tangelo.problem_decomposition.dmet package
Submodules
tangelo.problem_decomposition.dmet.dmet_problem_decomposition module
Employ DMET as a problem decomposition technique.
- class tangelo.problem_decomposition.dmet.dmet_problem_decomposition.DMETProblemDecomposition(opt_dict)
Bases:
ProblemDecompositionDMET single-shot algorithm is used for problem decomposition technique. By default, CCSD is used as the electronic structure solver, and Meta-Lowdin is used for the localization scheme. Users can define other electronic structure solver such as FCI or VQE as an impurity solver. IAO scheme can be used instead of the Meta-Lowdin localization scheme, but it cannot be used for minimal basis set.
The underlying mean-field for the computation is automatically detected from the SecondQuantizedMolecule. RHF, ROHF and UHF mean-fields are supported.
- molecule
The molecular system.
- Type:
- electron_localization
A type of localization scheme. Default is Meta-Lowdin.
- Type:
- fragment_atoms
List of number of atoms in each fragment. Sum of this list should be the same as the number of atoms in the original system.
- Type:
list
- fragment_solvers
List of solvers for each fragment. If only a string is detected, this solver is used for all fragments.
- Type:
list or str
- fragment_frozen_orbitals
List of frozen orbitals. List of integers freezes the n first orbitals in the fragment. Nested list of integers freezes orbitals based on indices.
- Type:
list
- optimizer
A function defining the classical optimizer and its behavior.
- Type:
function handle
- initial_chemical_potential
Initial value for the chemical potential.
- Type:
float
- solvers_options
List of dictionaries for the solver options. If only a single dictionary is passed, the same options are applied for every solver. This will raise an error if different solvers are parsed.
- Type:
list or dict
- virtual_orbital_threshold
Occupation threshold for the virtual orbital space. Setting it to 0. is the equivalent of turning off the virtual orbital space truncation. Default=1e-13.
- Type:
float
- verbose
Flag for DMET verbosity.
- Type:
bool
- build()
Building the orbitals list for each fragment. It sets the values of self.orbitals, self.orb_list and self.orb_list2.
- energy_error_bars(n_shots, n_resamples, purify=False, rdm_measurements=None)
Perform bootstrapping of measured qubit terms in RDMs to obtain error bars for the calculated energy. Can also perform McWeeny purification of the RDMs between resampling and calculating the energy.
- Parameters:
n_shots (int) – The number of shots used to resample from qubit terms.
n_resamples (int) – The number of bootstrapping samples for the estimate of the energy and standard deviation.
purify (bool) – Use mc_weeny_rdm_purification technique on 2-RDMs. Will only apply to fragments with 2 electrons.
rdm_measurements (dict) –
A dictionary with keys being the DMET fragment number and corresponding values of a dictionary with keys of qubit terms in the rdm and corresponding values of a frequencies dictionary of the measurements. Example: { 0: {((0, “X”), (1, “Y”)): {“10”: 0.5, “01”: 0.5},
((1, “Z”), (1, “X”)): {“00”: 0.25, “11”: 0.25, “01”: 0.5}}
- 1: {((0, “Z”)): {“0000”: 1}
((0, “X”), (1, “Y”)): {“1111”: 0.5, “0101”: 0.5}}
}. If run _oneshot_loop with save_results=True is called: self.rdm_measurements will have the proper dictionary format with all values populated.
- Returns:
float – The bootstrapped DMET energy and standard deviation.
- get_resources()
Estimate the resources required by DMET. Only supports fragments solved with VQESolver. Resources for each fragments are outputed as a list.
- property quantum_fragments_data
This aims to return a dictionary with all necessary components to run a quantum experiment for a (or more) DMET fragment(s).
- simulate()
Perform DMET loop to optimize the chemical potential. It converges when the electron summation across all fragments is the same as the number of electron in the molecule.
- Returns:
float – The DMET energy (dmet_energy).
tangelo.problem_decomposition.dmet.fragment module
Module for data structure for DMET fragments.
- class tangelo.problem_decomposition.dmet.fragment.SecondQuantizedDMETFragment(molecule: <module 'pyscf.gto' from '/Users/valentinsenicourt/Desktop/virtualenvs/test_release_0.4.2/lib/python3.10/site-packages/pyscf/gto/__init__.py'>, mean_field: <module 'pyscf.scf' from '/Users/valentinsenicourt/Desktop/virtualenvs/test_release_0.4.2/lib/python3.10/site-packages/pyscf/scf/__init__.py'>, fock: ~numpy.array, fock_frag_copy: ~numpy.array, t_list: list, one_ele: ~numpy.array, two_ele: ~numpy.array, uhf: bool, frozen_orbitals: list)
Bases:
objectMimicking SecondQuantizedMolecule for DMET fragments. It has the minimal number of attributes and methods to be parsed by electronic solvers.
- basis: str
- property fermionic_hamiltonian
- fock: array
- fock_frag_copy: array
- property frozen_mos
This property returns MOs indexes for the frozen orbitals. It was written to take into account if one of the two possibilities (occ or virt) is None. In fact, list + None, None + list or None + None return an error. An empty list cannot be sent because PySCF mp2 returns “IndexError: list index out of range”.
- Returns:
list – MOs indexes frozen (occupied + virtual).
- frozen_orbitals: list
- mean_field: <module 'pyscf.scf' from '/Users/valentinsenicourt/Desktop/virtualenvs/test_release_0.4.2/lib/python3.10/site-packages/pyscf/scf/__init__.py'>
- molecule: <module 'pyscf.gto' from '/Users/valentinsenicourt/Desktop/virtualenvs/test_release_0.4.2/lib/python3.10/site-packages/pyscf/gto/__init__.py'>
- n_active_electrons: int
- n_active_mos: int
- n_active_sos: int
- one_ele: array
- q: int
- spin: int
- t_list: list
- to_pyscf(basis=None)
Method to output the PySCF molecule.
- Returns
pyscf.gto.Mole: PySCF molecule.
- two_ele: array
- uhf: bool