1 0 KSP Residual norm 7.280770540237e-01 2 1 KSP Residual norm 3.337812721729e-01 3 2 KSP Residual norm 8.313739299774e-02 4 3 KSP Residual norm 5.251831933856e-02 5 4 KSP Residual norm 1.542615245853e-05 6 5 KSP Residual norm 9.020985913821e-08 7 0 KSP Residual norm 9.231724776328e-03 8 1 KSP Residual norm 5.040032789111e-03 9 2 KSP Residual norm 1.891976920888e-03 10 3 KSP Residual norm 8.513155336232e-08 11 0 KSP Residual norm 1.452666856494e-05 12 1 KSP Residual norm 1.038508253259e-05 13 2 KSP Residual norm 5.428066742752e-06 14 3 KSP Residual norm 5.770967845820e-07 15 4 KSP Residual norm 3.353276423895e-12 16SNES Object: 1 MPI process 17 type: newtonls 18 maximum iterations=50, maximum function evaluations=10000 19 tolerances: relative=1e-05, absolute=1e-25, solution=1e-05 20 total number of linear solver iterations=12 21 total number of function evaluations=25 22 norm schedule ALWAYS 23 SNESLineSearch Object: 1 MPI process 24 type: bt 25 interpolation: cubic 26 alpha=1.000000e-04 27 maxlambda=1.000000e+00, minlambda=1.000000e-12 28 tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08 29 maximum iterations=40 30 KSP Object: 1 MPI process 31 type: gmres 32 restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement 33 happy breakdown tolerance=1e-30 34 maximum iterations=10000, initial guess is zero 35 tolerances: relative=1e-05, absolute=1e-25, divergence=10000. 36 left preconditioning 37 using PRECONDITIONED norm type for convergence test 38 PC Object: 1 MPI process 39 type: jacobi 40 type DIAGONAL 41 linear system matrix, which is also used to construct the preconditioner: 42 Mat Object: 1 MPI process 43 type: mffd 44 rows=5, cols=5 45 Matrix-free approximation: 46 err=0.000345267 (relative error in function evaluation) 47 Using wp compute h routine 48 Does not compute normU 49number of SNES iterations = 3 50 51