327 citations · 4.5k across the 98 of their papers we have counts for
7 papers · 1 filter
Spatially Resolved Water Emission from Gravitationally Lensed Dusty Star Forming Galaxies at z 3
Sreevani Jarugula, Joaquin D. Vieira, Justin S. Spilker +17
Water (), one of the most ubiquitous molecules in the universe, has bright millimeter-wave emission lines easily observed at high-redshift with the current generation o…
Imaging the Molecular Interstellar Medium in a Gravitationally Lensed Star-forming Galaxy at z=5.7
Yordanka Apostolovski, Manuel Aravena, Timo Anguita +17
Aims: We present and study spatially resolved imaging obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) of multiple CO(65, 87 and 98) and tw…
Testing the Nature of Dark Matter with Extremely Large Telescopes
Joshua D. Simon, Simon Birrer, Keith Bechtol +12
For nearly 40 years, dark matter has been widely assumed to be cold and collisionless. Cold dark matter models make fundamental predictions for the behavior of dark matter on small…
Dark Matter Science in the Era of LSST
Keith Bechtol, Alex Drlica-Wagner, Kevork N. Abazajian +177
Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental…
Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope
Alex Drlica-Wagner, Yao-Yuan Mao, Susmita Adhikari +97
Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST…
Source structure and molecular gas properties from high-resolution CO imaging of SPT-selected dusty star-forming galaxies
Chenxing Dong, Justin S. Spilker, Anthony H. Gonzalez +17
We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of high-J CO lines (, 7, 8) and associated dust continuum towards five strongly lensed,…
Data-Driven Reconstruction of Gravitationally Lensed Galaxies using Recurrent Inference Machines
Warren R. Morningstar, Laurence Perreault Levasseur, Yashar D. Hezaveh +6
We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated…