Abstract

Abstract The Event Horizon Telescope (EHT) provides the unprecedented ability to directly resolve the structure and dynamics of black hole emission regions on scales smaller than their horizons. This has the potential to critically probe the mechanisms by which black holes accrete and launch outflows, and the structure of supermassive black hole spacetimes. However, accessing this information is a formidable analysis challenge for two reasons. First, the EHT natively produces a variety of data types that encode information about the image structure in nontrivial ways; these are subject to a variety of systematic effects associated with very long baseline interferometry and are supplemented by a wide variety of auxiliary data on the primary EHT targets from decades of other observations. Second, models of the emission regions and their interaction with the black hole are complex, highly uncertain, and computationally expensive to construct. As a result, the scientific utilization of EHT observations requires a flexible, extensible, and powerful analysis framework. We present such a framework, Themis, which defines a set of interfaces between models, data, and sampling algorithms that facilitates future development. We describe the design and currently existing components of Themis, how Themis has been validated thus far, and present additional analyses made possible by Themis that illustrate its capabilities. Importantly, we demonstrate that Themis is able to reproduce prior EHT analyses, extend these, and do so in a computationally efficient manner that can efficiently exploit modern high-performance computing facilities. Themis has already been used extensively in the scientific analysis and interpretation of the first EHT observations of M87.

Highlights

  • The Event Horizon Telescope (EHT), a global array of millimeter and submillimeter radio telescopes, has resolved the horizons of at least two black holes (Doeleman et al 2008, 2009, 2012; Doeleman 2010; Event Horizon Telescope Collaboration et al 2019a)

  • Due to the close proximity to their central black holes, both are empirically highly variable, providing statistical information about the dynamics within the millimeter-wavelength emission regions and creating opportunities to probe this dynamics directly at multiple wavelengths (Eckart et al 2008). Physical modeling of these sources provides the unique ability to synthesize all of these observations, which when combined with EHT data can provide a detailed description of the conditions and dynamics of material near black hole horizons

  • Modularity reduces the practical bars to significant contribution substantially: would-be developers need only understand the relevant elements of the interfaces between modules

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Summary

Introduction

The Event Horizon Telescope (EHT), a global array of millimeter and submillimeter radio telescopes, has resolved the horizons of at least two black holes (Doeleman et al 2008, 2009, 2012; Doeleman 2010; Event Horizon Telescope Collaboration et al 2019a). Due to the close proximity to their central black holes, both are empirically highly variable, providing statistical information about the dynamics within the millimeter-wavelength emission regions and creating opportunities to probe this dynamics directly at multiple wavelengths (Eckart et al 2008) Physical modeling of these sources provides the unique ability to synthesize all of these observations, which when combined with EHT data can provide a detailed description of the conditions and dynamics of material near black hole horizons.

Structure
Implementation
THEMIS Data Structures
D12 A15 A15 E19
Visibility Amplitudes
Closure Phases
Closure Amplitudes
Interferometric Polarization Fractions
Flux Measurements
THEMIS Models
Image-based Models
Phenomenological Geometric Models
Symmetric Gaussian
Asymmetric Gaussian
Crescent Model
The “Xsringauss” Model
Visual Binary
Interstellar Scattering Models
Default Diffractive Screen
Parameterized Diffractive Screen
Native Physical Models
SED-fitted RIAF
Extended RIAF
Orbiting Hot Spots
Shearing Hot Spots
External Physical Models
Priors
Likelihoods
Test Cases
Norm-marginalized Visibility Amplitudes
Shift-marginalized Closure Phases
Gain-marginalized Visibility Amplitude
Samplers
Grid Search
Bayesian Evidence
Validation Tests
Validation of the Samplers
Two-dimensional Gaussian Likelihood
Egg Box Test
Multivariate Cauchy Distribution
Self-tests with Simulated Data
Gaussian Model
Gaussian Model with Gain Errors
RIAF Model
Reproducing Previous Results
New Results
Extended RIAF Model
10. Code Performance
11. Summary
Visibility Amplitude Products
Polarization Fractions—Visibility Amplitude Quotients
Full Text
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