Introduction

Comrade is a Bayesian differentiable modular modeling framework for use with very long baseline interferometry. The goal is to allow the user to easily combine and modify a set of primitive models to construct complicated source structures. The benefit of this approach is that it is straightforward to construct different source models out of these primitives. Namely, an end-user does not have to create a separate source "model" every time they change the model specification. Additionally, most models currently implemented are differentiable with at Enzyme. This allows for gradient accelerated optimization and sampling (e.g., HMC) to be used with little effort by the end user.

Warning

As of 0.11 Comrade will only support AD with Enzyme. We have removed support for Zygote and ForwardDiff due to performance issues.

Tutorials

Our tutorial section currently has a large number of examples. Including:

• Geometric Modeling of EHT Data

• Imaging a Black Hole using only Closure Quantities

• Stokes I Simultaneous Image and Instrument Modeling

• Hierarchicial Interferometric Bayesian Imaging (HIBI)

• Modeling the Power Spectrum of an AGN with Markov Random Field Expansion

• Polarized Image and Instrumental Modeling

Note that these tutorials should be treated as starting points for your own modeling efforts! Comrade is highly flexible and so you should be able to combine different aspects of these tutorials to create your own models. We are currently working on a high-level imaging code that uses Comrade as a backend, but in the mean time these tutorials should help you get on your own VLBI imaging projects.

Contributing

This repository has recently moved to ColPrac. If you would like to contribute please feel free to open a issue or pull-request.

Requirements

The minimum Julia version we require is 1.10.