Roger Blandford

TL;DR: In this paper, the sky localization of the first observed compact binary merger is presented, where the authors describe the low-latency analysis of the LIGO data and present a sky localization map.

TL;DR: A full Monte Carlo simulation describing the interactions of cosmic rays with the lunar surface is developed, which is used to derive the cosmic-ray proton and helium spectra near Earth from the Moon gamma-ray data.

TL;DR: In this paper, the authors used convolutional neural networks and recurrent neural networks (RNNs) to estimate the parameters of strong gravitational lenses from interferometric observations, and found that the best results are obtained when the effects of the dirty beam are first removed from the images with deconvolution performed with an RNN-based structure before estimating the parameters.

TL;DR: In this paper, a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems is presented, which treats the source as a pixelated image and utilizes the Recurrent Inference Machine (RIM) to iteratively reconstruct the background source given a lens model.

TL;DR: In a celebrated article in PHYSICS TODAY entitled "Introducing the Black Hole" as discussed by the authors, Remo Ruffini and John Wheeler filed a dispatch from the campaign to understand gravity, and they now see that they wrote in the middle of a golden age, spanning the mid-1960s and the late 1970s, when remarkable discoveries in the theory of general relativity were made to confront equally stunning developments in observational astronomy.