Hybrid Very Long Baseline Interferometry Imaging and Modeling with Themis

TL;DR

This paper introduces a Bayesian image reconstruction method called Themis for very long baseline interferometry data, enabling detailed, statistically rigorous imaging and feature detection, exemplified by photon ring analysis in M87.

Contribution

Themis provides a full Bayesian framework for VLBI image reconstruction, allowing for uncertainty quantification and direct modeling of features like photon rings.

Findings

High-fidelity photon ring size measurements with 2-5% accuracy.

Robust detection of photon rings in simulated M87 data.

Enables precision tests of general relativity.

Abstract

Generating images from very long baseline interferometric observations poses a difficult, and generally not unique, inversion problem. This problem is simplified by the introduction of constraints, some generic (e.g., positivity of the intensity) and others motivated by physical considerations (e.g., smoothness, instrument resolution). It is further complicated by the need to simultaneously address instrumental systematic uncertainties and sparse coverage in the u-v plane. We report a new Bayesian image reconstruction technique in the parameter estimation framework Themis that has been developed for the Event Horizon Telescope. This has two key features: first, the full Bayesian treatment of the image reconstruction makes it possible to generate a full posterior for the images, permitting a rigorous and quantitative investigation into the statistical significance of image features. Second, it is possible to seamlessly incorporate directly modeled features simultaneously with image reconstruction. We demonstrate this second capability by incorporating a narrow, slashed ring in reconstructions of simulated M87 data in an attempt to detect and characterize the photon ring. We show that it is possible to obtain high-fidelity photon ring sizes, enabling mass measurements with accuracies of 2%-5% that are essentially insensitive to astrophysical uncertainties, and creating opportunities for precision tests of general relativity.