petsc-3.4.2 2013-07-02

# KSPSTCG

Code to run conjugate gradient method subject to a constraint on the solution norm. This is used in Trust Region methods for nonlinear equations, SNESNEWTONTR

### Options Database Keys

-ksp_stcg_radius <r> -Trust Region Radius

Notes: This is rarely used directly

Use preconditioned conjugate gradient to compute an approximate minimizer of the quadratic function

q(s) = g^T * s + 0.5 * s^T * H * s

subject to the trust region constraint

|| s || <= delta,

where

delta is the trust region radius, g is the gradient vector, H is the Hessian approximation, and M is the positive definite preconditioner matrix.

KSPConvergedReason may be

     KSP_CONVERGED_CG_NEG_CURVE if convergence is reached along a negative curvature direction,

     KSP_CONVERGED_CG_CONSTRAINED if convergence is reached along a constrained step,

     other KSP converged/diverged reasons

### Notes

The preconditioner supplied should be symmetric and positive definite.

### See Also

KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP, KSPSTCGSetRadius(), KSPSTCGGetNormD(), KSPSTCGGetObjFcn()

Level:developer
Location:src/ksp/ksp/impls/cg/stcg/stcg.c
Index of all KSP routines
Table of Contents for all manual pages
Index of all manual pages