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Register a new userHOLISMOKES. VI. New galaxy-scale strong lens candidates from the HSC-SSP imaging survey
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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.
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We report the largest sample of candidate strong gravitational lenses belonging to the Survey of Gravitationally-lensed Objects in HSC Imaging for group-to-cluster scale (SuGOHI-c) systems. These candidates are compiled from the S18A data release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. We visually inspect $sim39,500$ galaxy clusters, selected from several catalogs, overlapping with the Wide, Deep, and UltraDeep fields, spanning the cluster redshift range $0.05<z_{cl}<1.38$. We discover 641 candidate lens systems, of which 536 are new. From the full sample, 47 are almost certainly bonafide lenses, 181 of them are highly probable lenses and 413 are possible lens systems. Additionally, we present 131 lens candidates at galaxy-scale serendipitously discovered during the inspection. We obtained spectroscopic follow-up of 10 candidates using the X-shooter. With this follow-up, we confirm 8 systems as strong gravitational lenses. Of the remaining two, one of the sources is too faint to detect any emission, and the other has a tentative redshift close to the lens redshift, but additional arcs in this system are yet to be observed spectroscopically. Since the HSC-SSP is an ongoing survey, we expect to find $sim600$ definite or probable lenses using this procedure and even more if combined with other lens finding methods.
We present a list of galaxy-scale lens candidates including a highly probable interacting galaxy-scale lens in the Hyper Suprime-Cam (HSC) imaging survey. We combine HSC imaging with the blended-spectra catalog from the Galaxy And Mass Assembly (GAMA) survey to identify lens candidates, and use lens mass modeling to confirm the candidates. We find 46 matches between the HSC S14A_0b imaging data release and the GAMA catalog. Ten of them are probable lens systems according to their morphology and redshifts. There is one system with an interacting galaxy pair, HSC J084928+000949, that has a valid mass model. We predict the total mass enclosed by the Einstein radius of $sim0.72$ ($sim1.65$kpc) for this new expected lens system to be $sim10^{10.59}M_{odot}$. Using the photometry in the {it grizy} bands of the HSC survey and stellar population synthesis modeling with a Salpeter stellar initial mass function, we estimate the stellar mass within the Einstein radius to be $sim10^{10.46},M_{odot}$. We thus find a dark matter mass fraction within the Einstein radius of $sim25%$. Further spectroscopy or high-resolution imaging would allow confirmation of the nature of these lens candidates. The particular system with the interacting galaxy pair, if confirmed, would provide an opportunity to study the interplay between dark matter and stars as galaxies build up through hierarchical mergers.
We present a lensed quasar search based on the variability of lens systems in the HSC transient survey. Starting from 101,353 variable objects with i-band photometry in the HSC transient survey, we used a variability-based lens search method measuring the spatial extent in difference images to select potential lensed quasar candidates. We adopted conservative constraints in this variability selection and obtained 83,657 variable objects as possible lens candidates. We then ran CHITAH, a lens search algorithm based on the image configuration, on those 83,657 variable objects, and 2,130 variable objects were identified as potential lensed objects. We visually inspected the 2,130 variable objects, and seven of them are our final lensed quasar candidates. Additionally, we found one lensed galaxy candidate as a serendipitous discovery. Among the eight final lensed candidates, one is the only known quadruply lensed quasar in the survey field, HSCJ095921+020638. None of the other seven lensed candidates have been previously classified as a lens nor a lensed candidate. Three of the five final candidates with available HST images, including HSCJ095921+020638, show clues of a lensed feature in the HST images. A tightening of variability selection criteria might result in the loss of possible lensed quasar candidates, especially the lensed quasars with faint brightness or narrow separation, without efficiently eliminating the non-lensed objects; CHITAH is therefore important as an advanced examination to improve the lens search efficiency through the object configuration. The recovery of HSCJ095921+020638 proves the effectiveness of the variability-based lens search method, and this lens search method can be used in other cadenced imaging surveys, such as the upcoming Rubin Observatory Legacy Survey of Space and Time.
We report on a spectroscopic program to search for dual quasars using Subaru Hyper Suprime-Cam (HSC) images of SDSS quasars which represent an important stage during galaxy mergers. Using Subaru/FOCAS and Gemini-N/GMOS, we identify three new physically associated quasar pairs having projected separations less than 20 kpc, out of 26 observed candidates. These include the discovery of the highest redshift ($z=3.1$) quasar pair with a separation $<$ 10 kpc. Based on the sample acquired to date, the success rate of identifying physically associated dual quasars is $19%$ when excluding stars based on their HSC colors. Using the full sample of six spectroscopically confirmed dual quasars, we find that the black holes in these systems have black hole masses ($M_{BH} sim 10^{8-9}M_{odot}$) similar to single SDSS quasars as well as their bolometric luminosities and Eddington ratios. We measure the stellar mass of their host galaxies based on 2D image decomposition of the five-band ($grizy$) optical emission and assess the mass relation between supermassive black holes (SMBHs) and their hosts. Dual SMBHs appear to have elevated masses relative to their host galaxies. Thus mergers may not necessarily align such systems onto the local mass relation, as suggested by the Horizon-AGN simulation. This study suggests that dual luminous quasars are triggered prior to the final coalescence of the two SMBHs, resulting in early mass growth of the black holes relative to their host galaxies.
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.
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