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Abstract The Event Horizon Telescope (EHT) has released analyses of reconstructed images of horizon-scale millimeter emission near the supermassive black hole at the center of the M87 galaxy. Parts of the analyses made use of a large library of synthetic black hole images and spectra, which were produced using numerical general relativistic magnetohydrodynamics fluid simulations and polarized ray tracing. In this article, we describe thePATOKApipeline, which was used to generate the Illinois contribution to the EHT simulation library. We begin by describing the relevant accretion systems and radiative processes. We then describe the details of the three numerical codes we use,iharm,ipole, andigrmonty, paying particular attention to differences between the current generation of the codes and the originally published versions. Finally, we provide a brief overview of simulated data as produced byPATOKAand conclude with a discussion of limitations and future directions.
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This content will become publicly available on September 18, 2026
Validation and Calibration of Semianalytical Models for the Event Horizon Telescope Observations of Sagittarius A*
Abstract The Event Horizon Telescope (EHT) enables the exploration of black hole accretion flows at event-horizon scales. Fitting ray-traced physical models to EHT observations requires the generation of synthetic images, a task that is computationally demanding. This study leveragesALINet, a generative machine learning model, to efficiently produce radiatively inefficient accretion flow (RIAF) images as a function of the specified physical parameters.ALINethas previously been shown to be able to interpolate black hole images and their associated physical parameters after training on a computationally tractable set of library images. We utilize this model to estimate the uncertainty introduced by a number of anticipated unmodeled physical effects, including interstellar scattering and intrinsic source variability. We then use this to calibrate physical parameter estimates and their associated uncertainties from RIAF model fits to mock EHT data via a library of general relativistic magnetohydrodynamics models.
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- Award ID(s):
- 2034306
- PAR ID:
- 10660247
- Publisher / Repository:
- IOP
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 991
- Issue:
- 1
- ISSN:
- 0004-637X
- Page Range / eLocation ID:
- 105
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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