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The GD-1 stream is one of the longest and coldest stellar streams discovered to date, and one of the best objects for constraining the dark matter properties of the Milky Way. Using data from {it Gaia} DR2 we study the proper motions, distance, morphology and density of the stream to uncover small scale perturbations. The proper motion cleaned data shows a clear distance gradient across the stream, ranging from 7 to 12 kpc. However, unlike earlier studies that found a continuous gradient, we uncover a distance minimum at $varphi_{1}approx$-50 deg, after which the distance increases again. We can reliably trace the stream between -85$<varphi_{1}<$15 deg, showing an even further extent to GD-1 beyond the earlier extension of citet{Price-Whelan18a}. We constrain the stream track and density using a Boolean matched filter approach and find three large under densities and find significant residuals in the stream track lining up with these gaps. In particular, a gap is visible at $varphi_{1}$=-3 deg, surrounded by a clear sinusoidal wiggle. We argue that this wiggle is due to a perturbation since it has the wrong orientation to come from a progenitor. We compute a total initial stellar mass of the stream segment of 1.58$pm$0.07$times$10$^{4}$ M$_{odot}$. With the extended view of the spur in this work, we argue that the spur may be unrelated to the adjacent gap in the stream. Finally, we show that an interaction with the Sagittarius dwarf can create features similar to the spur.
Filaments in Herschel molecular cloud images are found to exhibit a characteristic width. This finding is in tension with spatial power spectra of the data, which show no indication of this characteristic scale. We demonstrate that this discrepancy i
The radio-loud active galactic nucleus in M 87 hosts a powerful jet fueled by a super-massive black hole in its center. A bright feature 80 pc away from the M 87 core has been reported to show superluminal motions, and possibly to be connected with a
Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. We take a closer look at this phenomenon and first show that real
We study how the behavior of deep policy gradient algorithms reflects the conceptual framework motivating their development. To this end, we propose a fine-grained analysis of state-of-the-art methods based on key elements of this framework: gradient
We investigate the bursty star formation histories (SFHs) of dwarf galaxies using the distribution of log($L_{Halpha}/L_{UV}$) of 185 local galaxies. We expand on the work of Weisz et al. 2012 to consider a wider range of SFHs and stellar metalliciti