Search

We report the results of searches for strong gravitational lens systems in the Dark Energy Survey (DES) Science Verification and Year 1 observations. The Science Verification data span approximately 250 sq. deg. with a median i-band limiting magnitude for extended objects (10σ) of 23.0. The Year 1 data span approximately 2000 sq. deg. and have an i-band limiting magnitude for extended objects (10σ) of 22.9. As these data sets are both wide and deep, they are particularly useful for identifying strong gravitational lens candidates. Potential strong gravitational lens candidate systems were initially identified based on a color and magnitude selection in the DES object catalogs or because the system is at the location of a previously identified galaxy cluster. Cutout images of potential candidates were then visually scanned using an object viewer and numerically ranked according to whether or not we judged them to be likely strong gravitational lens systems. Having scanned nearly 400,000 cutouts, we present 374 candidate strong lens systems, of which 348 are identified for the first time. We provide the R.A. and decl., the magnitudes and photometric properties of the lens and source objects, and the distance (radius) of the source(s) from the lens center for each system.

Strong lensing is a powerful probe of the matter distribution in galaxies and clusters and a relevant tool for cosmography. Analyses of strong gravitational lenses with deep learning have become a popular approach due to these astronomical objects' rarity and image complexity. Next-generation surveys will provide more opportunities to derive science from these objects and an increasing data volume to be analysed. However, finding strong lenses is challenging, as their number densities are orders of magnitude below those of galaxies. Therefore, specific strong lensing search algorithms are required to discover the highest number of systems possible with high purity and low false alarm rate. The need for better algorithms has prompted the development of an open community data science competition named strong gravitational lensing challenge (SGLC). This work presents the deep learning strategies and methodology used to design the highest scoring algorithm in the second SGLC (II SGLC). We discuss the approach used for this data set, the choice of a suitable architecture, particularly the use of a network with two branches to work with images in different resolutions, and its optimization. We also discuss the detectability limit, the lessons learned, and prospects for defining a tailor-made architecture in a survey in contrast to a general one. Finally, we release the models and discuss the best choice to easily adapt the model to a data set representing a survey with a different instrument. This work helps to take a step towards efficient, adaptable, and accurate analyses of strong lenses with deep learning frameworks. [ABSTRACT FROM AUTHOR]

We have modelled ~0.1 arcsec resolution Atacama Large Millimetre/submillimeter Array imaging of six strong gravitationally lensed galaxies detected by the Herschel Space Observatory. Our modelling recovers mass properties of the lensing galaxies and, by determining magnification factors, intrinsic properties of the lensed submillimetre sources. We find that the lensed galaxies all have high ratios of star formation rate to dust mass, consistent with or higher than the mean ratio for high-redshift submillimetre galaxies and low-redshift ultraluminous infrared galaxies. Source reconstruction reveals that most galaxies exhibit disturbed morphologies. Both the cleaned image plane data and the directly observed interferometric visibilities have been modelled, enabling comparison of both approaches. In the majority of cases, the recovered lens models are consistent between methods, all six having mass density profiles that are close to isothermal. However, one system with poor signal to noise shows mildly significant differences. [ABSTRACT FROM AUTHOR]

With the advent of wide-area submillimetre surveys, a large number of high-redshift gravitationally lensed dusty star-forming galaxies have been revealed. Because of the simplicity of the selection criteria for candidate lensed sources in such surveys, identified as those with S500 µm > 100 mJy, uncertainties associated with the modelling of the selection function are expunged. The combination of these attributes makes submillimetre surveys ideal for the study of strong lens statistics. We carried out a pilot study of the lensing statistics of submillimetreselected sources by making observations with the Atacama Large Millimeter Array (ALMA) of a sample of strongly lensed sources selected from surveys carried out with the Herschel Space Observatory. We attempted to reproduce the distribution of image separations for the lensed sources using a halo mass function taken from a numerical simulation that contains both dark matter and baryons. We used three different density distributions, one based on analytical fits to the haloes formed in the EAGLE simulation and two density distributions [Singular Isothermal Sphere (SIS) and SISSA] that have been used before in lensing studies. We found that we could reproduce the observed distribution with all three density distributions, as long as we imposed an upper mass transition of ~1013M⊙ for the SIS and SISSA models, above which we assumed that the density distribution could be represented by a Navarro-Frenk-White profile. We show that we would need a sample of ~500 lensed sources to distinguish between the density distributions, which is practical given the predicted number of lensed sources in the Herschel surveys. [ABSTRACT FROM AUTHOR]

We present a sample of 80 candidate strongly lensed galaxies with flux density above 100 mJy at 500 μm extracted from the Herschel Astrophysical Terahertz Large Area Survey, over an area of 600 deg2. Available imaging and spectroscopic data allow us to confirm the strong lensing in 20 cases and to reject it in one case. For other eight objects, the lensing scenario is strongly supported by the presence of two sources along the same line of sight with distinct photometric redshifts. The remaining objects await more follow-up observations to confirm their nature. The lenses and the background sources have median redshifts zL = 0.6 and zS = 2.5, respectively, and are observed out to zL =1.2 and zS =4.2.We measure the number counts of candidate lensed galaxies at 500 μm and compare them with theoretical predictions, finding a good agreement for a maximummagnification of the background sources in the range 10-20. These values are consistent with the magnification factors derived from the lens modelling of individual systems. The catalogue presented here provides sub-mm bright targets for follow-up observations aimed at exploiting gravitational lensing, to study with unprecedented details the morphological and dynamical properties of dusty star-forming regions in z ≳ 1.5 galaxies. [ABSTRACT FROM AUTHOR]

We have modelled Atacama Large Millimetre/sub-millimetre Array (ALMA) long baseline imaging of the strong gravitational lens system H-ATLAS J090311.6+003906 (SDP.81). We have reconstructed the distribution of band 6 and 7 continuum emission in the z = 3.042 source and determined its kinematic properties by reconstructing CO(5-4) and CO(8-7) line emission in bands 4 and 6. The continuum imaging reveals a highly non-uniform distribution of dust with clumps on scales of ~200 pc. In contrast, the CO line emission shows a relatively smooth, disc-like velocity field which is well fitted by a rotating disc model with an inclination angle of (40 ± 5)° and an asymptotic rotation velocity of 320 kms-1. The inferred dynamical mass within 1.5 kpc is (3.5 ± 0.5) × 1010 M⊙ which is comparable to the total molecular gas masses of (2.7 ± 0.5) × 1010 M⊙ and (3.5 ± 0.6) × 1010 M⊙ from the dust continuum emission and CO emission, respectively. Our new reconstruction of the lensed Hubble Space Telescope near-infrared emission shows two objects which appear to be interacting, with the rotating disc of gas and dust revealed by ALMA distinctly offset from the near-infrared emission. The clumpy nature of the dust and a low value of the Toomre parameter of Q ~ 0.3 suggest that the disc is in a state of collapse. We estimate a star formation rate in the disc of 470 ± 80 M⊙ yr-1 with an efficiency ~65 times greater than typical low-redshift galaxies. Our findings add to the growing body of evidence that the most infrared luminous, dust obscured galaxies in the high-redshift Universe represent a population of merger-induced starbursts. [ABSTRACT FROM AUTHOR]

Simple models of gravitational arcs are crucial for simulating large samples of these objects with full control of the input parameters. These models also provide approximate and automated estimates of the shape and structure of the arcs, which are necessary for detecting and characterizing these objects on massive wide-area imaging surveys. We here present and explore the ArcEllipse, a simple prescription for creating objects with a shape similar to gravitational arcs. We also present PaintArcs, which is a code that couples this geometrical form with a brightness distribution and adds the resulting object to images. Finally, we introduce ArcFitting, which is a tool that fits ArcEllipses to images of real gravitational arcs. We validate this fitting technique using simulated arcs and apply it to CFHTLS and HST images of tangential arcs around clusters of galaxies. Our simple ArcEllipse model for the arc, associated to a Sérsic profile for the source, recovers the total signal in real images typically within 10%-30%. The ArcEllipse+Sérsic models also automatically recover visual estimates of length-to-width ratios of real arcs. Residual maps between data and model images reveal the incidence of arc substructure. They may thus be used as a diagnostic for arcs formed by the merging of multiple images. The incidence of these substructures is the main factor that prevents ArcEllipse models from accurately describing real lensed systems. [ABSTRACT FROM AUTHOR]