chemqulacs.vqe.vqeci module

chemqulacs.vqe.vqeci module#

class chemqulacs.vqe.vqeci.AWSBackend(arn: str, qubit_mapping: Optional[Mapping[int, int]] = None, **run_kwargs)[source]#

Bases: Backend

Backend class for AWS Braket

Parameters:

  • arn (str) – ARN which specifies the device to use

  • qubit_mapping (Optional[Mapping[[int, int]]]) – Qubit mappings between the qubit indices used in the code and the qubit indices used in the backend.

class chemqulacs.vqe.vqeci.Ansatz(value)[source]#

Bases: Enum

An enum representing an ansatz for VQE

AllSinglesDoubles = 3#
GateFabric = 6#
HardwareEfficient = 1#
KUpCCGSD = 8#
ParticleConservingU1 = 4#
ParticleConservingU2 = 5#
SymmetryPreserving = 2#
UCCSD = 7#
class chemqulacs.vqe.vqeci.Backend[source]#

Bases: object

Base class represents backend

class chemqulacs.vqe.vqeci.ITensorBackend[source]#

Bases: Backend

Backend class for ITensor

class chemqulacs.vqe.vqeci.QiskitBackend(backend_name: str, hub: str = 'ibm-q', group: str = 'open', project: str = 'main', qubit_mapping: Optional[Mapping[int, int]] = None, **run_kwargs)[source]#

Bases: Backend

Backend class for Qiskit

Parameters:

  • backend_name (str) – Name of the qiskit backend

  • hub (str) –

  • group (str) –

  • project (str) –

  • qubit_mapping (Optional[Mapping[[int, int]]]) – Qubit mappings from the qubit indices used in the code to the backend qubit indices

class chemqulacs.vqe.vqeci.QulacsBackend[source]#

Bases: Backend

Backend class for Qulacs

class chemqulacs.vqe.vqeci.VQECI(mol=None, fermion_qubit_mapping=<quri_parts.openfermion.transforms.OpenFermionJordanWignerFactory object>, optimizer=<quri_parts.algo.optimizer.adam.Adam object>, backend: ~chemqulacs.vqe.vqeci.Backend = <chemqulacs.vqe.vqeci.QulacsBackend object>, shots_per_iter: int = 10000, initial_states=None, ansatz: ~chemqulacs.vqe.vqeci.Ansatz = Ansatz.ParticleConservingU1, layers: int = 2, k: int = 1, trotter_number: int = 1, excitation_number: int = 0, weight_policy: str = 'exponential', include_pi: bool = False, use_singles: bool = True, delta_sz: int = 0, singlet_excitation: bool = False, is_init_random: bool = False, seed: int = 0)[source]#

Bases: object

Parameters:

  • mol – SCF or Mole to define the problem size.

  • fermion_qubit_mapping (quri_parts.openfermion.transforms.OpenFermionQubitMapping) – Mapping from FermionOperator or InteractionOperator to Operator

  • optimizer –

  • backend (Backend) –

  • shots_per_iter (int) –

  • initial_states (optional) – Initial states for VQE

  • ansatz – ansatz used for VQE

  • layers (int) – Layers of gate operations. Used for HardwareEfficient, SymmetryPreserving, ParticleConservingU1, ParticleConservingU2, and GateFabric.

  • k (int) – Number of repetitions of excitation gates. Used for KUpCCGSD.

  • trotter_number (int) – Number of trotter decomposition. Used for UCCSD and kUpCCGSD.

  • include_pi (bool) – If True, the optional constant gate is inserted. Used for GateFabric.

  • use_singles – (bool): If True, single-excitation gates are applied. Used for UCCSD.

  • delta_sz (int) – Changes of spin in the excitation. Used for KUpCCGSD.

  • singlet_excitation (bool) – If True, the ansatz will be spin symmetric. Used for UCCSD and KUpCCGSD.

  • is_init_random (bool) – If False, initial parameters are initialized to 0s, else, initialized randomly.

  • seeed (int) – Random seed.

Returns:

None

kernel(h1, h2, norb, nelec, ecore=0, **kwargs)[source]#
make_dm2(_, norb, nelec, link_index=None, **kwargs)[source]#
make_rdm1(_, norb, nelec, link_index=None, sz=0, **kwargs)[source]#
make_rdm12(_, norb, nelec, link_index=None, sz=0, **kwargs)[source]#
spin_square(civec, norb, nelec)[source]#
chemqulacs.vqe.vqeci.generate_initial_states(n_orbitals, n_electron, excitation_number=0, fermion_qubit_mapping=<quri_parts.openfermion.transforms.OpenFermionJordanWignerFactory object>)[source]#
chemqulacs.vqe.vqeci.vqe(init_params, cost_fn, grad_fn, optimizer)[source]#
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