Daily Paper Digest

1, TITLE: MUSE unravels the ionisation and origin of metal enriched absorbers in the gas halo of a z = 2.92 radio galaxy
http://arxiv.org/abs/1904.05114
AUTHORS: S. Kolwa ; J. Vernet ; C. De Breuck ; M. Villar-Martin ; A. Humphrey ; F. Arrigoni-Battaia ; B. Gullberg ; T. Falkendal ; G. Drouart ; M. Lehnert ; D. Wylezalek ; A. Man
COMMENTS: 21 pages, 20 figures, accepted for publication in A&A
HIGHLIGHT: To do this, we obtain photoionisation grid models in \pkg{cloudy} which show that AGN radiation is capable of ionising the gas and producing the observed column densities in a gas of metallicity of Z/Z$_\odot \simeq$ 0.01 with a nitrogen abundance a factor of 10 greater than that of hydrogen.

2, TITLE: The stellar halo of the Milky Way traced by blue horizontal-branch stars in the Subaru Hyper Suprime-Cam Survey
http://arxiv.org/abs/1904.04966
AUTHORS: Tetsuya Fukushima ; Masashi Chiba ; Mikito Tanaka ; Kohei Hayashi ; Daisuke Homma ; Sakurako Okamoto ; Yutaka Komiyama ; Masayuki Tanaka ; Nobuo Arimoto ; Tadafumi Matsuno
COMMENTS: 15 pages, 10 figures, 3 tables, accepted for publication in PASJ
HIGHLIGHT: We report on the global structure of the Milky Way (MW) stellar halo up to its outer boundary based on the analysis of blue-horizontal branch stars (BHBs).

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53, TITLE: Evidence for the third stellar population in the Milky Way’s disk
http://arxiv.org/abs/1904.04881
AUTHORS: Daniela Carollo ; Masashi Chiba ; Miho Ishigaki ; Ken Freeman ; Chiara Battistini ; Tim Beers ; Patricia Tissera ; Francesca Primas ; Y. S. Lee
COMMENTS: 23 pages, 5 figures, submitted to Nature on April 9, 2019
HIGHLIGHT: In this article, we analyze the kinematics, spatial distribution, and chemistry of a large number of stars in the Solar Neighborhood, where all of the main Galactic components are well-represented.

1, TITLE: Approximation in $L^p(μ)$ with deep ReLU neural networks
http://arxiv.org/abs/1904.04789
AUTHORS: Felix Voigtlaender ; Philipp Petersen
COMMENTS: Accepted for presentation at SampTA 2019
HIGHLIGHT: After reviewing these findings, we show that the results concerning networks with fixed depth— which up to now only consider approximation in $L^p(\lambda)$ for the Lebesgue measure $\lambda$— can be generalized to approximation in $L^p(\mu)$, for any finite Borel measure $\mu$.

2, TITLE: On the approximation of the solution of partial differential equations by artificial neural networks trained by a multilevel Levenberg-Marquardt method
http://arxiv.org/abs/1904.04685
AUTHORS: Henri Calandra ; Serge Gratton ; Elisa Riccietti ; Xavier Vasseur
HIGHLIGHT: This paper is concerned with the approximation of the solution of partial differential equations by means of artificial neural networks.

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107, TITLE: On the Adaptivity of Stochastic Gradient-Based Optimization
http://arxiv.org/abs/1904.04480
AUTHORS: Lihua Lei ; Michael I. Jordan
COMMENTS: 41 pages
HIGHLIGHT: We present the stochastically controlled stochastic gradient (SCSG) method for composite convex finite-sum optimization problems and show that SCSG is adaptive to both strong convexity and target accuracy.