Open Access
Issue
A&A
Volume 618, October 2018
Article Number A56
Number of page(s) 12
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/201833480
Published online 12 October 2018

© ESO 2018

Licence Creative Commons
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

The ESA/Gaia space mission (Gaia Collaboration 2016b) constitutes an exceptional opportunity to characterise and to discover multiply imaged quasars, although this was not put forth as one of the science objectives in the mission proposal. With a spatial resolution of ∼0.18″ Gaia is roughly comparable to that of Hubble Space Telescope (HST) for this particular feature (e.g. Bellini et al. 2011). However Gaia being a scanning mission is unique in providing an all-sky coverage with that angular resolution. Thus, by the final Gaia data release (DR), a whole population of such multiply imaged quasars would be revealed, providing an all-sky, and the first of this kind, survey of multiply imaged quasars with well understood source detection biases (e.g. de Bruijne et al. 2015; Arenou et al. 2017, 2018).

Several programmes dedicated to systematic searches for lenses in large astronomical surveys such as SDSS, WISE, DES, PanSTARRS, among others, have been developed in recent years (e.g. More et al. 2016, 2017; Lin et al. 2017; Ostrovski et al. 2018), and many of them rely on supervised machine learning algorithms trained on simulations to handle the large volume of imaging data (e.g. Petrillo et al. 2017; Perreault Levasseur et al. 2017; Hartley et al. 2017; Pourrahmani et al. 2018; Lanusse et al. 2018). Naturally, even if Gaia does not provide images of the observed sources, contrary to the previously mentioned surveys, its high angular resolution over the entire sky is a major asset to contribute to the discovery and the study of multiply imaged quasars.

Finet & Surdej (2016) investigate the potential of Gaia for gravitational lensing and compared it to the detectability with seeing-limited observations for the same limiting magnitude (G = 20). They expect at maximum about ∼1600 multiply imaged quasars with an angular separation large enough to be resolved from the ground in an optimal seeing scenario, while scarcely ∼80 would be composed by more than two images. However, they predict that detections from space are much more encouraging, raising the number of multiply imaged quasars detectable by a Gaia-like survey to ∼2900, thanks to the improved resolving power alone.

The first Gaia data release (DR1; Gaia Collaboration 2016a), besides providing the best available two-parameter astrometry (positions only) at the epoch of its publication, contained only one G mean magnitude, and it did not reach the effective angular resolution necessary to include most of the multiply imaged quasars. This happened due to data processing issues and final astrometric quality reasons (Fabricius et al. 2016; Arenou et al. 2017). Yet, several multiply imaged quasars discovered from other large surveys such as Pan-STARRS, DES, SDSS-III BOSS, HSCS or VST-ATLAS, were subsequently identified with at least one Gaia DR1 detection (e.g. Agnello et al. 2015, 2017, 2018b; Lemon et al. 2017, 2018; Ostrovski et al. 2018).

The Gaia DR2 (Gaia Collaboration 2018) on the other hand, starts to deliver colour information and thus to become self-sufficient in the search for new lenses. It also starts to reach effective angular resolutions that are capable of resolving more multiply imaged quasars, expected with typical separations below 1″. The Gaia DR2 effective resolution reaches ∼0.4″, with completeness for separations larger than ∼2.2″ (Gaia Collaboration 2018). However this resolution applies strictly only to astrometry and G band photometry; colour data are available for objects with separations down to ∼2″, but its completeness only reaches ∼3.5″ (Gaia Collaboration 2018). Even if it is still far from the ultimate resolving power of the Gaia instrument, the Gaia DR2 is a significant advance over DR1, as beyond its much improved effective angular resolution, it contains five-parameter astrometric data (positions, proper-motions, parallax) and also colour information for most objects. This significantly simplifies the extraction of genuine extragalactic sources from the galactic stellar contaminants. Only the faintest or most problematic objects are characterised by just a two-parameters solution in this data release, which is unfortunately the case for several multiply imaged quasars as their magnitudes are often close to the Gaia limiting sensitivity at (G ∼ 20.7).

As part of a larger effort to discover and study multiply imaged quasar candidates from the various Gaia data releases, our group first searched for new lensed systems around known or candidate quasars, enabling the discovery of highly probable multiply imaged quasar candidates for the first time from Gaia data alone (Gaia GraL Paper I; Krone-Martins et al. 2018). In the present work, we report our findings regarding the identification of known gravitationally lensed quasars in Gaia DR2. We have analysed the statistical astrometric properties of the detected lensed images and provide improved relative astrometry for them. We also derive soft astrometric filters that will be applied, as part of a global blind search (Gaia GraL Paper III; Delchambre et al., in prep.), to differentiate foreground stars from extragalactic objects without rejecting the faint components of known lensed systems. To illustrate how the exquisite optical astrometry of Gaia at the sub-milliarcsecond level may help to better constrain the lenses, we performed a simple modelling of the quadruple lens HE0435-1223 in a Bayesian framework, both using Gaia and HST astrometry, for comparison purposes.

The paper is organised as follows: in Sect. 2 we describe the construction of our list of gravitationally lensed quasars and candidates from published data. Sect. 3 presents the matching statistics of this list of known systems with the Gaia DR2. Section 4 presents the astrometric properties of the Gaia DR2 data for the known systems. A simple modelling within the Bayesian framework of a known lens using Gaia DR2 astrometry is described and discussed in Sect. 5. Finally, we summarise our findings in Sect. 6.

2. Compiled list of gravitationally lensed quasars

We have attempted to compile an as-complete-as-possible list of known gravitationally lensed quasars that were published in the literature prior to the Gaia DR2, including some recent candidates that are not yet spectroscopically confirmed. The major source of known gravitational lenses included in our list is the CASTLES (CfA-Arizona Space Telescope LEns Survey of gravitational lenses) site (Kochanek et al. 1999)1 providing information for about 100 lenses, most of them observed with HST. Another important single source of known multiply imaged quasars is the SDSS Quasar Lens Search site (SQLS)2, aimed to discover lensed quasars from the large homogeneous data of the Sloan Digital Sky Survey (SDSS) providing data on 49 additional lensed systems. We also included several quasar systems from the Master Lens Database (Moustakas 2012)3, a community-supported compilation of all discovered strong gravitational lenses. Finally we complemented our list with recent and more scattered discoveries from the literature. This list is being kept up-to-date, and will be maintained at least until the final Gaia data release. For the sake of completeness, we also included in this list the candidates with indication in the literature of just one image (usually spectroscopic candidates) expecting from the exceptional resolving power of Gaia that it may resolve some of them into multiple images in one of its data releases.

Our resulting list of published lensed or lens-candidate quasars contains 481 systems (233 confirmed systems and 248 lensed quasar candidates). This list is only available in electronic form at the CDS, including access through Virtual Observatory ready tools, it comprises lens identifiers, references and the Gaia astrometry and photometry when a match was found in the DR2. A subset of our list is presented in Table B.1 (quadruply imaged quasars with at least one detection in the Gaia DR2). The summarised statistical properties of our entire list in terms of number of systems with 1, 2, 3, and 4 and more images and status are given in Table 1.

3. Gravitationally lensed quasars in Gaia DR2

We extracted sources from the Gaia DR2 within a radius of 10″ around each source of our compiled list of known gravitationally lensed quasars using ADQL and the Gaia archive facility at ESAC (Salgado et al. 2017). We obtained the positions (α, δ), parallaxes (ϖ), proper-motion components (μα, μδ) and fluxes in the G, GBP and GRP pass-bands (Evans et al. 2018) along with their respective uncertainties.

Table 1.

Statistics of the known multiply imaged quasars present in our reference list (Col. 2) and of the corresponding detected systems in Gaia DR2 (Col. 3).

For each individual image of each system, we performed a positional cross-match within a maximum angular separation of 0.5″ between the astrometry found in the literature and the Gaia DR2. We visually inspected all systems one by one, by comparing the Gaia DR2 detections to the system discovery papers and/or archival images from Aladin (Bonnarel et al. 2000; Boch et al. 2014).

Of the 481 gravitational lens systems (including candidates), 206 have at least one image matched with a Gaia DR2 source. The overall detection statistics of known systems that result from our examination is given in Table 1. An all-sky chart in galactic coordinates of the known lenses is shown in Fig. 1 along with a specification of the Gaia detection.

In Table B.1 we present a subset of our list: the quads for which at least one match was found in the Gaia DR2. The complete list of lenses and detection is available in electronic form only at the CDS.

Of the 44 known systems with four images (or more), 29 have at least one image detected in Gaia DR2. Within this group, one system has just one image detected, eight have two images, eight have three images and 12 are fully detected with four images seen in the Gaia data around the target direction. In Fig. A.1, we provide charts for the 12 systems with four detections with the Gaia DR2 positions given relative to the A image (the brightest image in the system discovery pass-band) together with flux ratios. Of those which are fully detected, only five are characterised by sub-milliarcsec astrometry, and are reported in Table 2. The faintest image (in G band) of the others is detected but poorly constrained.

Several quadruply imaged systems were not completely detected, despite the fact that the apparent magnitudes and angular separations of the system images are within Gaia’s capabilities. For example, this is the case Q2237+030; only two out of its four known components are published in Gaia DR2. The diffraction limited resolving power of the Gaia instrument is ∼0.2″, but as commented in Sect. 1, the effective angular resolution of the Gaia DR2 is much worse than that, attaining at most ∼0.4″, but with completeness of only ∼2.2″. This loss of resolution restricts the detection of the ∼2900 lenses predicted by Finet & Surdej (2016). This happens for multiple reasons, all of them at the ground processing stage, as the Gaia raw data cross-matching, the validation of the astrometric solution and the filtering of possible spurious sources. It is expected, however, that at each Gaia data release the effective angular resolution will improve and thus systems with each time smaller angular separations that are not yet separated in the Gaia DR2 will be disentangled.

thumbnail Fig. 1.

All-sky chart in galactic coordinates with the galactic anti-centre in the middle. The known multiply imaged quasars are indicated in grey. The systems presenting one or two counterparts in Gaia DR2 are surrounded by a green open circle. The systems with three Gaia DR2 detections are indicated with purple filled circles, while the systems with four or more detections are indicated with orange filled circles.

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4. Astrometric properties of the Gaia DR2 gravitationally lensed quasars

The images of a quasar produced by strong gravitational lensing are peculiar since they are not independent astronomical sources but multiple images of the same source, possibly with part of the host galaxy visible as small segments of an arc. Accordingly, they can produce some particular astrometric signatures in the Gaia DR2 solution, that could be helpful to discover further lensed quasar systems in the Gaia data.

Of the 382 individual images found in the Gaia DR2 coming from the 178 confirmed gravitationally lensed quasars with two or more images, 65 have a Gaia two-parameter astrometric solution, that is, right ascension and declination only (see Lindegren et al. 2018 for a description of the Gaia DR2 astrometric solution selection). The other 317 images have complete five-parameter solutions (α, δ, μα cos(δ), μδ, ϖ). We investigated the statistical properties of the Gaia DR2 parameters of the multiple images of the known gravitationally lensed quasars, with results shown in Fig. 2. This figure shows that parallaxes and proper motions of the images resulting from lensing occasionally reach large values for sources expected to have neither parallax nor motion. However, this results from the fact that these images are rather faint, at the limit of the Gaia DR2 sensitivity where the uncertainties from random noise are also large. In addition it may also be that some images are embedded in extended and diffuse structures.

In a search for multiply imaged quasars in the Gaia DR2, applying a straight astrometric filter aiming at excluding stars from the deviation from zero parallaxes and proper motions weighted by the expected uncertainties, would likely also exclude a large number of images of lenses. So, based on the distribution of these parameters for the known lenses, we established the following softer astrometric cuts, that at the expense of a certain level of stellar contamination, avoid the rejection of genuine lens systems or of one or several images within a system.

Gaia DR2 sources that should be accepted in such a search would likely comply with ϖ − 3σϖ < 4 mas and |μ| − 3σμ < 4 mas yr−1. We note here that μ stands for μα cos(δ) and μδ.

Indeed, we also adopted these soft filters in Gaia GraL Paper I (Krone-Martins et al. 2018), where we presented the first ever discoveries of quadruply imaged quasar candidates from data of an astrometric space mission. These statistical astrometric properties derived from Gaia measurements are also being used in a large, machine learning based, systematic blind search for lenses in Gaia DR2 (Gaia GraL Paper III; Delchambre et al., in prep.).

5. Gravitational lens modelling with sub-mas astrometry

Gravitational lensing provides an efficient tool to explore various aspects of our universe and several of its components. In the strong regime, the inference of physically meaningful quantities from observational data usually requires the accurate modelling of the gravitational potential of the deflector. For example, the ability of modern time-delay cosmography to infer the Hubble constant H0 with a competitive precision relies significantly on its capacity in dealing with families of degeneracies existing between different plausible lens mass profiles (Saha 2000; Wucknitz 2002; Liesenborgs & De Rijcke 2012; Schneider & Sluse 2013). To probe the deflector mass distribution in the region where multiple images are formed, simple parameterised mass models are commonly used whose parameters are fixed by the observational constraints (e.g. Keeton 2001, 2010; Lefor & Futamase 2014; Lefor 2014), typically the lensed quasar image positions, the morphology of extended components, microlensing-free flux ratios, and time delays between image pairs. Naturally, a better accuracy in the observed parameters leads to a more reliable model. For the five known lenses RXJ1131-1231, SDSS1004+4112, 2MASS J1134-2103, HE0435-1223, and WFI2033-4723, the Gaia DR2 provides quasar image position measurements with an unprecedented precision of a few tenths of a milliarcsecond. With an improvement of an order of magnitude over typical HST astrometric accuracy, these new astrometric data should help to better constrain the lens models. Considering four of the five known quadruply imaged quasars reported in Table 2 for which Gaia and HST astrometric data are available, the average of the Gaia astrometric uncertainties affecting the equatorial coordinates of the four lensed quasar images is found to be 0.43 mas compared to 3.29 mas using the corresponding HST data. This represents a huge gain (by more than a factor 7) in astrometric precision.

thumbnail Fig. 2.

Distributions of the astrometric parameters and their uncertainties for all the Gaia DR2 counterparts of the individual images of known multiply imaged quasars with five parameter astrometric solutions.

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thumbnail Fig. 3.

Results of the MCMC simulations for HE0435-1223, displayed as a corner plot for the five model parameters. Results obtained from Gaia’s data are presented in red and with HST data in grey. The diagonal panels illustrate the posterior PDFs while the off-axis panels illustrate the correlation between the parameters. The three inner contours represent the 68.3%, 95.4%, and 99.7% confidence intervals.

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thumbnail Fig. 4.

Results of the MCMC simulations for HE0435-1223, displayed as a corner plot for the source and deflector positions. Results obtained from Gaia’s data are presented in red and with HST data in grey. The diagonal panels The diagonal panels illustrate the posterior PDFs while the off-axis panels illustrate the correlation between the parameters. The three inner contours represent the 68.3%, 95.4%, and 99.7% confidence intervals.

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In this section, we illustrate how the improved astrometric accuracy obtained with Gaia may impact the lens modelling. To this end, we propose to optimise a smooth model to the observed image positions alone, within the Bayesian framework. The idea consists in simultaneously sampling the posterior probability density functions (PDFs) for all model parameters using a Markov chain Monte Carlo (MCMC) method, and then comparing the PDFs obtained from Gaia’s astrometry with the ones derived from the astrometry found in the literature. We want to point out that our objective here is not to construct a set of realistic lens models in the sense that they could be used to perform time delay cosmography. Instead, we have focussed on how Gaia astrometric uncertainties may positively affect the goodness of a more complex fit, which would include microlensing-free flux ratios, time delays, non-lensing data related to the main deflector, or even simultaneous reconstruction of the source and deflector surface brightnesses.

We model the main deflector as a singular isothermal ellipsoid (SIE, see e.g. Kormann et al. 1994) which effectively describes the mass distribution of a massive early-type galaxy in the region where multiple images are formed (Gilman et al. 2017). A SIE is characterised by five free parameters; the Einstein radius θE, the elliptical axes ratio q and position angle θq, and the lens centroid (xG, yG) with respect to image A. Since the lensed quasar image positions are generally most sensitive to the local mass distribution, we model the large-scale contributions and possible close line-of-sight galaxy perturbing effects with an external shear term (g) characterised by its absolute value γ and position angle θγ (see e.g., Kochanek et al. 2006). The resulting SIEg model is thus kept simple, which limits the number of free parameters and avoids the use of the full multi-plane lensing formalism (Schneider 2014; McCully et al. 2014, 2016). In addition, we consider the position of the point-like source (βx, βy) with respect to image A that is also free to vary during the optimization process, bringing the number of free parameters nk to nine.

To draw samples from the posterior PDFs, we used emcee4 (Foreman-Mackey et al. 2013), a python package which implements the affine invariant ensemble sampler for MCMC proposed by Goodman & Weare (2010). Since we only used the lensed image positions θobs as observational data to fit, the log-likelihood function simply reads

(1)

where k is the vector of free parameters, N the number of lensed images (hence 2N constraints), σobs the astrometric uncertainties, and θmodel(k) the lensed image positions obtained from the free parameters k and generated with the python package pySPT5 (Wertz & Orthen 2018). To control the sampling, only two hyperparameters need to be tuned: an adjustable scale parameter a and the number Nw of walkers. The scale parameter a has a direct impact on the acceptance rate of each walker, namely the ratio of accepted to proposed candidates, and was set to a = 2, following Goodman & Weare (2010). A walker can be seen as a Metropolis-Hastings chain (see, e.g., MacKay 2003) whose associated proposal distribution depends on the positions of all the other walkers (Foreman-Mackey et al. 2013). Prior to run the MCMC, we initialised Nw = 350 walkers in a small nk-dimensional ball of the parameter space around a highly probable solution, formerly obtained using the public lens modelling code lensmodel6 (v1.99, Keeton 2001). Obviously this initial model may not be the most appropriate one and is more likely a local solution in the parameter space. Nevertheless, it constitutes a valid starting point to illustrate our intention.

The analysis has been performed for the five lenses from Table 2 for which HST image position measurements are available, namely HE0435-1223, SDSS1004+4112, RXJ1131-1231, 2MASS J1134-2103, and WFI2033-4723. In Figs. 3 and 4, we illustrate the MCMC results in the form of corner plots for HE0435-1223, which are representative of each of the five quadruply imaged quasars that we have preliminarily modelled. The HE0435-1223 image positions measured with the Wide Field Camera 3 (IR/F160W, Robberto et al. 2002) mounted on the HST come from Kochanek et al. (2006), showing astrometric uncertainties between 3 and 5 mas. As expected, all the posterior PDFs obtained from the Gaia data show narrower widths than those obtained from HST data, while some of them are slightly shifted. Thus the use of Gaia astrometry data significantly reduces the ranges of valid model parameters around a highly probable solution, as shown in Table 3. The Einstein radius value has only been slightly improved with respect to HST observations, while the source position is constrained within a σ-error ellipse of (σβx, σβy) = (0.1,0.1) mas. This one order of magnitude improvement indicates that the sub-mas astrometry of Gaia clearly helps to better constrain the position of the point-like source as well as the source surface brightness reconstruction as part of a more realistic modelling scenario.

We also note that the Gaia DR2 astrometry reduces significantly the resulting correlation structure between the modelled parameters, in comparison with the correlations obtained from the modelling using HST data: the absolute value of the correlation coefficients between θq and θγ, and θq and q, in Fig. 3 and between βy and yG, and βx and xG in Fig. 4, are clearly reduced thanks to the improved astrometry.

A more advanced version of the lens modelling within the Bayesian framework described in this section will be consistently applied to all the known lenses and to the highly probable lens candidates discovered from a systematic search around quasars (Gaia GraL Paper I, Krone-Martins et al. 2018) and from the systematic blind-search for lenses in the entire Gaia DR2 (Gaia GraL Paper III, Delchambre et al., in prep.), and this will be presented in a forthcoming work (Gaia GraL Paper IV, Wertz et al., in prep.).

Table 3.

SIEg lens model parameters derived for HE0435-1223.

Table 2.

Relative astrometry for five known quadruply imaged quasars fully detected in the Gaia DR2.

6. Conclusions

The availability of high-precision and high-accuracy astrometric data as provided by the ESA/Gaia space mission opens a new window to detect and model gravitationally lensed quasar systems with an unprecedented refinement. This is bound to impact on fundamental applications in astronomy that are derived from this phenomena, such as the study of the lensing galaxy populations, distant quasars, dark matter and dark energy properties and consequently the determination of cosmological parameters. To exploit this new field with the Gaia data, we have set up a collaboration group, the Gaia GraL team, to systematically analyse the gravitationally lensed quasar content throughout the Gaia data releases. The topics covered include searches for new multiply imaged quasar candidates, identifications of known lenses in the Gaia data, modelling of the lenses using the outstanding Gaia astrometry and multi-colour photometry, and fostering ground-based follow-up for final confirmation.

In this paper we explain how we first generated an up-to-date list of known gravitationally lensed quasars, including lensed quasars too faint to be observed by Gaia. The Gaia GraL list of known gravitationally lensed quasars will be kept up-to-date with respect to the astronomical literature at least until the final Gaia data release. Each Gaia data release will be analysed to verify the detection of known gravitational lenses.

Then we provide here the first ever sub-milliarcsecond astrometric data for hundreds of known gravitationally lensed quasars. The search is based on the aforementioned list matched to the Gaia DR2 astrometric catalogue, the largest and most precise astrometric reference available to date. Our lens results bring almost one order of magnitude improvement in astrometric precision compared to a typical HST observation. Moreover, even if Gaia DR2 is still an early data release lacking many lensed images, it brings high-precision astrometry complemented with photometric data for most known lensed systems. Thus, it provides a glimpse of the content that will become available in the forthcoming Gaia data releases.

Of the 481 presently known or candidate gravitationally lensed quasars, we have found in the Gaia DR2 at least one counterpart for 206 of them. From these objects, the quadruply-imaged quasars occupy a specially relevant place, as they provide the more stringent physical parameter inferences. There are 44 presently known quads. From these, 29 have been found with at least one entry in Gaia DR2 and 12 of them are fully detected with all four images. As the images of many of these objects have smaller angular separations than the Gaia DR2 effective angular resolution, we expect the forthcoming data releases to provide information for most images with separations down to ∼0.18″, as the Gaia releases gradually reach the instrument spatial resolution. We also provide Gaia DR2 astrometric and photometric data for all known lenses to date.

Finally, we show that the adoption of high-precision astrometry from Gaia DR2 to model the well-known lens system HE0435-1223 results in a significant improvement in constraining the lens parameters of a SIEg model around a highly probable solution, and that it also significantly reduces the model parameter correlations, in comparison to standard HST astrometry. Such constraints will certainly be further improved with the increased precision of forthcoming Gaia nominal mission data releases, expected for 2020 (DR3) and 2022 (DR4), and the still to be announced data release(s) of the Gaia mission extension.

As a final conclusion this work vividly demonstrates the significant impact of high-precision astrometry from Gaia and future mission concepts as the JASMINE series (Gouda 2011), GaiaNIR (Hobbs et al. 2016), and Theia (The Theia Collaboration et al. 2017), to the study of strong gravitational lensing. This paper also exemplifies the ever wider impact of astrometry and of the Gaia satellite, pushing its limits from its original goal of studying the Milky Way galaxy towards more distant extragalactic sources and associated phenomena.

Acknowledgments

The authors wish to thank the referee for his constructive comments. AKM acknowledges the support from the Portuguese Fundação para a Ciência e a Tecnologia (FCT) through grants SFRH/BPD/74697/2010, from the Portuguese Strategic Programme UID/FIS/00099/2013 for CENTRA, from the ESA contract AO/1-7836/14/NL/HB and from the Caltech Division of Physics, Mathematics and Astronomy for hosting a research leave during 2017-2018, when this paper was prepared. LD and JS acknowledge support from the ESA PRODEX Programme “Gaia-DPAC QSOs” and from the Belgian Federal Science Policy Office. OW acknowledges support from a fellowship for Postdoctoral Researchers by the Alexander von Humboldt Foundation. SGD and MJG acknowledge a partial support from the NSF grants AST-1413600 and AST-1518308, and the NASA grant 16-ADAP16-0232. We acknowledge partial support from “Actions sur projet INSU-PNGRAM”, and from the Brazil-France exchange programmes Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Comité Français d’Évaluation de la Coopération Universitaire et Scientifique avec le Brésil (COFECUB). The authors wish to thank C. Spindola Duarte for her help with the source referencing. This work has made use of the computing facilities of the Laboratory of Astroinformatics (IAG/USP, NAT/Unicsul), whose purchase was made possible by the Brazilian agency FAPESP (grant 2009/54006-4) and the INCT-A, and we thank the entire LAi team, specially Carlos Paladini, Ulisses Manzo Castello, and Alex Carciofi for the support. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France. The original description of the VizieR service was published in A&AS 143, 23. This research has made use of ‘Aladin sky atlas’ developed at CDS, Strasbourg Observatory, France. This work has made use of results from the ESA space mission Gaia, the data from which were processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. The Gaia mission website is: http://www.cosmos.esa.int/gaia. Some of the authors are members of the Gaia Data Processing and Analysis Consortium (DPAC).


References

Appendix A: Gaia DR2 finding charts of known and confirmed quadruply-imaged quasars

thumbnail Fig. A.1.

Finding charts for the known GLs with four counterparts in the Gaia DR2. Gaia DR2 astrometry relative to the brightest image (A image) based on the original system discovery data is indicated by black points (except WGD2038-4008, see footnote in Table B.1). The numbers near each image, and the image size, indicate the flux ratios to the brightest image in the original system discovery data. We note that in some cases this may not be the brightest image detected by Gaia and therefore generates some flux ratios >1. North is up, east is left.

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Appendix B

Table B.1.

List of known quadruply-imaged quasars with at least one match in the Gaia DR2.

All Tables

Table 1.

Statistics of the known multiply imaged quasars present in our reference list (Col. 2) and of the corresponding detected systems in Gaia DR2 (Col. 3).

Table 2.

Relative astrometry for five known quadruply imaged quasars fully detected in the Gaia DR2.

Table 3.

SIEg lens model parameters derived for HE0435-1223.

Table B.1.

List of known quadruply-imaged quasars with at least one match in the Gaia DR2.

All Figures

thumbnail Fig. 1.

All-sky chart in galactic coordinates with the galactic anti-centre in the middle. The known multiply imaged quasars are indicated in grey. The systems presenting one or two counterparts in Gaia DR2 are surrounded by a green open circle. The systems with three Gaia DR2 detections are indicated with purple filled circles, while the systems with four or more detections are indicated with orange filled circles.

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In the text
thumbnail Fig. 2.

Distributions of the astrometric parameters and their uncertainties for all the Gaia DR2 counterparts of the individual images of known multiply imaged quasars with five parameter astrometric solutions.

Open with DEXTER
In the text
thumbnail Fig. 3.

Results of the MCMC simulations for HE0435-1223, displayed as a corner plot for the five model parameters. Results obtained from Gaia’s data are presented in red and with HST data in grey. The diagonal panels illustrate the posterior PDFs while the off-axis panels illustrate the correlation between the parameters. The three inner contours represent the 68.3%, 95.4%, and 99.7% confidence intervals.

Open with DEXTER
In the text
thumbnail Fig. 4.

Results of the MCMC simulations for HE0435-1223, displayed as a corner plot for the source and deflector positions. Results obtained from Gaia’s data are presented in red and with HST data in grey. The diagonal panels The diagonal panels illustrate the posterior PDFs while the off-axis panels illustrate the correlation between the parameters. The three inner contours represent the 68.3%, 95.4%, and 99.7% confidence intervals.

Open with DEXTER
In the text
thumbnail Fig. A.1.

Finding charts for the known GLs with four counterparts in the Gaia DR2. Gaia DR2 astrometry relative to the brightest image (A image) based on the original system discovery data is indicated by black points (except WGD2038-4008, see footnote in Table B.1). The numbers near each image, and the image size, indicate the flux ratios to the brightest image in the original system discovery data. We note that in some cases this may not be the brightest image detected by Gaia and therefore generates some flux ratios >1. North is up, east is left.

Open with DEXTER
In the text

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