0 SNES Function norm 1.371870931195e-01 
    0 KSP Residual norm 7.514924505889e-02 
    1 KSP Residual norm 3.030336958028e-02 
    2 KSP Residual norm 1.888992084147e-02 
    3 KSP Residual norm 1.177522877288e-02 
    4 KSP Residual norm 7.340211418424e-03 
    5 KSP Residual norm 4.575597188502e-03 
    6 KSP Residual norm 2.852246132704e-03 
    7 KSP Residual norm 1.777977314517e-03 
    8 KSP Residual norm 1.108320665138e-03 
    9 KSP Residual norm 6.908832226053e-04 
   10 KSP Residual norm 4.306692478914e-04 
   11 KSP Residual norm 2.684621583079e-04 
   12 KSP Residual norm 1.673486806782e-04 
   13 KSP Residual norm 1.043185419549e-04 
   14 KSP Residual norm 6.502804893050e-05 
   15 KSP Residual norm 4.053591114740e-05 
   16 KSP Residual norm 2.526848213304e-05 
   17 KSP Residual norm 1.575137134546e-05 
   18 KSP Residual norm 9.818781276847e-06 
   19 KSP Residual norm 6.120639508030e-06 
   20 KSP Residual norm 3.815364344206e-06 
   21 KSP Residual norm 2.378347076276e-06 
   22 KSP Residual norm 1.482567405097e-06 
   23 KSP Residual norm 9.241738233457e-07 
   24 KSP Residual norm 5.760933720795e-07 
   25 KSP Residual norm 3.591137997548e-07 
   26 KSP Residual norm 2.238573249394e-07 
   27 KSP Residual norm 1.395437935165e-07 
   28 KSP Residual norm 8.698607614054e-08 
   29 KSP Residual norm 5.422367594582e-08 
   30 KSP Residual norm 3.380089278699e-08 
   31 KSP Residual norm 2.107013832621e-08 
   32 KSP Residual norm 1.313429008095e-08 
   33 KSP Residual norm 8.187396406615e-09 
   34 KSP Residual norm 5.103698763462e-09 
   35 KSP Residual norm 3.181443751652e-09 
   36 KSP Residual norm 1.983186065549e-09 
   37 KSP Residual norm 1.236239704442e-09 
   38 KSP Residual norm 7.706228707023e-10 
   39 KSP Residual norm 4.803757858298e-10 
   40 KSP Residual norm 2.994472569552e-10 
   41 KSP Residual norm 1.866635534245e-10 
   42 KSP Residual norm 1.163586711608e-10 
   43 KSP Residual norm 7.253338715593e-11 
  1 SNES Function norm 2.289561804036e-10 
Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
SNES Object: 1 MPI processes
  type: newtonls
  maximum iterations=50, maximum function evaluations=10000
  tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
  total number of linear solver iterations=43
  total number of function evaluations=2
  norm schedule ALWAYS
  SNESLineSearch Object:   1 MPI processes
    type: bt
      interpolation: cubic
      alpha=1.000000e-04
    maxstep=1.000000e+08, minlambda=1.000000e-12
    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
    maximum iterations=40
  KSP Object:   1 MPI processes
    type: richardson
      Richardson: damping factor=1
    maximum iterations=10000, initial guess is zero
    tolerances:  relative=1e-09, absolute=1e-50, divergence=10000
    left preconditioning
    using PRECONDITIONED norm type for convergence test
  PC Object:   1 MPI processes
    type: asm
      Additive Schwarz: total subdomain blocks = 2, amount of overlap = 0
      Additive Schwarz: restriction/interpolation type - RESTRICT
      Local solve is same for all blocks, in the following KSP and PC objects:
      KSP Object:      (sub_)       1 MPI processes
        type: preonly
        maximum iterations=10000, initial guess is zero
        tolerances:  relative=1e-05, absolute=1e-50, divergence=10000
        left preconditioning
        using NONE norm type for convergence test
      PC Object:      (sub_)       1 MPI processes
        type: lu
          LU: out-of-place factorization
          tolerance for zero pivot 2.22045e-14
          matrix ordering: nd
          factor fill ratio given 5, needed 1.875
            Factored matrix follows:
              Mat Object:               1 MPI processes
                type: seqaij
                rows=16, cols=16
                package used to perform factorization: petsc
                total: nonzeros=120, allocated nonzeros=120
                total number of mallocs used during MatSetValues calls =0
                  using I-node routines: found 12 nodes, limit used is 5
        linear system matrix = precond matrix:
        Mat Object:         1 MPI processes
          type: seqaij
          rows=16, cols=16
          total: nonzeros=64, allocated nonzeros=64
          total number of mallocs used during MatSetValues calls =0
            not using I-node routines
    linear system matrix = precond matrix:
    Mat Object:     1 MPI processes
      type: seqaij
      rows=32, cols=32
      total: nonzeros=136, allocated nonzeros=136
      total number of mallocs used during MatSetValues calls =0
        not using I-node routines
N: 32 error l2 6.01813e-12 inf 8.12005e-11