Variability in GRMHD Simulations of Sgr A*: Implications for EHT Closure Phase Observations
Marrone, Daniel P.
AffiliationUniv Arizona, Steward Observ
Univ Arizona, Dept Astron
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PublisherIOP PUBLISHING LTD
CitationVariability in GRMHD Simulations of Sgr A*: Implications for EHT Closure Phase Observations 2017, 844 (1):35 The Astrophysical Journal
JournalThe Astrophysical Journal
Rights© 2017. The American Astronomical Society. All rights reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractClosure phases along different baseline triangles carry a large amount of information regarding the structures of the images of black holes in interferometric observations with the Event Horizon Telescope. We use long time span, high cadence, GRMHD+radiative transfer models of Sgr A* to investigate the expected variability of closure phases in such observations. We find that, in general, closure phases along small baseline triangles show little variability, except in the cases when one of the triangle vertices crosses one of the small regions of low visibility amplitude. The closure phase variability increases with the size of the baseline triangle, as larger baselines probe the small-scale structures of the images, which are highly variable. On average, the funnel-dominated MAD models show less closure phase variability than the disk-dominated SANE models, even in the large baseline triangles, because the images from the latter are more sensitive to the turbulence in the accretion flow. Our results suggest that image reconstruction techniques need to explicitly take into account the closure phase variability, especially if the quality and quantity of data allow for a detailed characterization of the nature of variability. This also implies that, if image reconstruction techniques that rely on the assumption of a static image are utilized, regions of the u-v space that show a high level of variability will need to be identified and excised.
VersionFinal published version
SponsorsNSF GRFP [DGE 1144085]; NASA/NSF TCAN [NNX14AB48G]; NSF [TM6-17006X, AST 1312034, AST-1207752, 1228509]; John Simon Guggenheim Memorial Foundation; Radcliffe Institute for Advanced Study at Harvard University