NbedDriver#

The NbedDriver controls all the main functionality of the package.

Module containg the NbedDriver Class.

class nbed.driver.NbedDriver(config: NbedConfig)[source]#

Bases: object

Function to return the embedding Qubit Hamiltonian.

Parameters:

config (NbedConfig) – A validated config model.

config#

Input configuration.

Type:

NbedConfig

localized_system#

A dataclass describing the localized C matrix and occupancy.

Type:

LocalizedSystem

mu#

Results for the $mu$-shift projector.

Type:

dict[str, Any]

huzinaga#

Results for the Huzinaga projector.

Type:

dict[str, Any]

two_e_cross#

two electron energy from cross terms (includes exchange correlation and Coulomb contribution) of subsystem DFT calculation

Type:

float

classical_energy#

environment correction energy to obtain total energy (for mu shift method)

Type:

float

embed(init_huzinaga_rhf_with_mu: bool = False, n_mo_overwrite: tuple[int | None, int | None] = (None, None)) → None[source]#

Run embedded scf calculation.

Parameters:

  • init_huzinaga_rhf_with_mu (bool) – Will run mu-shift projector even when input projector=’huzinaga’.

  • n_mo_overwrite (tuple[int, int]) – Enforces a specific number of MOs are included in the active region. Used for ACE-of-SPADE reaction path localization.

post_embed(embedded_scf: SCF, v_emb: ndarray[tuple[Any, ...], dtype[_ScalarT]], projector: ProjectorTypes) → dict[source]#

Projector-dependent components of the embedding procedure.

Parameters:

  • embedded_scf (scf.hf.SCF) – An embedded pyscf scf object.

  • v_emb (NDArray) – Embedding Potential

  • projector (ProjectorTypes) – Which projector the result should use.

Returns:

A dict of results.

Return type:

dict

nbed.driver.dft_in_dft(driver: NbedDriver, projection_method: ProjectorTypes) → dict[source]#

Return energy of DFT in DFT embedding.

Note run_mu_shift (bool) and run_huzinaga (bool) flags define which method to use (can be both) This is done when object is initialized.

Parameters:

  • driver (NbedDriver) – A driver object.

  • projection_method (callable) – Embedding method to use (mu or huzinaga).

Returns:

DFT-in-DFT embedding results.

Return type:

dict

nbed.driver.run_emb_ccsd(emb_pyscf_scf_rhf: SCF, frozen: list | None = None, convergence: float = 1e-06, max_ram_memory: int = 4000) → tuple[CCSDBase, float][source]#

Function run CCSD on embedded restricted Hartree Fock object.

Note emb_pyscf_scf_rhf is ROHF object for the active embedded subsystem (defined in localized basis) (see get_embedded_rhf method)

Parameters:

  • emb_pyscf_scf_rhf (scf.ROHF) – PySCF restricted Hartree Fock object of active embedded subsystem

  • frozen (List) – A path to an .xyz file describing molecular geometry.

  • convergence (float) – Convergence threshold.

  • max_ram_memory (int) – Maximum ram to use in solving.

Returns:

PySCF CCSD object e_ccsd_corr (float): electron correlation CCSD energy

Return type:

ccsd (cc.CCSD)

nbed.driver.run_emb_fci(emb_pyscf_scf_rhf: SCF, frozen: list | None = None, convergence: float | None = 1e-06, max_ram_memory: int | None = 4000) → SCF | FCISolver | CASBase[source]#

Function run FCI on embedded restricted Hartree Fock object.

Note emb_pyscf_scf_rhf is ROHF object for the active embedded subsystem (defined in localized basis) (see get_embedded_rhf method)

Parameters:

  • emb_pyscf_scf_rhf (scf.ROHF) – PySCF restricted Hartree Fock object of active embedded subsystem

  • frozen (List) – A path to an .xyz file describing moleclar geometry.

  • convergence (float) – convergence tolerance.

  • max_ram_memory (int) – Maximum memory allocation for FCI.

Returns:

PySCF FCI object

Return type:

fci_scf (fci.FCI)