For UmfPack and Newton:
If I change the test tolerance from 0.01 to 0.001 and keep the time steps at 100, it can't converge.
If I keep the test tolerance at 0.01 and change the time steps to 1000, it converges and the result doesn't change.
If I change the test tolerance to 0.001 and change the time steps to 1000, it also can't converge.
For SparseSYM and Krylov-Newton:
If I change the test tolerance from 0.01 to 0.001 and keep the time steps at 100, it converges and the result doesn't change.
If I keep the test tolerance at 0.01 and change the time steps to 1000, it converges and the result doesn't change.
If I change the test tolerance to 0.001 and change the time steps to 1000, it has a complex root.
I think the tolerance and time steps are enough. But the difference still has.
Is there any other way to make the two results more consistent?