Matrix: Newman/hep-th

Description: collaboration network, preprints in high-energy physics, www.arxiv.org

Newman/hep-th graph
(undirected graph drawing)


Newman/hep-th
scc of Newman/hep-th

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    Matrix properties
    number of rows8,361
    number of columns8,361
    nonzeros31,502
    # strongly connected comp.1,332
    explicit zero entries0
    nonzero pattern symmetrysymmetric
    numeric value symmetrysymmetric
    typereal
    structuresymmetric
    Cholesky candidate?no
    positive definite?no

    authorM. Newman
    editorM. Newman
    date2001
    kindundirected weighted graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 8361-by-24

    Notes:

    Network collection from M. Newman                                          
    http://www-personal.umich.edu/~mejn/netdata/                               
                                                                               
    The grapu hep-th contains the collaboration network of scientists          
    posting preprints on the high-energy theory archive at www.arxiv.org,      
    1995-1999, as compiled by M. Newman.  The network is weighted, with weights
    assigned as described in the original papers.  Please cite, as appropriate,
    one or more of:                                                            
                                                                               
      M. E. J. Newman, The structure of scientific collaboration networks,     
      Proc. Natl. Acad. Sci. USA 98, 404-409 (2001).                           
                                                                               
      M. E. J. Newman, Scientific collaboration networks: I. Network           
      construction and fundamental results, Phys. Rev. E 64, 016131 (2001).    
                                                                               
      M. E. J. Newman, Scientific collaboration networks: II. Shortest paths,  
      weighted networks, and centrality, Phys. Rev. E 64, 016132 (2001).       
    

    SVD-based statistics:
    norm(A)40.5189
    min(svd(A))1.72951e-50
    cond(A)2.3428e+51
    rank(A)7,101
    null space dimension1,260
    full numerical rank?no
    singular value gap1.55908e+06

    singular values (MAT file):click here
    SVD method used:s = svd (full (A)) ;
    status:ok

    Newman/hep-th svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.