Beyond compactness: A structural–dynamical–evolutionary manifold for the stellar-to-dynamical mass ratio in ultra-compact massive galaxies
Astronomy and Astrophysics 709 (2026)
Abstract:
Context. Ultra-compact massive galaxies (UCMGs) often exhibit elevated stellar-to-dynamical mass ratios when dynamical masses are estimated using standard virial prescriptions. This discrepancy has been interpreted as evidence for structural non-homology driven primarily by their compactness. Aims. This study investigates how the stellar-to-dynamical mass ratio depends on compactness (C), internal kinematics (σDiscovering 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.MIGHTEE-H i: the star-forming properties of H i -selected galaxies
Monthly Notices of the Royal Astronomical Society Oxford University Press 548:4 (2026) stag810
Abstract:
The interplay between atomic gas and the star formation history (SFH) of a galaxy are intrinsically linked, and we need to decouple these dependencies to understand their role in galaxy formation and evolution. In this paper, we analyse the SFH of 203 galaxies from the MIGHTEE-H i Survey Early Science Release data, cross-matched to with multiwavelength photometry across the COSMOS and XMM-LSS fields. We focus on the relationships between H i properties and star formation, with a sample which primarily traces gas-rich, star-forming systems at low redshift, extending to low stellar masses and probing regimes that are difficult to access with optically selected samples. A strong correlation emerges between a galaxy’s H i-to-stellar mass ratio and the time of formation, alongside an inverse correlation between stellar mass and time of formation, regardless of the inferred SFH. Additionally, galaxies with lower stellar masses and higher H i-to-stellar mass ratios exhibit longer gas depletion times compared to more massive galaxies, which appear to have depleted their gas and formed stars more efficiently. This suggests that smaller, gas-rich galaxies have higher depletion times due to shallower potential wells and less efficient star formation. Within this H i-selected sample, the efficiency of star formation is regulated primarily by stellar mass and gas fraction, with low-mass galaxies retaining extended atomic reservoirs due to inefficient conversion of H i into stars.The functional form of galaxy and halo luminosity and mass functions
(2026)
AT2024wpp: An Extremely Luminous Fast Ultraviolet Transient Powered by Accretion onto a Black Hole
(2026)