1 0 KSP Residual norm 7.280029743643e-01 2 1 KSP Residual norm 3.337699703998e-01 3 2 KSP Residual norm 8.311740393601e-02 4 3 KSP Residual norm 5.246933530538e-02 5 4 KSP Residual norm 4.966507189176e-10 6 0 KSP Residual norm 9.243456971952e-03 7 1 KSP Residual norm 5.047060548246e-03 8 2 KSP Residual norm 1.832186129208e-03 9 3 KSP Residual norm 3.923484692566e-12 10 0 KSP Residual norm 1.415224180979e-05 11 1 KSP Residual norm 8.046849055481e-06 12 2 KSP Residual norm 3.150100389056e-06 13 3 KSP Residual norm 1.353722415600e-14 14SNES Object: 1 MPI process 15 type: newtonls 16 maximum iterations=50, maximum function evaluations=10000 17 tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 18 total number of linear solver iterations=10 19 total number of function evaluations=23 20 norm schedule ALWAYS 21 SNESLineSearch Object: 1 MPI process 22 type: bt 23 interpolation: cubic 24 alpha=1.000000e-04 25 maxlambda=1.000000e+00, minlambda=1.000000e-12 26 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 27 maximum iterations=40 28 KSP Object: 1 MPI process 29 type: gmres 30 restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement 31 happy breakdown tolerance=1e-30 32 maximum iterations=10000, initial guess is zero 33 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 34 left preconditioning 35 using PRECONDITIONED norm type for convergence test 36 PC Object: 1 MPI process 37 type: jacobi 38 type DIAGONAL 39 linear system matrix, which is also used to construct the preconditioner: 40 Mat Object: 1 MPI process 41 type: mffd 42 rows=5, cols=5 43 Matrix-free approximation: 44 err=1.49012e-08 (relative error in function evaluation) 45 Using wp compute h routine 46 Does not compute normU 47number of SNES iterations = 3 48 49