85 citations · 148 across the 4 of their papers we have counts for
9 papers
Jet Launching from Binary Neutron Star Mergers: Incorporating Neutrino Transport and Magnetic Fields
Lunan Sun, Milton Ruiz, Stuart L. Shapiro +1
We perform general relativistic, magnetohydrodynamic (GRMHD) simulations of merging binary neutron stars incorporating neutrino transport and magnetic fields. Our new radiative tra…
Semantic Communications With AI Tasks
Yang Yang, Caili Guo, Fangfang Liu +4
A radical paradigm shift of wireless networks from ``connected things'' to ``connected intelligence'' undergoes, which coincides with the Shanno and Weaver's envisions: Communicati…
Enabling real-time multi-messenger astrophysics discoveries with deep learning
E. A. Huerta, Gabrielle Allen, Igor Andreoni +57
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that…
Great Impostors: Extremely Compact, Merging Binary Neutron Stars in the Mass Gap Posing as Binary Black Holes
Antonios Tsokaros, Milton Ruiz, Stuart L. Shapiro +2
Can one distinguish a binary black hole undergoing a merger from a binary neutron star if the individual compact companions have masses that fall inside the so-called mass gap of $…
Dynamically stable ergostars exist: General relativistic models and simulations
Antonios Tsokaros, Milton Ruiz, Lunan Sun +2
We construct the first dynamically stable ergostars (equilibrium neutron stars that contain an ergoregion) for a compressible, causal equation of state. We demonstrate their stabil…
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
Gabrielle Allen, Igor Andreoni, Etienne Bachelet +45
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrop…