Zooniverse

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.

Abstract:

We introduce a new kinematic disturbance parameter, (pronounced ‘DVSG’), which takes advantage of integral field spectroscopy (IFS) to quantify differences between a galaxy’s stellar and gas velocity maps. The motivation behind is to capture disturbances in the kinematics of a galaxy that might be missed by alternative methods, while also attempting to minimize bias towards galaxy properties or features of the IFS data. We first detail the reasons for introducing this parameter and explain how the value of a galaxy can be calculated. We then present initial results using to quantify the kinematic disturbance of obscured active galactic nuclei (AGNs) found in the MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) survey. We find that there is no statistically significant difference between the distributions of AGN and a control sample (matched in mass and redshift) of inactive galaxies. This suggests that AGN triggering may not be preferentially caused by any distinct kinematic disturbance process, or combination of processes, beyond those observed in inactive galaxies.

Abstract:

There is now clear evidence, from a variety of studies, that galactic bars contribute to and/or accelerate processes that quench galaxies. However, bars have a variety of strengths and pattern speeds, and previous work has suggested that slow and strong bars impact their hosts the most. In this paper, we continue to investigate the impact of bar strength and bar speed on host galaxy evolution in a sample of barred galaxies identified via classifications from Galaxy Zoo. We perform a comprehensive assessment of star formation tracers spanning a variety of time-scales, based on spatially resolved spectroscopic information from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Specifically, we examine the radial distributions of EW [H ], H , H , and Dn4000; spectral data that trace star formation on current, intermediate, and much longer time-scales. We investigate how these star formation tracers vary with respect to each other in diagnostic evolutionary planes for eight categories of barred galaxies (combinations of star forming or quenching; strong and weak; fast and slow). We continue to find that slow-strong bars drive the quenching of their hosts the most by triggering active star formation throughout the barred region; however, we note some additional complexity: we observe that stronger bars boost star formation at the bar centre while slower bars have increased star formation along the bar. This work adds to the growing evidence that galactic bars have both global and local impacts on their host galaxies.

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.

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).