A solver for inverting linear problems of the form A.x = b using the LSQR
method outlined in:
C. C. Paige and M. A. Saunders, Algorithm 583; LSQR: Sparse linear equations
and least-squares problems, TOMS 8(2), 195-209 (1982).
LSQR uses a functional representation of applying the A matrix, op(), in order
to optimally perform sparse operations. The algorithm also requires explicit
definition of the operator that is adjoint to op(), adj(). operator/adjoint
pairs can be debugged with an AdjointTester
b and x0 can be Fields or FieldArrays of any type structure, under the
following conditions:
1) op(x0) returns a type structure equivalent to b
2) adj(b) returns a type structure equivalent to x0
A solver for inverting linear problems of the form A.x = b using the LSQR method outlined in:
C. C. Paige and M. A. Saunders, Algorithm 583; LSQR: Sparse linear equations and least-squares problems, TOMS 8(2), 195-209 (1982).
LSQR uses a functional representation of applying the A matrix, op(), in order to optimally perform sparse operations. The algorithm also requires explicit definition of the operator that is adjoint to op(), adj(). operator/adjoint pairs can be debugged with an AdjointTester
b and x0 can be Fields or FieldArrays of any type structure, under the following conditions: 1) op(x0) returns a type structure equivalent to b 2) adj(b) returns a type structure equivalent to x0