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George N. Wong

Researcher at University of Illinois at Urbana–Champaign

Publications -  86
Citations -  18013

George N. Wong is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Supermassive black hole & Event Horizon Telescope. The author has an hindex of 23, co-authored 61 publications receiving 11433 citations. Previous affiliations of George N. Wong include Los Alamos National Laboratory & New York University.

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Decomposing the internal faraday rotation of black hole accretion flows

TL;DR: In this article, a set of general relativistic magneto-hydrodynamic (GRMHD) simulations appropriate for M87* and Sgr A were performed to better understand how accretion disc conditions are reflected in the observed rotation measure.
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Discriminating Accretion States via Rotational Symmetry in Simulated Polarimetric Images of M87

TL;DR: In this article, the authors proposed a modal image decomposition of the linear polarization field into basis functions with varying azimuthal dependence of the electric vector position angle, and applied this decomposition to images of ray traced general relativistic magnetohydrodynamics simulations of the Messier 87 accretion disk.
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Black Hole Glimmer Signatures of Mass, Spin, and Inclination

TL;DR: In this article, the authors provide a geometrically motivated treatment of the Kerr glimmer and evaluate it numerically for simple hotspot models to show that glimmer can be measured in a finite-resolution observation.
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Stochastic social behavior coupled to COVID-19 dynamics leads to waves, plateaus and an endemic state.

TL;DR: In this article, a stochastic dynamics of social activity is integrated into traditional epidemiological models to demonstrate the emergence of a new long timescale governing the epidemic, in broad agreement with empirical data.
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SYMBA: An end-to-end VLBI synthetic data generation pipeline: Simulating Event Horizon Telescope observations of M 87

Freek Roelofs, +245 more
TL;DR: The SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations that takes into account several realistic atmospheric, instrumental, and calibration effects is presented.