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A flexible Python platform for Regularized Maximum Likelihood imaging

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MPoL

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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 the following two references:

@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}
}

and

@ARTICLE{2023PASP..135f4503Z,
    author = {{Zawadzki}, Brianna and {Czekala}, Ian and {Loomis}, Ryan A. and {Quinn}, Tyler and {Grzybowski}, Hannah and {Frazier}, Robert C. and {Jennings}, Jeff and {Nizam}, Kadri M. and {Jian}, Yina},
        title = "{Regularized Maximum Likelihood Image Synthesis and Validation for ALMA Continuum Observations of Protoplanetary Disks}",
    journal = {\pasp},
    keywords = {Protoplanetary disks, Submillimeter astronomy, Radio interferometry, Deconvolution, Open source software, 1300, 1647, 1346, 1910, 1866, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
        year = 2023,
        month = jun,
    volume = {135},
    number = {1048},
        eid = {064503},
        pages = {064503},
        doi = {10.1088/1538-3873/acdf84},
archivePrefix = {arXiv},
    eprint = {2209.11813},
primaryClass = {astro-ph.EP},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2023PASP..135f4503Z},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Copyright Ian Czekala and contributors 2019-23

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