LINRES

References: Putrino2000

The linear response is used to calculate one of the following properties: nmr, epr, raman, … [Edit on GitHub]

Keywords

• ENERGY_GAP

• EPS

• EPS_FILTER

• EVERY_N_STEP

• MAX_ITER

• PRECONDITIONER

• RESTART

• RESTART_EVERY

• WFN_RESTART_FILE_NAME

Keyword descriptions

ENERGY_GAP: real = 2.00000000E-002

Usage: ENERGY_GAP 0.1

Energy gap estimate [a.u.] for preconditioning [Edit on GitHub]

EPS: real = 1.00000000E-010

Usage: EPS 1.e-6

target accuracy for the convergence of the conjugate gradient. [Edit on GitHub]

EPS_FILTER: real = 1.00000000E-015

Usage: EPS 1.e-8

Filter threshold for response density matrix. [Edit on GitHub]

EVERY_N_STEP: integer = 1

Usage: EVERY_N_STEP 50

Perform a linear response calculation every N-th step for MD run [Edit on GitHub]

MAX_ITER: integer = 100

Usage: MAX_ITER 200

Maximum number of conjugate gradient iteration to be performed for one optimization. [Edit on GitHub]

PRECONDITIONER: enum = FULL_SINGLE_INVERSE

Usage: PRECONDITIONER FULL_ALL

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.

• NONE skip preconditioning

Type of preconditioner to be used with all minimization schemes. They differ in effectiveness, cost of construction, cost of application. Properly preconditioned minimization can be orders of magnitude faster than doing nothing. [Edit on GitHub]

RESTART: logical = F

Lone keyword: T

Usage: RESTART

Restart the response calculation if the restart file exists [Edit on GitHub]

RESTART_EVERY: integer = 50

Usage: RESTART_EVERY 200

Restart the conjugate gradient after the specified number of iterations. [Edit on GitHub]

WFN_RESTART_FILE_NAME: string

Aliases: RESTART_FILE_NAME

Usage: WFN_RESTART_FILE_NAME

Root of the file names where to read the response functions from which to restart the calculation of the linear response [Edit on GitHub]