A free-form lensing model of A370 revealing stellar mass dominated BCGs, in Hubble Frontier Fields images

Diego, J. M.; Schmidt, Kasper B.; Broadhurst, Tom; Lam, Daniel; Vega-Ferrero, Jesús; Zheng, Wei; Lee, Slanger; Morishita, Takahiro; Bernstein, G. M.; Lim, Jeremy; Silk, Joseph; Ford, H. C.

doi:10.1093/mnras/stx2609

Cited by 45 publications

(40 citation statements)

References 71 publications

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“…However, we do find one prominent redshift overdensity at z ∼ 1.05, where the number of objects is more than double any other redshift bin. This overdensity, which is also detected in Diego et al (2018), consists of a significantly larger number of galaxies than either of the foreground groups, and may be indicative of additional substructure. As background objects, these galaxies also have a much better chance of affecting the positions of observed lensing constraints, so we investigate their effects on the mass model in Section 5.…”

Section: Foreground and Background Objectsmentioning

confidence: 72%

“…• System 3: While this system was too far north to be seen in the GTO cube, Images 3.1 and 3.2 did have low-resolution grism spectroscopy from GLASS (Diego et al 2018;hereafter D18), and we used this redshift (z GLASS = 1.95) in our earlier mass model. In the mosaic catalog, we detect C iii] emission in the central regions of these two images, giving rise to an updated redshift Ly-α and Ly-Break Figure 3.…”

Section: Multiply-imaged Systemsmentioning

confidence: 99%

“…Similarly, we use model predictions to investigate Systems 7 and 10, which may also be linked together. This possibility is presented in Diego et al (2018), who find that by decreasing the mass-to-light ratio of the two BCGs (which subsequently reduces the dark matter content of the galaxies), their model is able to fit all counterimages of both systems using a single source galaxy. This is a particularly intriguing possibility, not only because a combined System 7+10 would create yet another system with a large number of counterimages (n > 5) and one with multiple radial arcs, but also because the proposed solution -a BCG that is significantly depleted of dark matter -would be at odds with N-body simulations, and may challenge our un- 6 ).…”

Section: Complex Multiple-image Groupsmentioning

confidence: 99%

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Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

Lagattuta

Richard

Bauer

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We present an updated strong-lensing analysis of the massive cluster Abell 370 (A370), continuing the work first presented in Lagattuta et al. (2017). In this new analysis, we take advantage of the deeper imaging data from the Hubble Space Telescope (HST) Frontier Fields program, as well as a large spectroscopic mosaic obtained with the Multi-Unit Spectroscopic Explorer (MUSE). Thanks to the extended coverage of this mosaic, we probe the full 3D distribution of galaxies in the field, giving us a unique picture of the extended structure of the cluster and its surroundings. Our final catalog contains 584 redshifts, representing the largest spectroscopic catalog of A370 to date. Constructing the model, we measure a total mass distribution that is quantitatively similar to our previous work -though to ensure a low rms error in the model fit, we invoke a significantly large external shear term. Using the redshift catalog, we search for other bound groups of galaxies, which may give rise to a more physical interpretation of this shear. We identify three structures in narrow redshift ranges along the line of sight, highlighting possible infalling substructures into the main cluster halo. We also discover additional substructure candidates in low-resolution imaging at larger projected radii. More spectroscopic coverage of these regions (pushing close to the A370 virial radius) and more extended, high-resolution imaging will be required to investigate this possibility, further advancing the analysis of these interesting developments.

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Section: Foreground and Background Objectsmentioning

confidence: 72%

Section: Multiply-imaged Systemsmentioning

confidence: 99%

Section: Complex Multiple-image Groupsmentioning

confidence: 99%

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Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

Lagattuta

Richard

Bauer

et al. 2019

Monthly Notices of the Royal Astronomical Society

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“…Gravitational lensing offers a direct probe of the cluster mass distribution through observations of weak shear lensing (e.g., Gruen et al 2014;von der Linden et al 2014;Hoekstra et al 2015;Melchior et al 2017;Sereno et al 2017a;Medezinski et al 2018), weak magnification lensing (e.g., Hildebrandt et al 2011;Umetsu et al 2011b;Coupon et al 2013;Chiu et al 2016;Tudorica et al 2017), strong gravitational lensing (e.g., Broadhurst et al 2005a;Zitrin et al 2013;Jauzac et al 2015;Cerny et al 2017;Diego et al 2018), and the combination of these effects (e.g., Umetsu et al 2011a;Coe et al 2012;Medezinski et al 2013;Umetsu et al 2015Umetsu et al , 2016. The critical advantage of gravitational lensing is its unique ability to map the mass distribution independently of assumptions about their physical or dynamical state.…”

Section: Introductionmentioning

confidence: 99%

The Projected Dark and Baryonic Ellipsoidal Structure of 20 CLASH Galaxy Clusters*

Umetsu

Sereno

Tam

et al. 2018

ApJ

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We reconstruct the two-dimensional (2D) matter distributions in 20 high-mass galaxy clusters selected from the CLASH survey by using the new approach of performing a joint weak gravitational lensing analysis of 2D shear and azimuthally averaged magnification measurements. This combination allows for a complete analysis of the field, effectively breaking the mass-sheet degeneracy. In a Bayesian framework, we simultaneously constrain the mass profile and morphology of each individual cluster, assuming an elliptical Navarro-Frenk-White halo characterized by the mass, concentration, projected axis ratio, and position angle (PA) of the projected major axis. We find that spherical mass estimates of the clusters from azimuthally averaged weak-lensing measurements in previous work are in excellent agreement with our results from a full 2D analysis. Combining all 20 clusters in our sample, we detect the elliptical shape of weak-lensing halos at the 5σ significance level within a scale of 2 h Mpc 1 -. The median projected axis ratio is 0.67±0.07 at a virial mass of M M 15.2 2.8 10 vir 14 = ´ ( ) , which is in agreement with theoretical predictions from recent numerical simulations of the standard collisionless cold dark matter model. We also study misalignment statistics of the brightest cluster galaxy, X-ray, thermal Sunyaev-Zel'dovich effect, and strong-lensing morphologies with respect to the weak-lensing signal. Among the three baryonic tracers studied here, we find that the X-ray morphology is best aligned with the weak-lensing mass distribution, with a median misalignment angle of PA 21We also conduct a stacked quadrupole shear analysis of the 20 clusters assuming that the X-ray major axis is aligned with that of the projected mass distribution. This yields a consistent axis ratio of 0.67±0.10, suggesting again a tight alignment between the intracluster gas and dark matter.

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“…As such, lensing can be exploited to measure the distribution of mass in the Universe (e.g. Newman et al 2013;Han et al 2015;Diego et al 2018;Jauzac et al 2018), enhance the study of lensed high redshift galaxies (e.g. Coe et al 2013;Jones et al 2013;Stark et al 2015;Dye et al 2015) and constrain cosmological models (e.g.…”

Section: Introductionmentioning

confidence: 99%

Identifying strong lenses with unsupervised machine learning using convolutional autoencoder

Cheng

Conselice

et al. 2020

Monthly Notices of the Royal Astronomical Society

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In this paper we develop a new unsupervised machine learning technique comprising of a feature extractor, a convolutional autoencoder (CAE), and a clustering algorithm consisting of a Bayesian Gaussian mixture model (BGM). We applied this technique to visual band space-based simulated imaging data from the Euclid Space Telescope using data from the Strong Gravitational Lenses Finding Challenge. Our technique promisingly captures a variety of lensing features such as Einstein rings with different radii, distorted arc structures, etc, without using predefined labels. After the clustering process, we obtain several classification clusters separated by different visual features which seen in the images. Our method successfully picks up ∼63 percent of lensing images from all lenses in the training set. With the assumed probability proposed in this study, this technique reaches an accuracy of 77.25 ± 0.48% in binary classification using the training set. Additionally, our unsupervised clustering process can be used as the preliminary classification for future surveys of lenses to efficiently select targets and to speed up the labelling process. As the starting point of the astronomical application using this technique, we not only explore the application to gravitaional lensing systems, but also discuss the limitations and potential future uses of this technique.

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A free-form lensing model of A370 revealing stellar mass dominated BCGs, in Hubble Frontier Fields images

Cited by 45 publications

References 71 publications

Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

Probing 3D Structure with a Large MUSE Mosaic: Extending the Mass Model of Frontier Field Abell 370

The Projected Dark and Baryonic Ellipsoidal Structure of 20 CLASH Galaxy Clusters*

Identifying strong lenses with unsupervised machine learning using convolutional autoencoder

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