  0 SNES Function norm 0.146402
  1 SNES Function norm 0.00119047
  2 SNES Function norm 7.73027e-07
SNES Object: 1 MPI process
  type: newtonls
  maximum iterations=50, maximum function evaluations=10000
  tolerances: relative=1e-05, absolute=1e-25, solution=1e-05
  total number of linear solver iterations=4
  total number of function evaluations=3
  norm schedule ALWAYS
  Jacobian is built using colored finite differences on a DMDA
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: fgmres
      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-25, divergence=10000.
    right preconditioning
    using UNPRECONDITIONED norm type for convergence test
  PC Object: 1 MPI process
    type: mg
      type is FULL, levels=2 cycles=v
        Not using Galerkin computed coarse grid matrices
    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-25, divergence=10000.
        left preconditioning
        using NONE norm type for convergence test
      PC Object: (mg_coarse_) 1 MPI process
        type: lu
          out-of-place factorization
          tolerance for zero pivot 1.19209e-05
          using diagonal shift on blocks to prevent zero pivot [INBLOCKS]
          matrix ordering: nd
          factor fill ratio given 5., needed 1.875
            Factored matrix follows:
              Mat Object: (mg_coarse_) 1 MPI process
                type: seqaij
                rows=16, cols=16
                package used to perform factorization: petsc
                total: nonzeros=120, allocated nonzeros=120
                  using I-node routines: found 12 nodes, limit used is 5
        linear system matrix = precond matrix:
        Mat Object: 1 MPI process
          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
    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 0.498841, max 1.09745
          eigenvalues estimated via gmres: min 0.385405, max 0.997681
          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-25, 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-25, divergence=10000.
        left preconditioning
        using NONE norm type for convergence test
      PC Object: (mg_levels_1_) 1 MPI process
        type: sor
          type = local_symmetric, iterations = 1, local iterations = 1, omega = 1.
        linear system matrix = precond matrix:
        Mat Object: 1 MPI process
          type: seqaij
          rows=49, cols=49
          total: nonzeros=217, allocated nonzeros=217
          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 = precond matrix:
    Mat Object: 1 MPI process
      type: seqaij
      rows=49, cols=49
      total: nonzeros=217, allocated nonzeros=217
      total number of mallocs used during MatSetValues calls=0
        not using I-node routines
Number of SNES iterations = 2
