3.9.19. horton.meanfield.scf_oda – Optimal Damping SCF algorithm

class horton.meanfield.scf_oda.ODASCFSolver(threshold=1e-08, maxiter=128, skip_energy=False, debug=False)

Bases: object

Optional arguments:

maxiter
The maximum number of iterations. When set to None, the SCF loop will go one until convergence is reached.
threshold
The convergence threshold for the wavefunction
skip_energy
When set to True, the final energy is not computed.
debug
When set to True, for each mixing step, a plot is made to double check the cubic interpolation.
__call__(*args, **kwargs)

Find a self-consistent set of density matrices.

Arguments:

ham
An effective Hamiltonian.
lf
The linalg factory to be used.
overlap
The overlap operator.
occ_model
Model for the orbital occupations.
dm1, dm2, …
The initial density matrices. The number of dms must match ham.ndm.
__init__(threshold=1e-08, maxiter=128, skip_energy=False, debug=False)

Optional arguments:

maxiter
The maximum number of iterations. When set to None, the SCF loop will go one until convergence is reached.
threshold
The convergence threshold for the wavefunction
skip_energy
When set to True, the final energy is not computed.
debug
When set to True, for each mixing step, a plot is made to double check the cubic interpolation.
error(ham, lf, overlap, *dms)

See horton.meanfield.convergence.convergence_error_commutator().

kind = ‘dm’
horton.meanfield.scf_oda.check_cubic(ham, dm0s, dm1s, e0, e1, g0, g1, do_plot=True)

Method to test the correctness of the cubic interpolation

Arguments:

ham
An effective Hamiltonian.
dm0s
A list of density matrices for the initial state.
dm1s
A list of density matrices for the final state.
e0
The energy of the initial state.
e1
The energy of the final state.
g0
The derivative of the energy for the initial state.
g1
The derivative of the energy for the initial state.

This method interpolates between two state with a parameter lambda going from 0 to 1. The arguments g0 and g1 are derivatives toward this parameter lambda.

Optional arguments:

do_plot
When set to True, a plot is made to visualize the interpolation. Otherwise, an AssertionError is made if the error on the interpolation. is too large.

This function is mainly useful as a tool to double check the implementation of Fock matrices.