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  1. Abstract We have found a class of circular radio objects in the Evolutionary Map of the Universe Pilot Survey, using the Australian Square Kilometre Array Pathfinder telescope. The objects appear in radio images as circular edge-brightened discs, about one arcmin diameter, that are unlike other objects previously reported in the literature. We explore several possible mechanisms that might cause these objects, but none seems to be a compelling explanation.

    We utilize the galaxy shape catalogue from the first-year data release of the Subaru Hyper Suprime-Cam (HSC) survey to study the dark matter content of galaxy groups in the Universe using weak lensing. We use galaxy groups from the Galaxy Mass and Assembly galaxy survey in approximately 100 sq. degrees of the sky that overlap with the HSC survey as lenses. We restrict our analysis to the 1587 groups with at least five members. We divide these groups into six bins each of group luminosity and group member velocity dispersion and measure the lensing signal with a signal-to-noise ratio of 55 and 51 for these two different selections, respectively. We use a Bayesian halo model framework to infer the halo mass distribution of our groups binned in the two different observable properties and constrain the power-law scaling relation and the scatter between mean halo masses and the two-group observable properties. We obtain a 5 per cent constraint on the amplitude of the scaling relation between halo mass and group luminosity with 〈M〉 = (0.81 ± 0.04) × 1014 h−1 M⊙ for Lgrp = 1011.5 h−2 L⊙, and a power-law index of α = 1.01 ± 0.07. We constrain the amplitude of the scaling relation between halo mass andmore »velocity dispersion to be 〈M〉 = (0.93 ± 0.05) × 1014 h−1 M⊙ for $\sigma = 500\, {\rm km\, s}^{-1}$ and a power-law index to be α = 1.52 ± 0.10. However, these scaling relations are sensitive to the exact cuts applied to the number of group members. Comparisons with similar scaling relations from the literature show that our results are consistent and have significantly reduced errors.

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