0 TS dt 8.33333e-06 time 0.
1 TS dt 8.33333e-05 time 8.33333e-06
2 TS dt 0.000833333 time 9.16667e-05
3 TS dt 0.00833333 time 0.000925
4 TS dt 0.0132237 time 0.00925833
5 TS dt 0.0132566 time 0.022482
6 TS dt 0.0132919 time 0.0357387
7 TS dt 0.0133226 time 0.0490305
8 TS dt 0.0133482 time 0.0623531
9 TS dt 0.0133897 time 0.0757014
10 TS dt 0.0134319 time 0.0890911
11 TS dt 0.0134682 time 0.102523
12 TS dt 0.0134977 time 0.115991
13 TS dt 0.0135238 time 0.129489
14 TS dt 0.00489702 time 0.133796
15 TS dt 0.0100499 time 0.138693
16 TS dt 0.0135701 time 0.148743
17 TS dt 0.0136074 time 0.162313
18 TS dt 0.00444936 time 0.165984
19 TS dt 0.00858076 time 0.170433
20 TS dt 0.013541 time 0.179014
21 TS dt 0.0136961 time 0.192555
22 TS dt 0.00532605 time 0.197268
23 TS dt 0.010851 time 0.202594
24 TS dt 0.0137439 time 0.213445
25 TS dt 0.0137662 time 0.227189
26 TS dt 0.00367174 time 0.22978
27 TS dt 0.00589472 time 0.233452
28 TS dt 0.0114309 time 0.239346
29 TS dt 0.0138401 time 0.250777
30 TS dt 0.0137489 time 0.264617
31 TS dt 0.00291312 time 0.266458
32 TS dt 0.00408174 time 0.269371
33 TS dt 0.00693935 time 0.273453
34 TS dt 0.0130397 time 0.280392
35 TS dt 0.0139752 time 0.293432
36 TS dt 0.0129219 time 0.307407
TS Object: 1 MPI process
  type: arkimex
    ARK IMEX 3
    Stiff abscissa       ct =  0.000000  0.871733  0.600000  1.000000 
  Fully implicit: no
  Stiffly accurate: yes
  Explicit first stage: yes
  FSAL property: yes
    Nonstiff abscissa     c =  0.000000  0.871733  0.600000  1.000000 
  initial time step=8.33333e-06
  maximum steps=1000
  maximum time=0.3
  maximum number of step rejections=10
  maximum number of SNES failures allowed=1
  using relative error tolerance of 0.0001,   using absolute error tolerance of 0.0001
  TSAdapt Object: 1 MPI process
    type: basic
    safety factor 0.9
    extra safety factor after step rejection 0.5
    clip fastest increase 10.
    clip fastest decrease 0.1
    maximum allowed timestep 1e+20
    minimum allowed timestep 1e-20
    maximum solution absolute value to be ignored -1.
  SNES Object: 1 MPI process
    type: newtonls
    maximum iterations=50, maximum function evaluations=10000
    tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
    norm schedule ALWAYS
    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 MULTIPLICATIVE, levels=3 cycles=v
          Cycles per PCApply=1
          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-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 1.63333
              Factored matrix:
                Mat Object: (mg_coarse_) 1 MPI process
                  type: seqaij
                  rows=60, cols=60
                  package used to perform factorization: petsc
                  total: nonzeros=294, allocated nonzeros=294
                    not using I-node routines
          linear system matrix, which is also used to construct the preconditioner:
          Mat Object: 1 MPI process
            type: seqaij
            rows=60, cols=60
            total: nonzeros=180, allocated nonzeros=180
              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 0.1, max 1.1
            eigenvalues estimated via gmres: min 1., max 1.
            eigenvalues estimated using gmres with transform: [0. 0.1; 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=3, 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=120, cols=120
            total: nonzeros=360, allocated nonzeros=360
              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 0.1, max 1.1
            eigenvalues estimated via gmres: min 1., max 1.
            eigenvalues estimated using gmres with transform: [0. 0.1; 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=3, 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=240, cols=240
            total: nonzeros=720, allocated nonzeros=720
              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=240, cols=240
        total: nonzeros=720, allocated nonzeros=720
          not using I-node routines
