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Core Mass Estimates in Strong Lensing Galaxy Clusters: a Comparison Between Masses Obtained from Detailed Lens Models, Single-Halo Lens Models, and Einstein Radii

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 Publication date 2021
  fields Physics
and research's language is English




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The core mass of galaxy clusters is both an important anchor of the radial mass distribution profile and probe of structure formation. With thousands of strong lensing galaxy clusters being discovered by current and upcoming surveys, timely, efficient, and accurate core mass estimates are needed. We assess the results of two efficient methods to estimate the core mass of strong lensing clusters: the mass enclosed by the Einstein radius ($M_{corr}(<theta_E)$ where $theta_{rm E}$ is approximated from arc positions; Remolina Gonz{a}lez et al. 2020), and single-halo lens model ($M_{rm{SHM}}(<rm{e}theta_{rm{E}})$; Remolina Gonz{a}lez et al. 2021), against measurements from publicly available detailed lens models ($M_{rm{DLM}}$) of the same clusters. We use data from the Sloan Giant Arc Survey, the Reionization Lensing Cluster Survey, the Hubble Frontier Fields, and the Cluster Lensing and Supernova Survey with Hubble. We find a scatter of $18.3%$ ($8.4%$) with a bias of $-7.5%$ ($0.4%$) between $M_{corr}(<theta_E)$ ($M_{rm{SHM}}(<rm{e}theta_{rm{E}})$) and $M_{rm{DLM}}$. Last, we compare the statistical uncertainties measured in this work to those from simulations. This work demonstrates the successful application of these methods to observational data. As the effort to efficiently model the mass distribution of strong lensing galaxy clusters continues, we need fast, reliable methods to advance the field.



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Strong gravitational lensing by galaxy clusters magnifies background galaxies, enhancing our ability to discover statistically significant samples of galaxies at z>6, in order to constrain the high-redshift galaxy luminosity functions. Here, we present the first five lens models out of the Reionization Lensing Cluster Survey (RELICS) Hubble Treasury Program, based on new HST WFC3/IR and ACS imaging of the clusters RXC J0142.9+4438, Abell 2537, Abell 2163, RXC J2211.7-0349, and ACT-CLJ0102-49151. The derived lensing magnification is essential for estimating the intrinsic properties of high-redshift galaxy candidates, and properly accounting for the survey volume. We report on new spectroscopic redshifts of multiply imaged lensed galaxies behind these clusters, which are used as constraints, and detail our strategy to reduce systematic uncertainties due to lack of spectroscopic information. In addition, we quantify the uncertainty on the lensing magnification due to statistical and systematic errors related to the lens modeling process, and find that in all but one cluster, the magnification is constrained to better than 20% in at least 80% of the field of view, including statistical and systematic uncertainties. The five clusters presented in this paper span the range of masses and redshifts of the clusters in the RELICS program. We find that they exhibit similar strong lensing efficiencies to the clusters targeted by the Hubble Frontier Fields within the WFC3/IR field of view. Outputs of the lens models are made available to the community through the Mikulski Archive for Space Telescopes
116 - Alexandra Abate 2009
We present weak lensing mass estimates of seven shear-selected galaxy cluster candidates from the Deep Lens Survey. The clusters were previously identified as mass peaks in convergence maps of 8.6 sq. deg of R band imaging, and followed up with X-ray and spectroscopic confirmation, spanning a redshift range 0.19 - 0.68. Most clusters contained multiple X-ray peaks, yielding 17 total mass concentrations. In this paper, we constrain the masses of these X-ray sources with weak lensing, using photometric redshifts from the full set of BVRz imaging to properly weight background galaxies according to their lensing distance ratios. We fit both NFW and singular isothermal sphere profiles, and find that the results are insensitive to the assumed profile. We also show that the results do not depend significantly on the assumed prior on the position of the mass peak, but that this may become an issue in future larger samples. The inferred velocity dispersions for the extended X-ray sources range from 250-800 km/s, with the exception of one source for which no lensing signal was found. This work further establishes shear selection as a viable technique for finding clusters, but also highlights some unresolved issues such as determination of the mass profile center without biasing the mass estimate, and fully accounting for line-of-sight projections. A follow-up paper will examine the mass-X-ray scaling relations of these clusters.
98 - Shawn Knabel 2020
Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies -- such as mixed spectroscopy of multiple galaxies along the line of sight, machine learning algorithms, and citizen science -- have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine learning, and citizen science identification of galaxy-galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the GAMA survey. In these, we have the opportunity to compare high-completeness spectroscopic identifications against high-fidelity imaging from the Kilo Degree Survey (KiDS) used for both machine learning and citizen science lens searches. We find that the three methods -- spectroscopy, machine learning, and citizen science -- identify 47, 47, and 13 candidates respectively in the 180 square degrees surveyed. These identifications barely overlap, with only two identified by both citizen science and machine learning. We have traced this discrepancy to inherent differences in the selection functions of each of the three methods, either within their parent samples (i.e. citizen science focuses on low-redshift) or inherent to the method (i.e. machine learning is limited by its training sample and prefers well-separated features, while spectroscopy requires sufficient flux from lensed features to lie within the fiber). These differences manifest as separate samples in estimated Einstein radius, lens stellar mass, and lens redshift. The combined sample implies a lens candidate sky-density $sim0.59$ deg$^{-2}$ and can inform the construction of a training set spanning a wider mass-redshift space.
We present Hubble Space Telescope (HST) imaging data and CFHT Near IR ground-based images for the final sample of 56 candidate galaxy-scale lenses uncovered in the CFHT Legacy Survey as part of the Strong Lensing in the Legacy Survey (SL2S) project. The new images are used to perform lens modeling, measure surface photometry, and estimate stellar masses of the deflector early-type galaxies. Lens modeling is performed on the HST images (or CFHT when HST is not available) by fitting the spatially extended light distribution of the lensed features assuming a singular isothermal ellipsoid mass profile and by reconstructing the intrinsic source light distribution on a pixelized grid. Based on the analysis of systematic uncertainties and comparison with inference based on different methods we estimate that our Einstein Radii are accurate to sim3%. HST imaging provides a much higher success rate in confirming gravitational lenses and measuring their Einstein radii than CFHT imaging does. Lens modeling with ground-based images however, when successful, yields Einstein radius measurements that are competitive with spaced-based images. Information from the lens models is used together with spectroscopic information from the companion paper IV to classify the systems, resulting in a final sample of 39 confirmed (grade-A) lenses and 17 promising candidates. The redshifts of the main deflector span a range 0.3<zd< 0.8, providing an excellent sample for the study of the cosmic evolution of the mass distribution of early-type galaxies over the second half of the history of the Universe.
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