RESPONSE_SOLVER

Description: Specify how atomic blocks should be clustered in the used matrices, in order to improve flop rate, and possibly speedup the matrix multiply. Note that the atomic s_preconditioner can not be used. Furthermore, since screening is on matrix blocks, slightly more accurate results can be expected with molecular.

Valid values:

ATOMIC Using atomic blocks
MOLECULAR Using molecular blocks.

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MAX_ITER

Type: integer
Default: 50
Usage: MAX_ITER 200

Description: Maximum number of conjugate gradient iteration to be performed for one optimization.

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MAX_ITER_LANCZOS

Type: integer
Default: 128
Usage: MAX_ITER_LANCZOS 128

Description: Maximum number of lanczos iterations.

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METHOD

Type: enum
Default: AO_ORTHO
Usage: METHOD SOLVER

Description: Algorithm used to solve response equation. Both solver are conjugate gradient based, but use either a vector (MO-coefficient) or density matrix formalism in the orthonormal AO-basis to obtain response density

Valid values:

MO_SOLVER Solver based on MO (vector) formalism
AO_ORTHO Solver based on density matrix formalism

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PRECONDITIONER

Type: enum
Default: MULTI_LEVEL
Usage: PRECONDITIONER FULL_ALL

Description: Type of preconditioner to be used with MO conjugate gradient solver. They differ in effectiveness, cost of construction, cost of application. Properly preconditioned minimization can be orders of magnitude faster than doing nothing. Only multi-level conjugate gradient preconditioner (MULTI_LEVEL) available for AO response solver (AO_ORTHO).

Valid values:

FULL_ALL Most effective state selective preconditioner based on diagonalization, requires the ENERGY_GAP parameter to be an underestimate of the HOMO-LUMO gap. This preconditioner is recommended for almost all systems, except very large systems where make_preconditioner would dominate the total computational cost.
FULL_SINGLE_INVERSE Based on H-eS cholesky inversion, similar to FULL_SINGLE in preconditioning efficiency but cheaper to construct, might be somewhat less robust. Recommended for large systems.
FULL_SINGLE Based on H-eS diagonalisation, not as good as FULL_ALL, but somewhat cheaper to apply.
FULL_KINETIC Cholesky inversion of S and T, fast construction, robust, and relatively good, use for very large systems.
FULL_S_INVERSE Cholesky inversion of S, not as good as FULL_KINETIC, yet equally expensive.
MULTI_LEVEL Based on same CG as AO-solver itself, but uses cheaper linear transformation
NONE skip preconditioning