Publications
Deep learning inference with the Event Horizon Telescope-I. Calibration improvements and a comprehensive synthetic data library
Abstract
Context. In a series of publications, we describe a comprehensive comparison of Event Horizon Telescope (EHT) data with theoretical models of the observed Sagittarius A* (Sgr A*) and Messier 87* (M87*) horizon-scale sources.Aims. In this article, we report on improvements made to our observational data reduction pipeline and present the generation of observables derived from the EHT models. We make use of ray-traced general relativistic magnetohydrodynamic simulations that are based on different black hole spacetime metrics and accretion physics parameters. These broad classes of models provide a good representation of the primary targets observed by the EHT.Methods. We describe how we combined multiple frequency bands and polarization channels of the observational data to improve our fringe-finding sensitivity and stabilization of atmospheric phase fluctuations. To generate realistic synthetic …
- Date
- May 1, 2025
- Authors
- M Janssen, C-k Chan, J Davelaar, I Natarajan, H Olivares, B Ripperda, J Röder, M Rynge, M Wielgus
- Journal
- Astronomy & Astrophysics
- Volume
- 698
- Pages
- A60
- Publisher
- EDP Sciences