Detection of an extremely luminous radio counterpart to the Be/X-ray binary A0538−66
Monthly Notices of the Royal Astronomical Society Oxford University Press 548:1 (2026) stag224
Abstract:
We present the discovery of radio emission from the Be/X-ray binary A0538−66 with the Australian Square Kilometre Array Pathfinder, and results from a subsequent weekly monitoring campaign with the MeerKAT radio telescope. A0538−66, located in the Large Magellanic Cloud, hosts a neutron star with a short spin period ( ms) in a highly eccentric -d orbit . Its rare episodes of super-Eddington accretion, rapid optical and X-ray flares, and other peculiar properties make it an interesting system among high-mass X-ray binaries. Our MeerKAT data reveal that it is also one of the most radio-luminous neutron star X-ray binaries observed to date, reaching (at 1.28 GHz), with radio emission that appears to be orbitally modulated. We consider several possible mechanisms for the radio emission, and place A0538−66 in context by comparing it to similar systems.Detection of an Extremely Luminous Radio Counterpart to the Be/X-ray Binary A0538-66
(2026)
Bars in low-density environments rotate faster than bars in dense regions
Monthly Notices of the Royal Astronomical Society Oxford University Press 547:2 (2026) stag175
Abstract:
Does the environment of a galaxy directly influence the kinematics of its bar? We present observational evidence that bars in high-density environments exhibit significantly slower rotation rates than bars in low-density environments. Galactic bars are central, extended structures composed of stars, dust and gas, present in approximately 30–70 per cent of luminous spiral galaxies in the local Universe. Recent simulation studies have suggested that the environment can influence the bar rotation rate, , which is used to classify bars as either fast () or slow (). We use estimates of obtained with the Tremaine–Weinberg method applied to Integral Field Unit spectroscopy from Mapping Nearby Galaxies at Apache Point Observatory and Calar Alto Legacy Integral Field Area. After cross-matching these with the projected neighbour density, , we retain 286 galaxies. The analysis reveals that bars in high-density environments are significantly slower (median ) compared to bars in low-density environments (median ); Anderson–Darling p-value of (). This study marks the first empirical test of the hypothesis that fast bars are formed by global instabilities in isolated galaxies, while slow bars are triggered by tidal interactions in dense environments, in agreement with predictions from numerous N-body simulations. Future studies would benefit from a larger sample of galaxies with reliable Integral Field Unit data, required to measure bar rotation rates. Specifically, more data are necessary to study the environmental influence on bar formation within dense settings (i.e. groups, clusters and filaments).Galaxy Zoo: Cosmic Dawn – morphological classifications for over 41 000 galaxies in the Euclid Deep Field North from the Hawaii Two-0 Cosmic Dawn survey
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2025) staf2250
Abstract:
Abstract We present morphological classifications of over 41 000 galaxies out to zphot ∼ 2.5 across six square degrees of the Euclid Deep Field North (EDFN) from the Hawaii Twenty Square Degree (H20) survey, a part of the wider Cosmic Dawn survey. Galaxy Zoo citizen scientists play a crucial role in the examination of large astronomical data sets through crowdsourced data mining of extragalactic imaging. This iteration, Galaxy Zoo: Cosmic Dawn (GZCD), saw tens of thousands of volunteers and the deep learning foundation model Zoobot collectively classify objects in ultra-deep multiband Hyper Suprime-Cam (HSC) imaging down to a depth of mHSC − i = 21.5. Here, we present the details and general analysis of this iteration, including the use of Zoobot in an active learning cycle to improve both model performance and volunteer experience, as well as the discovery of 51 new gravitational lenses in the EDFN. We also announce the public data release of the classifications for over 45 000 subjects, including more than 41 000 galaxies (median zphot of 0.42 ± 0.23), along with their associated image cutouts. This data set provides a valuable opportunity for follow-up imaging of objects in the EDFN as well as acting as a truth set for training deep learning models for application to ground-based surveys like that of the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) collaboration and the newly operational Vera C. Rubin Observatory.Strong Bars, Strong Inflow: The Effect of Bar Strength on Gas Inflow
Research Notes of the American Astronomical Society IOP Publishing 9:12 (2025) 341