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Millimeter Light Curves of Sagittarius A Observed during the 2017 Event Horizon Telescope Campaign
Journal article   Peer reviewed

Millimeter Light Curves of Sagittarius A Observed during the 2017 Event Horizon Telescope Campaign

Maciek Wielgus, Nicola Marchili, Iván Martí-Vidal, Garrett K. Keating, Venkatessh Ramakrishnan, Paul Tiede, Ed Fomalont, Sara Issaoun, Joey Neilsen, Michael A. Nowak, …
The Astrophysical Journal Letters, Vol.930(2), p.L19
05/12/2022
DOI: https://doi.org/10.3847/2041-8213/ac6428
Handle:
https://hdl.handle.net/10192/66536

Abstract

Black holes Galactic Center Radio interferometry
The Event Horizon Telescope (EHT) observed the compact radio source, Sagittarius A* (Sgr A*), in the Galactic Center on 2017 April 5–11 in the 1.3 mm wavelength band. At the same time, interferometric array data from the Atacama Large Millimeter/submillimeter Array and the Submillimeter Array were collected, providing Sgr A* light curves simultaneous with the EHT observations. These data sets, complementing the EHT very long baseline interferometry, are characterized by a cadence and signal-to-noise ratio previously unattainable for Sgr A* at millimeter wavelengths, and they allow for the investigation of source variability on timescales as short as a minute. While most of the light curves correspond to a low variability state of Sgr A*, the April 11 observations follow an X-ray flare and exhibit strongly enhanced variability. All of the light curves are consistent with a red-noise process, with a power spectral density (PSD) slope measured to be between −2 and −3 on timescales between 1 minute and several hours. Our results indicate a steepening of the PSD slope for timescales shorter than 0.3 hr. The spectral energy distribution is flat at 220 GHz, and there are no time lags between the 213 and 229 GHz frequency bands, suggesting low optical depth for the event horizon scale source. We characterize Sgr A*’s variability, highlighting the different behavior observed just after the X-ray flare, and use Gaussian process modeling to extract a decorrelation timescale and a PSD slope. We also investigate the systematic calibration uncertainties by analyzing data from independent data reduction pipelines.

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