TDCOSMO XXIX: JWST/NIRSpec IFU Spatially Resolved Kinematics of Three Time-delay Lenses
(2026)
The promise of self-supervised and active learning for Strong Lens discovery: Astronomaly applied to KiDS
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2026) stag1642
Abstract:
Abstract Strong gravitational lenses (SGLs) are rare systems whose discovery currently relies primarily on supervised machine learning methods trained on large simulated datasets. We present the first application of Astronomaly:PROTEGE to SGL discovery, demonstrating that a human-in-the-loop active learning framework can efficiently identify lenses in large imaging surveys without the need for simulated training data. We consider a sample of 3.7 million bright galaxies from the Kilo-Degree Survey (KiDS) DR4. Feature representations are extracted using a convolutional neural network pre-trained on the ImageNet dataset and subsequently fine-tuned on KiDS data using the self-supervised Bootstrap Your Own Latent (BYOL) framework. Within the embedding of these representations, the active learning loop of Astronomaly iteratively selects the most informative systems for expert inspection. A total of 3,000 objects are inspected across multiple rounds, yielding 34 high-quality (grade A/B) SGL candidates. On the basis that these systems occupy similar regions in the learned feature space, we expand this sample through nearest-neighbour similarity analysis. Including the active learning discoveries, we identify a total of 140 grade A/B candidates and more than 1,000 additional lower-confidence systems (grade C). Among the A/B candidates, 81 are newly identified, while ∼22% of previously known grade A/B KiDS lenses are recovered. These results demonstrate strong potential for next-generation surveys such as Euclid, Roman, and Rubin’s Legacy Survey of Space and Time. With approximately 60% of the high-quality candidates newly reported, this approach complements supervised methods by reducing reliance on simulations and enabling the discovery of a diverse population of SGLs.Little Red Dots: One Photometric Tag Concealing Diverse Spectroscopic Flavors of Massive Star Formation and Black Hole Activity
(2026)
Mid-infrared Colors Vary with Galactic Environment: Contrasting Star-forming Disks, Young Centers, and Quiescent Star-formation Deserts
Astrophysical Journal 1008:1 (2026)
Abstract:
We present 50–100 pc-resolution JWST/MIRI and NIRCam measurements of mid-infrared (mid-IR) color variations in the diffuse interstellar medium (ISM) of 71 nearby star-forming galaxies from the PHANGS-JWST survey. Mid-IR emission traces the dust column density, intensity (U) and hardness of the interstellar radiation field, and the physical state (charge, size) and abundance of polycyclic aromatic hydrocarbons (PAHs). Mid-IR colors that trace PAH band ratios remain fairly constant in the diffuse ISM of star-forming disks. However, they show stark variations in extreme environments: highly star-forming central molecular zones (CMZs) and star formation deserts/quiescent bulges. In CMZs, PAH-to-continuum (3.3/21, 7.7/21, and 11.3/21 μm) and the 10/21 μm continuum colors are 0.2–0.4 dex lower than in normal disks. We attribute this to higher U based on the far-infrared dust colors and the high 21 μm/ΣFrom relics to stripped systems: The environmental origin of compact galaxies
Astronomy & Astrophysics EDP Sciences 713 (2026) A180-A180