@inproceedings{Frey2011-03Loose-17714,
  year={2011},
  doi={10.1109/PACIFICVIS.2011.5742372},
  title={Loose Capacity-Constrained Representatives for the Qualitative Visual Analysis in Molecular Dynamics},
  isbn={978-1-61284-935-5},
  publisher={IEEE},
  booktitle={2011 IEEE Pacific Visualization Symposium},
  pages={51--58},
  author={Frey, Steffen and Schlömer, Thomas and Grottel, Sebastian and Dachsbacher, Carsten and Deussen, Oliver and Ertl, Thomas}
}

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    <dcterms:bibliographicCitation>First publ. in: Proceedings of the 2011 IEEE Pacific Visualization Symposium, 2011 : PacificVIS '11 ; Hongkong, China, 1 - 4 March 2011 / ed. by Guiseppe Di Battista; Jean-Daniel Fekete, ... - Piscataway, NJ : IEEE Service Center, 2011. - pp. 51-58. - ISBN 978-1-61284-935-5</dcterms:bibliographicCitation>
    <dc:creator>Dachsbacher, Carsten</dc:creator>
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    <dc:creator>Grottel, Sebastian</dc:creator>
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    <dcterms:abstract xml:lang="eng">Molecular dynamics is a widely used simulation technique to investigate material properties and structural changes under external forces. The availability of more powerful clusters and algorithms continues to increase the spatial and temporal extents of the simulation domain. This poses a particular challenge for the visualization of the underlying processes which might consist of millions of particles and thousands of time steps. Some application domains have developed special visual metaphors to only represent the relevant information of such data sets but these approaches typically require detailed domain knowledge that might not always be available or applicable. We propose a general technique that replaces the huge amount of simulated particles by a smaller set of representatives that are used for the visualization instead. The representatives capture the characteristics of the underlying particle density and exhibit coherency over time. We introduce loose capacity-constrained Voronoi diagrams for the generation of these representatives by means of a GPU-friendly, parallel algorithm. This way we achieve visualizations that reflect the particle distribution and geometric structure of the original data very faithfully. We evaluate our approach using real-world data sets from the application domains of material science, thermodynamics and dynamical systems theory.</dcterms:abstract>
    <dc:contributor>Schlömer, Thomas</dc:contributor>
    <dcterms:issued>2011-03</dcterms:issued>
    <dc:creator>Deussen, Oliver</dc:creator>
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    <dc:contributor>Frey, Steffen</dc:contributor>
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