  0 SNES Function norm 1.32334
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 1.3212
        1 KSP Residual norm 0.299275
        2 KSP Residual norm 0.043515
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0408746
        1 KSP Residual norm 0.00715117
        2 KSP Residual norm 0.00200882
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 1.34445
      1 KSP Residual norm 0.289515
      2 KSP Residual norm 0.0546877
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0380401
        1 KSP Residual norm 0.00836889
        2 KSP Residual norm 0.00486415
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00592336
        1 KSP Residual norm 0.00127555
        2 KSP Residual norm 0.000253948
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0502885
      1 KSP Residual norm 0.00692009
      2 KSP Residual norm 0.00304318
    0 KSP Residual norm 5.82901
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.22657
        1 KSP Residual norm 0.0513167
        2 KSP Residual norm 0.00746422
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00701122
        1 KSP Residual norm 0.0012265
        2 KSP Residual norm 0.000344611
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.230327
      1 KSP Residual norm 0.0496328
      2 KSP Residual norm 0.00935522
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00652181
        1 KSP Residual norm 0.00143468
        2 KSP Residual norm 0.000834414
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00101614
        1 KSP Residual norm 0.000218815
        2 KSP Residual norm 4.35646e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0085981
      1 KSP Residual norm 0.00118416
      2 KSP Residual norm 0.000520109
    1 KSP Residual norm 0.00134258
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.524964
        1 KSP Residual norm 0.103069
        2 KSP Residual norm 0.0217471
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0207058
        1 KSP Residual norm 0.00314867
        2 KSP Residual norm 0.00113072
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 1.8397
      1 KSP Residual norm 0.217655
      2 KSP Residual norm 0.117319
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0498378
        1 KSP Residual norm 0.0109218
        2 KSP Residual norm 0.00247682
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00270397
        1 KSP Residual norm 0.000566248
        2 KSP Residual norm 0.000118256
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.11456
      1 KSP Residual norm 0.012674
      2 KSP Residual norm 0.00749368
    2 KSP Residual norm 2.52518e-06
  1 SNES Function norm 0.0426538
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0793943
        1 KSP Residual norm 0.017905
        2 KSP Residual norm 0.00276128
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000710871
        1 KSP Residual norm 0.000148814
        2 KSP Residual norm 2.61706e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0422535
      1 KSP Residual norm 0.0104256
      2 KSP Residual norm 0.000711525
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00102555
        1 KSP Residual norm 0.000703008
        2 KSP Residual norm 0.000457301
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000432665
        1 KSP Residual norm 9.69389e-05
        2 KSP Residual norm 1.52326e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.000226183
      1 KSP Residual norm 4.76493e-05
      2 KSP Residual norm 1.0857e-05
    0 KSP Residual norm 0.780398
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.101721
        1 KSP Residual norm 0.0229401
        2 KSP Residual norm 0.00353783
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000910901
        1 KSP Residual norm 0.000190679
        2 KSP Residual norm 3.35381e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0541359
      1 KSP Residual norm 0.0133576
      2 KSP Residual norm 0.000911499
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00131394
        1 KSP Residual norm 0.000900707
        2 KSP Residual norm 0.000585904
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000554339
        1 KSP Residual norm 0.0001242
        2 KSP Residual norm 1.95163e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.00028944
      1 KSP Residual norm 6.10183e-05
      2 KSP Residual norm 1.38846e-05
    1 KSP Residual norm 1.23638e-05
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.396136
        1 KSP Residual norm 0.0823979
        2 KSP Residual norm 0.0138349
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0143355
        1 KSP Residual norm 0.0024337
        2 KSP Residual norm 0.000681786
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.624996
      1 KSP Residual norm 0.0849283
      2 KSP Residual norm 0.0370791
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0121259
        1 KSP Residual norm 0.00254363
        2 KSP Residual norm 0.000483193
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000359102
        1 KSP Residual norm 6.39233e-05
        2 KSP Residual norm 1.7077e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0361135
      1 KSP Residual norm 0.00417517
      2 KSP Residual norm 0.002293
    2 KSP Residual norm 1.0644e-08
  2 SNES Function norm 0.000676784
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00128086
        1 KSP Residual norm 0.000282989
        2 KSP Residual norm 4.71378e-05
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 1.75471e-05
        1 KSP Residual norm 3.47885e-06
        2 KSP Residual norm 7.25532e-07
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.000688903
      1 KSP Residual norm 0.000169178
      2 KSP Residual norm 1.32901e-05
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 1.991e-05
        1 KSP Residual norm 1.14298e-05
        2 KSP Residual norm 7.56087e-06
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 7.30858e-06
        1 KSP Residual norm 1.64187e-06
        2 KSP Residual norm 2.5929e-07
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 4.03112e-06
      1 KSP Residual norm 9.40672e-07
      2 KSP Residual norm 1.73312e-07
    0 KSP Residual norm 0.0123756
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.103481
        1 KSP Residual norm 0.0228627
        2 KSP Residual norm 0.00380829
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00141765
        1 KSP Residual norm 0.000281056
        2 KSP Residual norm 5.86174e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0556575
      1 KSP Residual norm 0.0136682
      2 KSP Residual norm 0.00107369
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00160855
        1 KSP Residual norm 0.000923429
        2 KSP Residual norm 0.000610855
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.000590472
        1 KSP Residual norm 0.000132649
        2 KSP Residual norm 2.09484e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.000325537
      1 KSP Residual norm 7.59825e-05
      2 KSP Residual norm 1.39924e-05
    1 KSP Residual norm 2.71146e-07
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.384332
        1 KSP Residual norm 0.0842136
        2 KSP Residual norm 0.0117152
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.0119953
        1 KSP Residual norm 0.00218223
        2 KSP Residual norm 0.000525707
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.307391
      1 KSP Residual norm 0.0524142
      2 KSP Residual norm 0.0157681
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00668548
        1 KSP Residual norm 0.00129655
        2 KSP Residual norm 0.000287599
        Residual norms for mg_levels_1_ solve.
        0 KSP Residual norm 0.00021681
        1 KSP Residual norm 4.00612e-05
        2 KSP Residual norm 1.00219e-05
      Residual norms for mg_levels_2_ solve.
      0 KSP Residual norm 0.0154905
      1 KSP Residual norm 0.00200478
      2 KSP Residual norm 0.0009371
    2 KSP Residual norm 1.134e-10
  3 SNES Function norm 1.8565e-07
SNES Object: 1 MPI process
  type: newtonls
  maximum iterations=50, maximum function evaluations=10000
  tolerances: relative=1e-05, absolute=1e-50, solution=1e-08
  total number of linear solver iterations=6
  total number of function evaluations=4
  norm schedule ALWAYS
  Jacobian is built using a DMDA local Jacobian
  SNESLineSearch Object: 1 MPI process
    type: bt
      interpolation: cubic
      alpha=1.000000e-04
    maxlambda=1.000000e+00, minlambda=1.000000e-12
    tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
    maximum iterations=40
  KSP Object: 1 MPI process
    type: gmres
      restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement
      happy breakdown tolerance=1e-30
    maximum iterations=10000, initial guess is zero
    tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
    left preconditioning
    using PRECONDITIONED norm type for convergence test
  PC Object: 1 MPI process
    type: mg
      type is FULL, levels=3 cycles=v
        Using Galerkin computed coarse grid matrices for pmat
    Coarse grid solver -- level 0 -------------------------------
      KSP Object: (mg_coarse_) 1 MPI process
        type: preonly
        maximum iterations=10000, initial guess is zero
        tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
        left preconditioning
        not checking for convergence
      PC Object: (mg_coarse_) 1 MPI process
        type: lu
          out-of-place factorization
          tolerance for zero pivot 2.22045e-14
          using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
          matrix ordering: nd
          factor fill ratio given 5., needed 1.59172
            Factored matrix:
              Mat Object: (mg_coarse_) 1 MPI process
                type: seqaij
                rows=25, cols=25
                package used to perform factorization: petsc
                total: nonzeros=269, allocated nonzeros=269
                  using I-node routines: found 17 nodes, limit used is 5
        linear system matrix, which is also used to construct the preconditioner:
        Mat Object: 1 MPI process
          type: seqaij
          rows=25, cols=25
          total: nonzeros=169, allocated nonzeros=169
          total number of mallocs used during MatSetValues calls=0
            not using I-node routines
    Down solver (pre-smoother) on level 1 -------------------------------
      KSP Object: (mg_levels_1_) 1 MPI process
        type: chebyshev
          Chebyshev polynomial of first kind
          eigenvalue targets used: min 0.499526, max 1.09896
          eigenvalues estimated via gmres: min 0.229855, max 0.999052
          eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1]
          KSP Object: (mg_levels_1_esteig_) 1 MPI process
            type: gmres
              restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement
              happy breakdown tolerance=1e-30
            maximum iterations=10, initial guess is zero
            tolerances: relative=1e-12, absolute=1e-50, divergence=10000.
            left preconditioning
            using PRECONDITIONED norm type for convergence test
          estimating eigenvalues using a noisy random number generated right-hand side
        maximum iterations=2, nonzero initial guess
        tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
        left preconditioning
        not checking for convergence
      PC Object: (mg_levels_1_) 1 MPI process
        type: sor
          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
        linear system matrix, which is also used to construct the preconditioner:
        Mat Object: 1 MPI process
          type: seqaij
          rows=81, cols=81
          total: nonzeros=625, allocated nonzeros=625
          total number of mallocs used during MatSetValues calls=0
            not using I-node routines
    Up solver (post-smoother) same as down solver (pre-smoother)
    Down solver (pre-smoother) on level 2 -------------------------------
      KSP Object: (mg_levels_2_) 1 MPI process
        type: chebyshev
          Chebyshev polynomial of first kind
          eigenvalue targets used: min 0.499175, max 1.09819
          eigenvalues estimated via gmres: min 0.050574, max 0.998351
          eigenvalues estimated using gmres with transform: [0. 0.5; 0. 1.1]
          KSP Object: (mg_levels_2_esteig_) 1 MPI process
            type: gmres
              restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement
              happy breakdown tolerance=1e-30
            maximum iterations=10, initial guess is zero
            tolerances: relative=1e-12, absolute=1e-50, divergence=10000.
            left preconditioning
            using PRECONDITIONED norm type for convergence test
          estimating eigenvalues using a noisy random number generated right-hand side
        maximum iterations=2, nonzero initial guess
        tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
        left preconditioning
        not checking for convergence
      PC Object: (mg_levels_2_) 1 MPI process
        type: sor
          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
        linear system matrix, which is also used to construct the preconditioner:
        Mat Object: 1 MPI process
          type: seqaij
          rows=289, cols=289
          total: nonzeros=1377, allocated nonzeros=1377
          total number of mallocs used during MatSetValues calls=0
            not using I-node routines
    Up solver (post-smoother) same as down solver (pre-smoother)
    linear system matrix, which is also used to construct the preconditioner:
    Mat Object: 1 MPI process
      type: seqaij
      rows=289, cols=289
      total: nonzeros=1377, allocated nonzeros=1377
      total number of mallocs used during MatSetValues calls=0
        not using I-node routines
