ift-resolve 0.15

Radio imaging with information field theory

resolve

Documentation: http://ift.pages.mpcdf.de/resolve

Resolve aims to be a general radio aperature synthesis algorithm. It is based on Bayesian principles and formulated in the language of information field theory. Its features include single-frequency imaging with either only a diffuse or a diffuse+point-like sky model as prior, single-channel antenna-based calibration with a regularization in temporal domain and w-stacking.

Resolve is in beta stage: You are more than welcome to test it and help to make it applicable. In the likely case that you encounter bugs, please contact me via email.

Requirements

For running the installation script:

• Python version 3.10 or later.
• C++17 capable compiler, e.g. g++ 7 or later.
• pybind11>=2.6
• setuptools

Automatically installed by installation script:

• ducc0
• nifty8
• numpy

Optional dependencies:

• astropy
• pytest, pytest-cov (for testing)
• mpi4py
• python-casacore (for reading measurement sets)
• h5py
• matplotlib
• dask-ms[xarray, zarr] (for reading pfb-clean xds files)
• jax-finufft (for using the finufft in jax-resolve)
• jaxlinop (for using ducc gridder in jax-resolve)

Installation

For a blueprint how to install resolve, you may look at the Dockerfile.

For installing resolve on a Linux machine, the following steps are necessary. First install the necessary dependencies, for example via:

pip3 install --upgrade pybind11 setuptools

Finally, clone the resolve repository and install resolve on your system:

git clone --recursive https://gitlab.mpcdf.mpg.de/ift/resolve
cd resolve
pip install --user .

Related publications

• Bayesian radio interferometric imaging with direction-dependent calibration (doi, arXiv).
• Variable structures in M87* from space, time and frequency resolved interferometry (doi, arXiv).
• Comparison of classical and Bayesian imaging in radio interferometry (doi, arXiv).
• Unified radio interferometric calibration and imaging with joint uncertainty quantification (doi, arXiv).
• Radio imaging with information field theory (doi, arXiv).