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Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes

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Topological Methods in Data Analysis and Visualization VI

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

The current generation of radio and millimeter telescopes, particularly the Atacama Large Millimeter Array (ALMA), offers enormous advances in observing capabilities. While these advances represent an unprecedented opportunity to facilitate scientific understanding, the increased complexity in the spatial and spectral structure of these ALMA data cubes lead to challenges in their interpretation. In this paper, we perform a feasibility study for applying topological data analysis and visualization techniques never before tested by the ALMA community. Using techniques based on contour trees, we seek to improve upon existing analysis and visualization workflows of ALMA data cubes, in terms of accuracy and speed in feature extraction. We review our development process in building effective analysis and visualization capabilities for the astrophysicists. We also summarize effective design practices by identifying domain-specific needs of simplicity, integrability, and reproducibility, in order to best target and service the large astrophysics community.

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Notes

  1. 1.

    Based upon sublevel set filtration, topological features typically appear as points in the upper left corner of the persistence diagram; points in the lower right corner correspond to features in superlevel set filtration and/or extended persistence [17], which are not the focus of this paper.

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Acknowledgements

This work was funded in part by a NRAO-NSF ALMA Development Grant titled Feature Extraction & Visualization of ALMA Data Cubes through Topological Data Analysis.

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Authors and Affiliations

  1. University of South Florida, Tampa, USA

    Paul Rosen

  2. University of Utah, Salt Lake City, USA

    Anil Seth, Chris R. Johnson & Bei Wang

  3. Brandeis University, Waltham, USA

    Elisabeth Mills

  4. National Radio Astronomy Observatory, Charlottesville, USA

    Adam Ginsburg & Jeff Kern

  5. Westminster College, Salt Lake City, USA

    Julia Kamenetzky

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  1. Paul Rosen
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  7. Chris R. Johnson
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Corresponding author

Correspondence to Paul Rosen .

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Editors and Affiliations

  1. Department of Science and Technology, Linköping University, Norrköping, Sweden

    Ingrid Hotz

  2. Department of Science and Technology, Linköping University, Norrköping, Sweden

    Talha Bin Masood

  3. Heidelberg University, IWR, Heidelberg, Germany

    Filip Sadlo

  4. CNRS, Department of Scientific Computing, Sorbonne Université, Paris, France

    Julien Tierny

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Rosen, P. et al. (2021). Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes. In: Hotz, I., Bin Masood, T., Sadlo, F., Tierny, J. (eds) Topological Methods in Data Analysis and Visualization VI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-030-83500-2_6

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