Discovering Strong Gravitational Lenses in the Dark Energy Survey with Interactive Machine Learning and Crowd-sourced Inspection with Space Warps
The Astrophysical Journal American Astronomical Society 1002:2 (2026) 116
Abstract:
We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces ∼236 million DES cutout images to 22,564 targets of interest, including ∼85% of previously reported galaxy–galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out ∼90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified as “definite” lenses and 516 as “probable” lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy–galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include ∼100 of our “definite” lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.Decoupling the AGN outflow and star-forming disc kinematics in the nuclear region of NGC 7582 with JWST NIRSpec and MIRI/MRS
Monthly Notices of the Royal Astronomical Society Oxford University Press 548:4 (2026) stag785
Abstract:
We present a detailed study of the inner regions of NGC 7582, a nearby Seyfert 2 galaxy, from the Galaxy Activity, Torus, and Outflow Survey (GATOS). The galaxy hosts a circumnuclear star-forming disc and an active galactic nucleus (AGN)-driven biconical ionized outflow. Using James Webb Space Telescope Near-Infrared Spectrograph (NIRSpec) and Mid-Infrared Instrument/Medium-Resolution Spectrometer (MIRI/MRS) integral-field spectroscopy, we analyse ionic emission lines spanning a wide range of ionization potentials (IPs, –126 eV). Gaussian line-profile fitting reveals kinematic stratification: low-IP species ( eV; e.g. [Fe ii], [Ar ii], and [Ne ii]) trace ordered disc rotation with PA , while high-IP species ( eV; e.g. [O iv], [Mg iv], and [Ne v]) follow the outflow with PA . Outflowing gas exhibits systematically higher velocity dispersions ( km s−1) than the disc ( km s−1), consistent with turbulent or bulk motions. Intermediate-IP lines, [S iii], [Ar iii], and [Ne iii], show contributions from both components, with the outflow characterized by higher dispersion, lower amplitude, and higher velocities in double-Gaussian fits. For these lines, a thin inclined disc plus 1D outflow model enables robust separation and quantification of the disc and outflow velocity fields. The outflow is consistent with a hollow bicone capable of accelerating gas beyond the local escape velocity, implying most material is unlikely to be re-accreted. The ionization cone opening angle shows no dependence on IP, indicating the AGN torus polar regions are largely unobscured. Our study provides new insights into AGN-driven outflows and circumnuclear disc dynamics, offering a framework to disentangle overlapping interstellar medium kinematics in nearby active galaxies.TDCOSMO XXV: A "soup-to-nuts" 6.5% $H_0$ measurement $-$ strong lensing and dynamics with a maximally flexible mass sheet
(2026)
Spatially Resolved Kinematics of SLACS Lens Galaxies. II: Breaking Degeneracies with Lensing and Dynamical Models
(2026)
The WEAVE acquisition and guiding software: pattern recognition-based acquisition and multifibre guiding
RAS Techniques and Instruments Oxford University Press 5 (2026) rzag026