Critical Point Detection

Critical Point Detection is a computational method in vector field analysis that identifies locations where the velocity vector vanishes and characterizes the local flow topology by analyzing the eigenstructure of the Jacobian matrix.

151

Publications

6.6K

Citations

797

Authors

214

Institutions

Publications per year

2017–2026

33

Authors

797

  1. AR
    Alyn Rockwood

    Arizona State University, United States

    4 publications · 139 citations

    4

    h-index

  2. GS
    Gerik Scheuermann

    Leipzig University, Germany

    4 publications · 244 citations

    4

    h-index

  3. AP
    Alex Pang

    University of California, Santa Cruz, United States

    3 publications · 300 citations

    3

    h-index

  4. DK
    David Kao

    University of Colorado Denver, United States

    3 publications · 300 citations

    3

    h-index

  5. HH
    Hans Hagen

    University of Kaiserslautern, Germany

    3 publications · 153 citations

    3

    h-index

1–5 of 797

Venues

  1. IEEE Visualization

    Conference · 4 publications · 196 citations

    4

    h-index

  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 4 publications · 135 citations

    4

    h-index

  3. The Journal of Chemical Physics

    3 publications · 54 citations

    3

    h-index

  4. Physical Review Letters

    PRL · 3 publications · 354 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 150 citations

    3

    h-index

1–5