chemqulacs.vqe.vqeci module

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

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)

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

Bases: object

Base class represents backend

class chemqulacs.vqe.vqeci.ITensorBackend

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)

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

Bases: Backend

Backend class for Qulacs

class chemqulacs.vqe.vqeci.VQECI(mol=None, fermion_qubit_mapping=<quri_parts.openfermion.transforms.OpenFermionJordanWigner object>, optimizer=<quri_parts.algo.optimizer.adam.Adam object>, backend: ~chemqulacs.vqe.vqeci.Backend = <chemqulacs.vqe.vqeci.QulacsBackend object>, shots_per_iter: int = 10000, 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)

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) –

• 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)

make_dm2(_, norb, nelec, link_index=None, **kwargs)

make_rdm1(_, norb, nelec, link_index=None, **kwargs)

make_rdm12(_, norb, nelec, link_index=None, **kwargs)

spin_square(civec, norb, nelec)

chemqulacs.vqe.vqeci.vqe(init_params, cost_fn, grad_fn, optimizer)