MPoL 0.2.0

Regularized Maximum Likelihood Imaging for Radio Astronomy

MPoL

A Million Points of Light are needed to synthesize image cubes from interferometers.

MPoL is a flexible Python package designed for Regularized Maximum Likelihood imaging. We focus on supporting spectral line and continuum observations from interferometers like the Atacama Large Millimeter/Submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA). There is potential to extend the package to work on other Fourier reconstruction problems like sparse aperture masking and kernel phase interferometry.

Documentation and installation instructions: https://mpol-dev.github.io/MPoL/

Citation

If you use this package or derivatives of it, please cite

@software{mpol,
author       = {Ian Czekala and
                Jeff Jennings and   
                Brianna Zawadzki and
                Ryan Loomis and
                Kadri Nizam and 
                Megan Delamer and 
                Kaylee de Soto and
                Robert Frazier and
                Hannah Grzybowski and
                Mary Ogborn and                    
                Tyler Quinn},
title        = {MPoL-dev/MPoL: v0.2.0 Release},
month        = nov,
year         = 2023,
publisher    = {Zenodo},
version      = {v0.2.0},
doi          = {10.5281/zenodo.3594081},
url          = {https://doi.org/10.5281/zenodo.3594081}
}

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Copyright Ian Czekala and contributors 2019-23