J
John M. Blondin
Researcher at North Carolina State University
Publications - 183
Citations - 10344
John M. Blondin is an academic researcher from North Carolina State University. The author has contributed to research in topics: Supernova & Supernova remnant. The author has an hindex of 56, co-authored 177 publications receiving 9739 citations. Previous affiliations of John M. Blondin include University of Chicago & University of Virginia.
Papers
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Dynamics of Kepler's supernova remnant
TL;DR: In this article, the authors studied the dynamics of supernova ejecta interaction with the dense circumstellar medium (CSM) and identified the transmitted shock with the nonradiative, Balmerdominated shocks found recently in Kepler's SNR.
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X-Ray and Ultraviolet Line Emission from SNR 1987A
TL;DR: In this article, the authors simulate the hydrodynamics of this interaction and calculate the resulting X-ray and ultraviolet emission-line spectrum and light curves, which is consistent with the ROSAT observations if Fe is depleted on grains.
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Late-Time Evolution of Composite Supernova Remnants: Deep Chandra Observations and Hydrodynamical Modeling of a Crushed Pulsar Wind Nebula in SNR G327.1-1.1
Tea Temim,Tea Temim,Patrick Slane,Christopher Kolb,John M. Blondin,John P. Hughes,Niccolò Bucciantini +6 more
TL;DR: In this paper, a multaceted investigation of the interaction between a pulsar wind nebula (PWN) and its host SNR G327.1-1.1 is presented.
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Hoyle-lyttleton accretion in three dimensions
John M. Blondin,Eric Raymer +1 more
TL;DR: In this paper, the authors investigated the stability of the mass accretion of an ideal gas onto a compact object moving through a uniform medium at Mach 3 by using overset spherical grids.
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Neutron star masses from hydrodynamical effects in obscured sgHMXBs
TL;DR: In this paper, the authors used an hydrodynamical code to simulate the flow of the stellar wind around the neutron star, and a grid of simulations was used to study the dependency of the absorbing column density and of the X-ray light-curves on the model parameters.