Matrix: GHS_psdef/torsion1

Description: Gould, Hu, & Scott: optimization problem (CUTEr)

GHS_psdef/torsion1 graph
(undirected graph drawing)


GHS_psdef/torsion1 dmperm of GHS_psdef/torsion1

  • Home page of the UF Sparse Matrix Collection
  • Matrix group: GHS_psdef
  • Click here for a description of the GHS_psdef group.
  • Click here for a list of all matrices
  • Click here for a list of all matrix groups
  • download as a MATLAB mat-file, file size: 328 KB. Use UFget(1315) or UFget('GHS_psdef/torsion1') in MATLAB.
  • download in Matrix Market format, file size: 371 KB.
  • download in Rutherford/Boeing format, file size: 263 KB.

    Matrix properties
    number of rows40,000
    number of columns40,000
    nonzeros197,608
    structural full rank?yes
    structural rank40,000
    # of blocks from dmperm5
    # strongly connected comp.5
    explicit zero entries0
    nonzero pattern symmetrysymmetric
    numeric value symmetrysymmetric
    typereal
    structuresymmetric
    Cholesky candidate?yes
    positive definite?yes

    authorR. Dembo, U. Tulowitzki
    editorP. Toint
    date1983
    kindduplicate optimization problem
    2D/3D problem?no

    Notes:

    duplicate of GHS_psdef/obstclae
    

    Ordering statistics:result
    nnz(chol(P*(A+A'+s*I)*P')) with AMD1,058,836
    Cholesky flop count1.2e+08
    nnz(L+U), no partial pivoting, with AMD2,077,672
    nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD2,073,834
    nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD3,783,582

    SVD-based statistics:
    norm(A)8.1995
    min(svd(A))0.2
    cond(A)40.9975
    rank(A)40,000
    sprank(A)-rank(A)0
    null space dimension0
    full numerical rank?yes

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

    GHS_psdef/torsion1 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.