Searching for galaxy-scale strong-lenses in galaxy clusters with deep networks -- I: methodology and network performance
G. Angora, P. Rosati, M. Meneghetti, M. Brescia, A. Mercurio, C. Grillo, P. Bergamini, A. Acebron, G. Caminha, M. Nonino, L. Tortorelli, L. Bazzanini, E. Vanzella
Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological simulations. We search for galaxy-galaxy strong-lensing systems in HST multi-band imaging of galaxy cluster cores from the CLASH and HFF programs by exploring the classification capabilities of deep learning techniques. Convolutional neural networks are trained utilising highly-realistic simulations of galaxy-scale strong lenses injected into the HST cluster fields around cluster members. To this aim, we take advantage of extensive spectroscopic information on member galaxies in 16 clusters and the accurate knowledge of the deflection fields in half of these from high-precision strong lensing models. Using observationally-based distributions, we sample magnitudes, redshifts and sizes of the background galaxy population. By placing these sources within the secondary caustics associated with cluster galaxies, we build a sample of ~3000 galaxy-galaxy strong lenses which preserve the full complexity of real multi-colour data and produce a wide diversity of strong lensing configurations. We study two deep learning networks processing a large sample of image cutouts in three HST/ACS bands, and we quantify their classification performance using several standard metrics. We find that both networks achieve a very good trade-off between purity and completeness (85%-95%), as well as good stability with fluctuations within 2%-4%. We characterise the limited number of false negatives and false positives in terms of the physical properties of the background sources and cluster members. We also demonstrate the neural networks' high degree of generalisation by applying our method to HST observations of 12 clusters with previously known galaxy-scale lensing systems.
Searching for Highly Magnified Stars at Cosmological Distances: Discovery of a Redshift 0.94 Blue Supergiant in Archival Images of the Galaxy Cluster MACS J0416.1-2403
Source REconstruction of Arcs behind Cluster Halos (SourceREACH): A New Source Reconstruction Algorithm Optimized for Giant Arcs and Galaxy Cluster Lenses
Probing sub-galactic mass structure with the power spectrum of surface-brightness anomalies in high-resolution observations of galaxy-galaxy strong gravitational lenses. I. Power-spectrum measurement and feasibility study
A shot in the dark: searching for dark substructures in the RX J0437+00 galaxy cluster
University of Hertfordshire（赫特福德大学）；Durham University（杜伦大学）；University of KwaZulu-Natal（夸祖鲁-纳塔尔大学）；STAR Institute, Quartier Agora - Allée du six Août, 19c B-4000 Liège, Belgium（列日STAR研究所）；Univ. Grenoble Alpes, CNRS, Grenoble INP*, LPSC-IN2P3, 38000 Grenoble, France（格勒诺布尔阿尔卑斯大学）
The first simultaneous measurement of Hubble constant and post-Newtonian parameter from Time-Delay Strong Lensing
强引力透镜一直是宇宙学模型和引力的有力探索。到目前为止，已经分别获得了任一域中的约束。我们提出了一种新的方法，通过它的宇宙学模型，特别是哈勃常数，和后牛顿参数可以同时约束。利用强透镜的时间延迟天体照相术，结合偏转透镜的恒星运动学，我们证明了哈勃常数和后牛顿参数分别包含在反映透镜质量和动力学质量的两个距离比中。通过对H0 LiCOW合作组公开发布的4个透镜距离后验的再分析，得到了哈勃常数和后牛顿参数的同时约束。我们的结果表明，没有偏离广义相对论，具有哈勃常数的$γ_{\texttt{PPN}}=0.87^{+0.19}_{-0.17}$有利于本地宇宙值，$H_0=73.65^{+1.95}_{-2.26}$ km s $^{-1}$ Mpc $^{-1}$。最后，我们预测的鲁棒性的重力测试，通过使用时间延迟强透镜的约束，我们预计在未来几年。我们发现，40个透镜的联合约束能够达到后牛顿参数的$7.7\%$和哈勃常数的$1.4\%$的数量级。
Probing sub-galactic mass structure with the power spectrum of surface-brightness anomalies in high-resolution observations of galaxy-galaxy strong gravitational lenses. II.Observational constraints on the sub-galactic matter power spectrum
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: A Catalogue of Strong Galaxy-Galaxy Lens Candidates
我们在斯隆数字巡天（SDSS）第十六次数据发布（DR 16）的扩展重子振荡光谱巡天（eBOSS）中包含的$\approx2$百万个星系光谱中，光谱检测到838个可能的候选者，448个可能的候选者和265个可能的强透镜候选者。我们应用重子振荡光谱巡天（BOSS）发射线透镜巡天（BELLS）的光谱检测方法，并添加高斯拟合信息，分级，额外的检查观测量和额外的检查方法来改进我们的选择方法。我们在SDSS-I/II的Legacy调查和DESI Legacy调查的低分辨率图像中观察到477名候选人具有透镜证据，这比使用类似透镜证据观察到的BELLS候选人的百分比高$12\%$。我们在BOSS调查的最新和改进的缩减范围内进行的搜索，在搜索所有BOSS和eBOSS星系时，预期透镜候选者的数量增加了$20\%$。我们的候选者的目标和背景红移的分布是类似的候选者和确认的透镜内的贝尔观测。我们在SDSS DR 16的增值目录（VAC）中展示了我们的透镜物体光谱识别（SILO）候选者。在后续的高分辨率成像中对这些透镜候选者的检查可能会产生比SDSS中以前的光谱检测调查中发现的透镜多两倍的透镜，这将把SDSS中以前的透镜调查结果扩展到更高的红移，限制螺旋星系中质量结构的模型，并测试在低分辨率图像中包括可能的透镜特征的识别是否对光谱检测程序有价值。
Implications from simulated strong gravitational lensing systems: constraining cosmological parameters using Gaussian Processes
强引力透镜系统（SGL）将宇宙学信息编码为源/透镜距离比$\mathcal{D}_{\rm obs}=\mathcal{D}_{\rm ls}/\mathcal{D}_{\rm s}$，可用于精确约束宇宙学参数。在本文中，基于未来的测量390强透镜系统从即将到来的LSST调查，我们已经成功地重建的距离比$\mathcal{D}_{\rm obs}$（与源红移$z_s\sim 4.0$），直接从数据，而不假设任何参数的形式。最近开发的方法的基础上，模型无关的重建方法，高斯过程（GP）被用于我们的研究这些强透镜系统。我们的研究结果表明，独立测量的物质密度参数（$Ω_m$），可以预期从这样强的透镜统计。更具体地说，可以预期在一致性$Λ$ CDM模型中以$ΔΩ_m\sim0.015$的精度估计$Ω_m$，该模型提供了与普朗克2015结果相当的$Ω_m$约束。在修正的引力理论（DGP）框架下，未来LSST巡天的390个可探测星系透镜体将导致$ΔΩ_m\sim0.030$的严格拟合。\textbf{Finally, we have discussed three possible sources of systematic errors (sample incompleteness, the determination of length of lens redshift bin, and t…
