qiskit.aqua.algorithms.QPE
class QPE(operator=None, state_in=None, iqft=None, num_time_slices=1, num_ancillae=1, expansion_mode='trotter', expansion_order=1, shallow_circuit_concat=False, quantum_instance=None)
The Quantum Phase Estimation algorithm.
QPE (also sometimes abbreviated as PEA, for Phase Estimation Algorithm), has two quantum registers, control and target, where the control consists of several qubits initially put in uniform superposition, and the target a set of qubits prepared in an eigenstate (often a guess of the eigenstate) of the unitary operator of a quantum system. QPE then evolves the target under the control using dynamics on the unitary operator. The information of the corresponding eigenvalue is then ‘kicked-back’ into the phases of the control register, which can then be deconvoluted by an Inverse Quantum Fourier Transform (IQFT), and measured for read-out in binary decimal format. QPE also requires a reasonably good estimate of the eigen wave function to start the process. For example, when estimating molecular ground energies in chemistry, the Hartree-Fock method could be used to provide such trial eigen wave functions.
Parameters
- operator (
Union[OperatorBase,LegacyBaseOperator,None]) – The Hamiltonian Operator - state_in (
Optional[InitialState]) – An optional InitialState component representing an initial quantum state.Nonemay be supplied. - iqft (
Optional[QuantumCircuit]) – A Inverse Quantum Fourier Transform component - num_time_slices (
int) – The number of time slices, has a minimum value of 1. - num_ancillae (
int) – The number of ancillary qubits to use for the measurement, has a min. value of 1. - expansion_mode (
str) – The expansion mode (‘trotter’|’suzuki’) - expansion_order (
int) – The suzuki expansion order, has a min. value of 1. - shallow_circuit_concat (
bool) – Set True to use shallow (cheap) mode for circuit concatenation of evolution slices. By default this is False. Seeqiskit.aqua.operators.common.evolution_instruction()for more information. - quantum_instance (
Union[QuantumInstance,Backend,BaseBackend,None]) – Quantum Instance or Backend
__init__
__init__(operator=None, state_in=None, iqft=None, num_time_slices=1, num_ancillae=1, expansion_mode='trotter', expansion_order=1, shallow_circuit_concat=False, quantum_instance=None)
Parameters
- operator (
Union[OperatorBase,LegacyBaseOperator,None]) – The Hamiltonian Operator - state_in (
Optional[InitialState]) – An optional InitialState component representing an initial quantum state.Nonemay be supplied. - iqft (
Optional[QuantumCircuit]) – A Inverse Quantum Fourier Transform component - num_time_slices (
int) – The number of time slices, has a minimum value of 1. - num_ancillae (
int) – The number of ancillary qubits to use for the measurement, has a min. value of 1. - expansion_mode (
str) – The expansion mode (‘trotter’|’suzuki’) - expansion_order (
int) – The suzuki expansion order, has a min. value of 1. - shallow_circuit_concat (
bool) – Set True to use shallow (cheap) mode for circuit concatenation of evolution slices. By default this is False. Seeqiskit.aqua.operators.common.evolution_instruction()for more information. - quantum_instance (
Union[QuantumInstance,Backend,BaseBackend,None]) – Quantum Instance or Backend
Methods
__init__([operator, state_in, iqft, …]) | type operatorUnion[OperatorBase, LegacyBaseOperator, None] |
compute_minimum_eigenvalue([operator, …]) | Computes minimum eigenvalue. |
construct_circuit([measurement]) | Construct circuit. |
run([quantum_instance]) | Execute the algorithm with selected backend. |
set_backend(backend, **kwargs) | Sets backend with configuration. |
supports_aux_operators() | Whether computing the expectation value of auxiliary operators is supported. |
Attributes
aux_operators | Returns aux operators |
backend | Returns backend. |
operator | Returns operator |
quantum_instance | Returns quantum instance. |
random | Return a numpy random. |
aux_operators
Returns aux operators
Return type
Optional[List[Union[OperatorBase, LegacyBaseOperator]]]
backend
Returns backend.
Return type
Union[Backend, BaseBackend]
compute_minimum_eigenvalue
compute_minimum_eigenvalue(operator=None, aux_operators=None)
Computes minimum eigenvalue. Operator and aux_operators can be supplied here and if not None will override any already set into algorithm so it can be reused with different operators. While an operator is required by algorithms, aux_operators are optional. To ‘remove’ a previous aux_operators array use an empty list here.
Parameters
- operator (
Union[OperatorBase,LegacyBaseOperator,None]) – If not None replaces operator in algorithm - aux_operators (
Optional[List[Union[OperatorBase,LegacyBaseOperator]]]) – If not None replaces aux_operators in algorithm
Return type
MinimumEigensolverResult
Returns
MinimumEigensolverResult
construct_circuit
construct_circuit(measurement=False)
Construct circuit.
Parameters
measurement (bool) – Boolean flag to indicate if measurement should be included in the circuit.
Returns
quantum circuit.
Return type
operator
Returns operator
Return type
Optional[LegacyBaseOperator]
quantum_instance
Returns quantum instance.
Return type
Optional[QuantumInstance]
random
Return a numpy random.
run
run(quantum_instance=None, **kwargs)
Execute the algorithm with selected backend.
Parameters
- quantum_instance (
Union[QuantumInstance,Backend,BaseBackend,None]) – the experimental setting. - kwargs (dict) – kwargs
Returns
results of an algorithm.
Return type
dict
Raises
AquaError – If a quantum instance or backend has not been provided
set_backend
set_backend(backend, **kwargs)
Sets backend with configuration.
Return type
None
supports_aux_operators
classmethod supports_aux_operators()
Whether computing the expectation value of auxiliary operators is supported.
If the minimum eigensolver computes an eigenstate of the main operator then it can compute the expectation value of the aux_operators for that state. Otherwise they will be ignored.
Return type
bool
Returns
True if aux_operator expectations can be evaluated, False otherwise