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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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Verification of radiative transfer schemes for the EHT

Ralphp Eatough, +248 more
TL;DR: In this paper, the authors compare the performance of EHT radiative transfer codes with the results of the Event Horizon Telescope (EHT) Collaboration to model the supermassive black hole in the giant elliptical galaxy M87.
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THEMIS: A parameter estimation framework for the Event Horizon Telescope

Avery E. Broderick, +235 more
TL;DR: Themis is demonstrated to be able to reproduce prior EHT analyses, extend these, and do so in a computationally efficient manner that can efficiently exploit modern high-performance computing facilities.
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Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope

Maciek Wielgus, +262 more
TL;DR: In this paper, the authors analyzed M87* data collected with prototype EHT arrays in 2009, 2011, 2012, and 2013 and found that the M87 * morphology in 2009-2017 was consistent with a persistent asymmetric ring of approximately 40 µas diameter.
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Polarimetric Properties of Event Horizon Telescope Targets from ALMA

Ciriaco Goddi, +306 more
TL;DR: In this paper, the authors present a list of authors who have contributed to the work of this paper and discuss their own work in the field of literature, including the authors of this paper.
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Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity.

TL;DR: In this paper, the authors developed a general approach to encompass both short and long-term variations in individual social activity, and demonstrate how to incorporate them phenomenologically into a wide class of epidemiological models through reparameterization.