlensing on the color curves and find that there is no strong influence on them during the investigated time interval of the plateau phase. The color curves are only weakly affected by microlensing due to the almost achromatic behavior of the intensity profiles. However, the lack of non-linear structure in the color curves makes time-delay measurements difficult given the possible presence of differential dust extinction. Therefore, we further investigate SN phase inference through spectral absorption lines under the influence of microlensing and Gaussian noise. As the spectral features shift to longer wavelengths with progressing time after explosion, the measured wavelength of a specific absorption line provides information on the epoch of the SN. The comparison between retrieved epochs of two observed lensing images then gives the time delay of the images. We find that the phase retrieval method using spectral features yields accurate delays with uncertainties $\small {\lesssim}$2 days, making it a promising approach., Comment: 19 pages, 17 figures

The redshifts of galaxies are a key attribute that is needed for nearly all extragalactic studies. Since spectroscopic redshifts require additional telescope and human resources, millions of galaxies are known without spectroscopic redshifts. Therefore, it is crucial to have methods for estimating the redshift of a galaxy based on its photometric properties, the so-called photo-$z$. We developed NetZ, a new method using a Convolutional Neural Network (CNN) to predict the photo-$z$ based on galaxy images, in contrast to previous methods which often used only the integrated photometry of galaxies without their images. We use data from the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP) in five different filters as training data. The network over the whole redshift range between 0 and 4 performs well overall and especially in the high-$z$ range better than other methods on the same data. We obtain an accuracy $|z_\text{pred}-z_\text{ref}|$ of $\sigma = 0.12$ (68% confidence interval) with a CNN working for all galaxy types averaged over all galaxies in the redshift range of 0 to $\sim$4. By limiting to smaller redshift ranges or to Luminous Red Galaxies (LRGs), we find a further notable improvement. We publish more than 34 million new photo-$z$ values predicted with NetZ here. This shows that the new method is very simple and fast to apply, and, importantly, covers a wide redshift range limited only by the available training data. It is broadly applicable and beneficial to imaging surveys, particularly upcoming surveys like the Rubin Observatory Legacy Survey of Space and Time which will provide images of billions of galaxies with similar image quality as HSC., Comment: 10 pages, 11 figures, 1 catalog, published in A&A

The commissioning team for the Vera C. Rubin observatory is planning a set of engineering and science verification observations with the Legacy Survey of Space and Time (LSST) commissioning camera and then the Rubin Observatory LSST Camera. The time frame for these observations is not yet fixed, and the commissioning team will have flexibility in selecting fields to observe. In this document, the Dark Energy Science Collaboration (DESC) Commissioning Working Group presents a prioritized list of target fields appropriate for testing various aspects of DESC-relevant science performance, grouped by season for visibility from Rubin Observatory at Cerro Pachon. Our recommended fields include Deep-Drilling fields (DDFs) to full LSST depth for photo-$z$ and shape calibration purposes, HST imaging fields to full depth for deblending studies, and an $\sim$200 square degree area to 1-year depth in several filters for higher-level validation of wide-area science cases for DESC. We also anticipate that commissioning observations will be needed for template building for transient science over a broad RA range. We include detailed descriptions of our recommended fields along with associated references. We are optimistic that this document will continue to be useful during LSST operations, as it provides a comprehensive list of overlapping data-sets and the references describing them., Comment: 37 pages, 4 figures. This DESC Note has also been shared with the Vera C. Rubin Observatory project and other Rubin Science Collaborations. The code, and data, along with the background references and research used to produce the tables and figures in this document can be found in an accompanying code supplement in the LSST DESC Zenodo community at http://doi.org/10.5281/zenodo.4148042

Modelling the mass distributions of strong gravitational lenses is often necessary to use them as astrophysical and cosmological probes. With the high number of lens systems ($>10^5$) expected from upcoming surveys, it is timely to explore efficient modeling approaches beyond traditional MCMC techniques that are time consuming. We train a CNN on images of galaxy-scale lenses to predict the parameters of the SIE mass model ($x,y,e_x,e_y$, and $\theta_E$). To train the network, we simulate images based on real observations from the HSC Survey for the lens galaxies and from the HUDF as lensed galaxies. We tested different network architectures, the effect of different data sets, and using different input distributions of $\theta_E$. We find that the CNN performs well and obtain with the network trained with a uniform distribution of $\theta_E$ $>0.5"$ the following median values with $1\sigma$ scatter: $\Delta x=(0.00^{+0.30}_{-0.30})"$, $\Delta y=(0.00^{+0.30}_{-0.29})" $, $\Delta \theta_E=(0.07^{+0.29}_{-0.12})"$, $\Delta e_x = -0.01^{+0.08}_{-0.09}$ and $\Delta e_y = 0.00^{+0.08}_{-0.09}$. The bias in $\theta_E$ is driven by systems with small $\theta_E$. Therefore, when we further predict the multiple lensed image positions and time delays based on the network output, we apply the network to the sample limited to $\theta_E>0.8"$. In this case, the offset between the predicted and input lensed image positions is $(0.00_{-0.29}^{+0.29})"$ and $(0.00_{-0.31}^{+0.32})"$ for $x$ and $y$, respectively. For the fractional difference between the predicted and true time delay, we obtain $0.04_{-0.05}^{+0.27}$. Our CNN is able to predict the SIE parameters in fractions of a second on a single CPU and with the output we can predict the image positions and time delays in an automated way, such that we are able to process efficiently the huge amount of expected lens detections in the near future., Comment: 17 pages, 14 Figures

To use strongly lensed Type Ia supernovae (LSNe Ia) for cosmology, a time-delay measurement between the multiple supernova (SN) images is necessary. The sharp rise and decline of SN Ia light curves make them promising for measuring time delays, but microlensing can distort these light curves and therefore add large uncertainties to the measurements. An alternative approach is to use color curves where uncertainties due to microlensing are significantly reduced for a certain period of time known as the achromatic phase. In this work, we investigate in detail the achromatic phase, testing four different SN Ia models with various microlensing configurations. We find on average an achromatic phase of around three rest-frame weeks or longer for most color curves but the spread in the duration of the achromatic phase (due to different microlensing maps and filter combinations) is quite large and an achromatic phase of just a few days is also possible. Furthermore, the achromatic phase is longer for smoother microlensing maps, lower macro-magnifications and larger mean Einstein radii of microlenses. From our investigations, we do not find a strong dependency on the model or on asymmetries in the SN ejecta. Further, we find that three independent LSST color curves exhibit features such as extreme points or turning points within the achromatic phase, which make them promising for time-delay measurements. These curves contain combinations of rest-frame bands $u$, $g$, $r$, and $i$ and to observe them for typical LSN Ia redshifts, it would be ideal to cover (observer-frame) filters $r$, $i$, $z$, $y$, $J$, and $H$., Comment: 17 pages, 15 figures; accepted for publication in A&A

The H0LiCOW collaboration inferred via gravitational lensing time delays a Hubble constant $H_0=73.3^{+1.7}_{-1.8}$ km s$^{-1}{\rm Mpc}^{-1}$, describing deflector mass density profiles by either a power-law or stars plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in $H_0$. We quantify any potential effect of the MST with flexible mass models that are maximally degenerate with H0. Our calculation is based on a new hierarchical approach in which the MST is only constrained by stellar kinematics. The approach is validated on hydrodynamically simulated lenses. We apply the method to the TDCOSMO sample of 7 lenses (6 from H0LiCOW) and measure $H_0=74.5^{+5.6}_{-6.1}$ km s$^{-1}{\rm Mpc}^{-1}$. In order to further constrain the deflector mass profiles, we then add imaging and spectroscopy for 33 strong gravitational lenses from the SLACS sample. For 9 of the SLAC lenses we use resolved kinematics to constrain the stellar anisotropy. From the joint analysis of the TDCOSMO+SLACS sample, we measure $H_0=67.4^{+4.1}_{-3.2}$ km s$^{-1}{\rm Mpc}^{-1}$, assuming that the TDCOSMO and SLACS galaxies are drawn from the same parent population. The blind H0LiCOW, TDCOSMO-only and TDCOSMO+SLACS analyses are in mutual statistical agreement. The TDCOSMO+SLACS analysis prefers marginally shallower mass profiles than H0LiCOW or TDCOSMO-only. While our new analysis does not statistically invalidate the mass profile assumptions by H0LiCOW, and thus their $H_0$ measurement relying on those, it demonstrates the importance of understanding the mass density profile of elliptical galaxies. The uncertainties on $H_0$ derived in this paper can be reduced by physical or observational priors on the form of the mass profile, or by additional data, chiefly spatially resolved kinematics of lens galaxies., Comment: accepted by A&A. Full analysis available at https://github.com/TDCOSMO/hierarchy_analysis_2020_public updated permanent analysis script links

We present six new time-delay measurements obtained from $R_c$-band monitoring data acquired at the Max Planck Institute for Astrophysics (MPIA) 2.2 m telescope at La Silla observatory between October 2016 and February 2020. The lensed quasars HE 0047-1756, WG 0214-2105, DES 0407-5006, 2M 1134-2103, PSJ 1606-2333 and DES 2325-5229 were observed almost daily at high signal-to-noise ratio to obtain high-quality light curves where we can record fast and small-amplitude variations of the quasars. We measured time delays between all pairs of multiple images with only one or two seasons of monitoring with the exception of the time delays relative to image D of PSJ 1606-2333. The most precise estimate was obtained for the delay between image A and image B of DES 0407-5006, where $\tau_{AB} = -128.4^{+3.5}_{-3.8}$ d (2.8% precision) including systematics due to extrinsic variability in the light curves. For HE 0047-1756, we combined our high-cadence data with measurements from decade-long light curves from previous COSMOGRAIL campaigns, and reach a precision of 0.9 d on the final measurement. The present work demonstrates the feasibility of measuring time delays in lensed quasars in only one or two seasons, provided high signal-to-noise ratio data are obtained at a cadence close to daily., Comment: 14 pages, 9 figures, 4 Tables, published in A&A

We investigate the environment and line of sight of the H0LiCOW lens B1608+656 using Subaru Suprime-Cam and the Hubble Space Telescope (HST) to perform a weak lensing analysis. We compare three different methods to reconstruct the mass map of the field, i.e. the standard Kaiser-Squires inversion coupled with inpainting and Gaussian or wavelet filtering, and $\tt{Glimpse}$ a method based on sparse regularization of the shear field. We find no substantial difference between the 2D mass reconstructions, but we find that the ground-based data is less sensitive to small-scale structures than the space-based observations. Marginalising over the results obtained with all the reconstruction techniques applied to the two available HST filters F606W and F814W, we estimate the external convergence, $\kappa_{\rm ext}$ at the position of B1608+656 is $\kappa_{\rm ext} = 0.11^{+0.06}_{-0.04}$, where the error bars corresponds respectively to the 16th and 84th quartiles. This result is compatible with previous estimates using the number-counts technique, suggesting that B1608+656 resides in an over-dense line of sight, but with a completely different technique. Using our mass reconstructions, we also compare the convergence at the position of several groups of galaxies in the field of B1608+656 with the mass measurements using various analytical mass profiles, and find that the weak lensing results favor truncated halo models., Comment: Accepted MNRAS

We present a systematic search for wide-separation (Einstein radius >1.5"), galaxy-scale strong lenses in the 30 000 sq.deg of the Pan-STARRS 3pi survey on the Northern sky. With long time delays of a few days to weeks, such systems are particularly well suited for catching strongly lensed supernovae with spatially-resolved multiple images and open new perspectives on early-phase supernova spectroscopy and cosmography. We produce a set of realistic simulations by painting lensed COSMOS sources on Pan-STARRS image cutouts of lens luminous red galaxies with known redshift and velocity dispersion from SDSS. First of all, we compute the photometry of mock lenses in gri bands and apply a simple catalog-level neural network to identify a sample of 1050207 galaxies with similar colors and magnitudes as the mocks. Secondly, we train a convolutional neural network (CNN) on Pan-STARRS gri image cutouts to classify this sample and obtain sets of 105760 and 12382 lens candidates with scores pCNN>0.5 and >0.9, respectively. Extensive tests show that CNN performances rely heavily on the design of lens simulations and choice of negative examples for training, but little on the network architecture. Finally, we visually inspect all galaxies with pCNN>0.9 to assemble a final set of 330 high-quality newly-discovered lens candidates while recovering 23 published systems. For a subset, SDSS spectroscopy on the lens central regions proves our method correctly identifies lens LRGs at z~0.1-0.7. Five spectra also show robust signatures of high-redshift background sources and Pan-STARRS imaging confirms one of them as a quadruply-imaged red source at z_s = 1.185 strongly lensed by a foreground LRG at z_d = 0.3155. In the future, we expect that the efficient and automated two-step classification method presented in this paper will be applicable to the deeper gri stacks from the LSST with minor adjustments., Comment: 18 pages and 11 figures (plus appendix), version published in A&A

Dynamical modelling of Integral-Field-Unit (IFU) stellar kinematics is a powerful tool to unveil the dynamical structure and mass build-up of galaxies in the local Universe, while gravitational lensing is nature's cosmic telescope to explore the properties of galaxies beyond the local Universe. We present a new approach which unifies dynamical modelling of galaxies with the magnification power of strong gravitational lensing, to reconstruct the structural and dynamical properties of high-redshift galaxies. By means of axisymmetric Jeans modelling, we create a dynamical model of the source galaxy, assuming a surface brightness and surface mass density profile. We then predict how the source's surface brightness and kinematics would look like when lensed by the foreground mass distribution and compare with the mock observed arcs of strong gravitational lensing systems. For demonstration purposes, we create and analyse mock data of the strong lensing system RX J1131-1231. By modelling both the lens and source, we recover the dynamical mass within the effective radius of strongly lensed high-redshift sources within 5% uncertainty, and we improve the constraints on the lens mass parameters by up to 50%. This machinery is particularly well suited for future observations from large segmented-mirror telescopes, such as the James Webb Space Telescope, that will yield high sensitivity and angular-resolution IFU data for studying distant and faint galaxies., Comment: 16 pages, 13 figures

We present the HOLISMOKES programme on strong gravitational lensing of supernovae as a probe of supernova (SN) physics and cosmology. We investigate the effects of microlensing on early-phase SN Ia spectra using four different SN explosion models, and find that within 10 rest-frame days after SN explosion, distortions of SN Ia spectra due to microlensing are typically negligible ($<$1% distortion within the 1$\sigma$ spread, and $\lesssim$10% distortion within the 2$\sigma$ spread). This shows great prospects of using lensed SNe Ia to obtain intrinsic early-phase SN spectra for deciphering SN Ia progenitors. As a demonstration of the usefulness of lensed SNe Ia for cosmology, we simulate a sample of mock lensed SN Ia systems that are expected to have accurate and precise time-delay measurements in the era of the Rubin Observatory Legacy Survey of Space and Time (LSST). Adopting realistic yet conservative uncertainties on their time-delay distances and lens angular diameter distances (of 6.6% and 5%, respectively), we find that a sample of 20 lensed SNe Ia would allow a constraint on the Hubble constant ($H_0$) with 1.3% uncertainty in the flat $\Lambda$CDM cosmology. We find a similar constraint on $H_0$ in an open $\Lambda$CDM cosmology, while the constraint degrades to $3\%$ in a flat $w$CDM cosmology. We anticipate lensed SNe to be an independent and powerful probe of SN physics and cosmology in the upcoming LSST era., Comment: 15 pages, 14 figures, accepted for publication in A&A

We study possible systematic effects on the values of the cosmological parameters measured through strong lensing analyses of the HFF galaxy cluster MACS J1149.5+2223. We use the observed positions of a large set of spectroscopically selected multiple images, including those of supernova "Refsdal" with their estimated time delays. Starting from our reference model in a flat $\Lambda$CDM cosmology, published in Grillo et al. (2018), we confirm the relevance of the longest measurable time delay, between SX and S1, and an approximately linear relation between its value and that of $H_{0}$. We perform true blind tests by considering a range of time delays around its original estimate of $345 \pm 10$ days, as an accurate measurement of this time delay was not known at the time of analysis and writing. We investigate separately the impact of a constant sheet of mass at the cluster redshift, of a power-law profile for the mass density of the cluster main halo and of some scatter in the cluster member scaling relations. Remarkably, we find that these systematic effects do not introduce a significant bias on the inferred values of $H_{0}$ and $\Omega_{\rm m}$ and that the statistical uncertainties dominate the total error budget: a 3% uncertainty on the time delay of image SX translates into approximately 6% and 40% (including both statistical and systematic $1\sigma$) uncertainties for $H_{0}$ and $\Omega_{\rm m}$, respectively. Furthermore, our model accurately reproduces the extended surface brightness distribution of the supernova host, covering more than $3 \times 10^{4}$ $HST$ pixels. We also present the interesting possibility of measuring the value of the equation-of-state parameter $w$ of the dark energy density, currently with a 30% uncertainty. We conclude that time-delay cluster lenses have the potential to become soon an alternative and competitive cosmological probe., Comment: 10 pages, 8 figures, 1 table; ApJ in press (all main results and figures unchanged, only minor changes during revision)

Time-delay cosmography of lensed quasars has achieved 2.4% precision on the measurement of the Hubble constant, $H_0$. As part of an ongoing effort to uncover and control systematic uncertainties, we investigate three potential sources: 1- stellar kinematics, 2- line-of-sight effects, and 3- the deflector mass model. To meet this goal in a quantitative way, we reproduced the H0LiCOW/SHARP/STRIDES (hereafter TDCOSMO) procedures on a set of real and simulated data, and we find the following. First, stellar kinematics cannot be a dominant source of error or bias since we find that a systematic change of 10% of measured velocity dispersion leads to only a 0.7% shift on $H_0$ from the seven lenses analyzed by TDCOSMO. Second, we find no bias to arise from incorrect estimation of the line-of-sight effects. Third, we show that elliptical composite (stars + dark matter halo), power-law, and cored power-law mass profiles have the flexibility to yield a broad range in $H_0$ values. However, the TDCOSMO procedures that model the data with both composite and power-law mass profiles are informative. If the models agree, as we observe in real systems owing to the "bulge-halo" conspiracy, $H_0$ is recovered precisely and accurately by both models. If the two models disagree, as in the case of some pathological models illustrated here, the TDCOSMO procedure either discriminates between them through the goodness of fit, or it accounts for the discrepancy in the final error bars provided by the analysis. This conclusion is consistent with a reanalysis of six of the TDCOSMO (real) lenses: the composite model yields $74.0^{+1.7}_{-1.8}$ $km.s^{-1}.Mpc^{-1}$, while the power-law model yields $H_0=74.2^{+1.6}_{-1.6}$ $km.s^{-1}.Mpc^{-1}$. In conclusion, we find no evidence of bias or errors larger than the current statistical uncertainties reported by TDCOSMO., Comment: 19 pages, 9 figures, 4 tables, published in A&A

Context. The precise determination of the present-day expansion rate of the Universe, expressed through the Hubble constant $H_0$, is one of the most pressing challenges in modern cosmology. Assuming flat $\Lambda$CDM, $H_0$ inference at high redshift using cosmic-microwave-background data from Planck disagrees at the 4.4$\sigma$ level with measurements based on the local distance ladder made up of parallaxes, Cepheids and Type Ia supernovae (SNe Ia), often referred to as "Hubble tension". Independent, cosmological-model-insensitive ways to infer $H_0$ are of critical importance. Aims. We apply an inverse-distance-ladder approach, combining strong-lensing time-delay-distance measurements with SN Ia data. By themselves, SNe Ia are merely good relative distance indicators, but by anchoring them to strong gravitational lenses one can obtain an $H_0$ measurement that is relatively insensitive to other cosmological parameters. Methods. A cosmological parameter estimate is performed for different cosmological background models, both for strong-lensing data alone and for the combined lensing + SNe Ia data sets. Results. The cosmological-model dependence of strong-lensing $H_0$ measurements is significantly mitigated through the inverse distance ladder. In combination with SN Ia data, the inferred $H_0$ consistently lies around 73-74 km s$^{-1}$ Mpc$^{-1}$, regardless of the assumed cosmological background model. Our results agree nicely with those from the local distance ladder, but there is a >2$\sigma$ tension with Planck results, and a ~1.5$\sigma$ discrepancy with results from an inverse distance ladder including Planck, Baryon Acoustic Oscillations and SNe Ia. Future strong-lensing distance measurements will reduce the uncertainties in $H_0$ from our inverse distance ladder., Comment: 5 pages, 3 figures, A&A letters accepted version

Galaxies and galaxy groups located along the line of sight towards gravitationally lensed quasars produce high-order perturbations of the gravitational potential at the lens position. When these perturbation are too large, they can induce a systematic error on $H_0$ of a few-percent if the lens system is used for cosmological inference and the perturbers are not explicitly accounted for in the lens model. In this work, we present a detailed characterization of the environment of the lens system WFI2033-4723 ($z_{\rm src} = 1.662$, $z_{\rm lens}$ = 0.6575), one of the core targets of the H0LICOW project for which we present cosmological inferences in a companion paper (Rusu et al. 2019). We use the Gemini and ESO-Very Large telescopes to measure the spectroscopic redshifts of the brightest galaxies towards the lens, and use the ESO-MUSE integral field spectrograph to measure the velocity-dispersion of the lens ($\sigma_{\rm {los}}= 250^{+15}_{-21}$ km/s) and of several nearby galaxies. In addition, we measure photometric redshifts and stellar masses of all galaxies down to $i < 23$ mag, mainly based on Dark Energy Survey imaging (DR1). Our new catalog, complemented with literature data, more than doubles the number of known galaxy spectroscopic redshifts in the direct vicinity of the lens, expanding to 116 (64) the number of spectroscopic redshifts for galaxies separated by less than 3 arcmin (2 arcmin) from the lens. Using the flexion-shift as a measure of the amplitude of the gravitational perturbation, we identify 2 galaxy groups and 3 galaxies that require specific attention in the lens models. The ESO MUSE data enable us to measure the velocity-dispersions of three of these galaxies. These results are essential for the cosmological inference analysis presented in Rusu et al. (2019)., Comment: Matches the version accepted for publication by MNRAS. Note that this paper previously appeared as H0LICOW XI

We present new measurements of the time delays of WFI2033-4723. The data sets used in this work include 14 years of data taken at the 1.2m Leonhard Euler Swiss telescope, 13 years of data from the SMARTS 1.3m telescope at Las Campanas Observatory and a single year of high-cadence and high-precision monitoring at the MPIA 2.2m telescope. The time delays measured from these different data sets, all taken in the R-band, are in good agreement with each other and with previous measurements from the literature. Combining all the time-delay estimates from our data sets results in Dt_AB = 36.2-0.8+0.7 days (2.1% precision), Dt_AC = -23.3-1.4+1.2 days (5.6%) and Dt_BC = -59.4-1.3+1.3 days (2.2%). In addition, the close image pair A1-A2 of the lensed quasars can be resolved in the MPIA 2.2m data. We measure a time delay consistent with zero in this pair of images. We also explore the prior distributions of microlensing time-delay potentially affecting the cosmological time-delay measurements of WFI2033-4723. There is however no strong indication in our measurements that microlensing time delay is neither present nor absent. This work is part of a H0LiCOW series focusing on measuring the Hubble constant from WFI2033-4723., Comment: Submitted to Astronomy and Astrophysics

The upcoming Large Synoptic Survey Telescope (LSST) will detect many strongly lensed Type Ia supernovae (LSNe Ia) for time-delay cosmography. This will provide an independent and direct way for measuring the Hubble constant $H_0$, which is necessary to address the current $4.4 \sigma$ tension in $H_0$ between the local distance ladder and the early Universe measurements. We present a detailed analysis of different observing strategies for the LSST, and quantify their impact on time-delay measurement between multiple images of LSNe Ia. For this, we produced microlensed mock-LSST light curves for which we estimated the time delay between different images. We find that using only LSST data for time-delay cosmography is not ideal. Instead, we advocate using LSST as a discovery machine for LSNe Ia, enabling time delay measurements from follow-up observations from other instruments in order to increase the number of systems by a factor of 2 to 16 depending on the observing strategy. Furthermore, we find that LSST observing strategies, which provide a good sampling frequency (the mean inter-night gap is around two days) and high cumulative season length (ten seasons with a season length of around 170 days per season), are favored. Rolling cadences subdivide the survey and focus on different parts in different years; these observing strategies trade the number of seasons for better sampling frequency. In our investigation, this leads to half the number of systems in comparison to the best observing strategy. Therefore rolling cadences are disfavored because the gain from the increased sampling frequency cannot compensate for the shortened cumulative season length. We anticipate that the sample of lensed SNe Ia from our preferred LSST cadence strategies with rapid follow-up observations would yield an independent percent-level constraint on $H_0$., Comment: 25 pages, 22 figures; accepted for publication in A&A