1 Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 5 2SNES Object: 1 MPI process 3 type: newtontr 4 Trust region parameters: 5 eta1=0.001, eta2=0.25, eta3=0.75 6 t1=0.25, t2=2. 7 delta_min=1e-12, delta_0=0.2, delta_max=1e+10 8 kmdc=0. 9 fallback=NEWTON 10 qn=DIFFERENT 11 norm=INFINITY 12 maximum iterations=50, maximum function evaluations=10000 13 tolerances: relative=1e-08, absolute=1e-50, solution=0. 14 total number of linear solver iterations=5 15 total number of function evaluations=6 16 norm schedule ALWAYS 17 KSP Object: 1 MPI process 18 type: gmres 19 restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement 20 happy breakdown tolerance=1e-30 21 maximum iterations=10000, initial guess is zero 22 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 23 left preconditioning 24 using PRECONDITIONED norm type for convergence test 25 PC Object: 1 MPI process 26 type: mat 27 PCApply() == MatSolve() 28 linear system matrix, followed by the matrix used to construct the preconditioner: 29 Mat Object: (snes_tr_qn_) 1 MPI process 30 type: lmvmdfp 31 rows=16, cols=16 32 Max. storage: 5 33 Used storage: 4 34 Number of updates: 4 35 Number of rejects: 0 36 Number of resets: 0 37 J0: 38 Mat Object: (snes_tr_qn_mat_lmvm_J0_) 1 MPI process 39 type: diagonal 40 rows=16, cols=16 41 Vec Object: 1 MPI process 42 type: seq 43 Rescale type: diagonal 44 Rescale history: 1 45 Rescale params: alpha=1., beta=0.5, rho=1. 46 Rescale convex factor: theta=0.125 47 Mat Object: (snes_tr_qn_pre_) 1 MPI process 48 type: lmvmbfgs 49 rows=16, cols=16 50 Max. storage: 5 51 Used storage: 4 52 Number of updates: 4 53 Number of rejects: 0 54 Number of resets: 0 55 J0: 56 Mat Object: (snes_tr_qn_pre_mat_lmvm_J0_) 1 MPI process 57 type: diagonal 58 rows=16, cols=16 59 Vec Object: 1 MPI process 60 type: seq 61 Rescale type: diagonal 62 Rescale history: 1 63 Rescale params: alpha=1., beta=0.5, rho=1. 64 Rescale convex factor: theta=0.125 65Number of SNES iterations = 5 66