Daftar Publikasi dengan Tag: Astrophysics - Cosmology and Nongalactic Astrophysics

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 $\sim 1.0--3.0$"), intermediate redshift lenses (z $\sim 0.4-0.7$), 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 $\gt 0.8$" 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 $\sim 0.01$% 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.

We present a catalog of 4195 optically confirmed Sunyaev-Zel'dovich (SZ) selected galaxy clusters detected with signal-to-noise textgreater 4 in 13,211 deg$^2$ of sky surveyed by the Atacama Cosmology Telescope (ACT). Cluster candidates were selected by applying a multi-frequency matched filter to 98 and 150 GHz maps constructed from ACT observations obtained from 2008-2018, and confirmed using deep, wide-area optical surveys. The clusters span the redshift range $0.04 \lt z \lt 1.91$ (median z = 0.52). The catalog contains 222 $z \gt 1$ clusters, and a total of 868 systems are new discoveries. Assuming an SZ-signal vs. mass scaling relation calibrated from X-ray observations, the sample has a 90% completeness mass limit of $\textrm{M500c} \gt 3.8 \times 10^{14}$ M$_\odot$, evaluated at z = 0.5, for clusters detected at signal-to-noise ratio textgreater 5 in maps filtered at an angular scale of 2.4'. The survey has a large overlap with deep optical weak-lensing surveys that are being used to calibrate the SZ-signal mass-scaling relation, such as the Dark Energy Survey (4566 deg$^2$), the Hyper Suprime-Cam Subaru Strategic Program (469 deg$^2$), and the Kilo Degree Survey (825 deg$^2$). We highlight some noteworthy objects in the sample, including potentially projected systems; clusters with strong lensing features; clusters with active central galaxies or star formation; and systems of multiple clusters that may be physically associated. The cluster catalog will be a useful resource for future cosmological analyses, and studying the evolution of the intracluster medium and galaxies in massive clusters over the past 10 Gyr.

Gravitationally lensed quasars are useful for studying astrophysics and cosmology, and enlarging the sample size of lensed quasars is important for multiple studies. In this work, we develop a lens search algorithm for four-image (quad) lensed quasars based on their time variability. In the development of the lens search algorithm, we constructed a pipeline simulating multi-epoch images of lensed quasars in cadenced surveys, accounting for quasar variabilities, quasar hosts, lens galaxies, and the PSF variation. Applying the simulation pipeline to the Hyper Suprime-Cam (HSC) transient survey, we generated HSC-like difference images of the mock lensed quasars from Oguri & Marshall's lens catalog. We further developed a lens search algorithm that picks out variable objects as lensed quasar candidates based on their spatial extent in the difference images. We tested our lens search algorithm with the mock lensed quasars and variable objects from the HSC transient survey. Using difference images from multiple epochs, our lens search algorithm achieves a high true-positive rate (TPR) of 90.1% and a low false-positive rate (FPR) of 2.3% for the bright quads with wide separation. With a preselection of the number of blobs in the difference image, we obtain a TPR of 97.6% and a FPR of 2.6% for the bright quads with wide separation. Even when difference images are only available in one single epoch, our lens search algorithm can still detect the bright quads with wide separation at high TPR of 97.6% and low FPR of 2.4% in the optimal seeing scenario, and at TPR of $\sim94%$ and FPR of $\sim5%$ in typical scenarios. Therefore, our lens search algorithm is promising and is applicable to ongoing and upcoming cadenced surveys, particularly the HSC transient survey and the Rubin Observatory Legacy Survey of Space and Time, for finding new lensed quasar systems. [abridged]