Acknowledgments

Building good software is hard. A special thanks to all of those who have contributed to the development so far.

If you use mystic to do research that leads to publication, we ask that you
acknowledge use of mystic by citing the following in your publication::

    M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
    "Building a framework for predictive science", Proceedings of
    the 10th Python in Science Conference, 2011;
    http://arxiv.org/pdf/1202.1056

    Michael McKerns, Patrick Hung, and Michael Aivazis,
    "mystic: a simple model-independent inversion framework", 2009- ;
    http://dev.danse.us/trac/mystic

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Authors

These folks built the code and documentation:

• Mike McKerns, California Institute of Technology
• Patrick Hung, California Institute of Technology

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Contributors

These nice folks shared ideas and opinions:

• Michael Aivazis, California Institute of Technology
• Paul Kienzle, National Institute of Standards and Technology
• Alta Fang, California Institute of Technology
• Tim Sullivan, California Institute of Technology

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Reviewers

These folks gave up precious time to provide feedback:

• Chris Farrow, Michigan State University {#64}
• Youngshin Kim, Iowa State University {#1, #55}
• Paul Kienzle, National Institute of Standards and Technology {#16, #28, #49}
• Chen Li, California Institute of Technology {#79, #80, #81, #82}
• Alta Fang, California Institute of Technology {#75}
• Lisa Mauger, California Institute of Technology {#102}

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Funding

This work is DANSE software developed and funded under NSF award DMR-0520547.