CircuitStateFn
class qiskit.opflow.state_fns.CircuitStateFn(*args, **kwargs)
Bases: StateFn
Deprecated: A class for state functions and measurements which are defined by the action of a QuantumCircuit starting from |0⟩, and stored using Terra’s QuantumCircuit class.
The class qiskit.opflow.state_fns.circuit_state_fn.CircuitStateFn is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/opflow_migration.
Parameters
- primitive – The
QuantumCircuit(orInstruction, which will be converted) which defines the behavior of the underlying function. - coeff – A coefficient multiplying the state function.
- is_measurement – Whether the StateFn is a measurement operator.
- from_operator – if True the StateFn is derived from OperatorStateFn. (Default: False)
Raises
TypeError – Unsupported primitive, or primitive has ClassicalRegisters.
Attributes
INDENTATION
Default value: ' '
coeff
A coefficient by which the state function is multiplied.
instance_id
Return the unique instance id.
is_measurement
Whether the StateFn object is a measurement Operator.
num_qubits
parameters
primitive
Type: QuantumCircuit
The primitive which defines the behavior of the underlying State function.
settings
Return settings.
Methods
add
add(other)
Return Operator addition of self and other, overloaded by +.
Parameters
other (OperatorBase) – An OperatorBase with the same number of qubits as self, and in the same ‘Operator’, ‘State function’, or ‘Measurement’ category as self (i.e. the same type of underlying function).
Returns
An OperatorBase equivalent to the sum of self and other.
Return type
adjoint
adjoint()
Return a new Operator equal to the Operator’s adjoint (conjugate transpose), overloaded by ~. For StateFns, this also turns the StateFn into a measurement.
Returns
An OperatorBase equivalent to the adjoint of self.
Return type
assign_parameters
assign_parameters(param_dict)
Binds scalar values to any Terra Parameters in the coefficients or primitives of the Operator, or substitutes one Parameter for another. This method differs from Terra’s assign_parameters in that it also supports lists of values to assign for a give Parameter, in which case self will be copied for each parameterization in the binding list(s), and all the copies will be returned in an OpList. If lists of parameterizations are used, every Parameter in the param_dict must have the same length list of parameterizations.
Parameters
param_dict (dict) – The dictionary of Parameters to replace, and values or lists of values by which to replace them.
Returns
The OperatorBase with the Parameters in self replaced by the values or Parameters in param_dict. If param_dict contains parameterization lists, this OperatorBase is an OpList.
Return type
compose
compose(other, permutation=None, front=False)
Composition (Linear algebra-style: A@B(x) = A(B(x))) is not well defined for states in the binary function model, but is well defined for measurements.
Parameters
- other (OperatorBase) – The Operator to compose with self.
- permutation (List[int] | None) –
List[int]which defines permutation on other operator. - front (bool) – If front==True, return
other.compose(self).
Returns
An Operator equivalent to the function composition of self and other.
Raises
ValueError – If self is not a measurement, it cannot be composed from the right.
Return type
eval
eval(front=None)
Evaluate the Operator’s underlying function, either on a binary string or another Operator. A square binary Operator can be defined as a function taking a binary function to another binary function. This method returns the value of that function for a given StateFn or binary string. For example, op.eval('0110').eval('1110') can be seen as querying the Operator’s matrix representation by row 6 and column 14, and will return the complex value at those “indices.” Similarly for a StateFn, op.eval('1011') will return the complex value at row 11 of the vector representation of the StateFn, as all StateFns are defined to be evaluated from Zero implicitly (i.e. it is as if .eval('0000') is already called implicitly to always “indexing” from column 0).
If front is None, the matrix-representation of the operator is returned.
Parameters
front (str |Dict[str, complex] | ndarray |OperatorBase |Statevector | None) – The bitstring, dict of bitstrings (with values being coefficients), or StateFn to evaluated by the Operator’s underlying function, or None.
Returns
The output of the Operator’s evaluation function. If self is a StateFn, the result is a float or complex. If self is an Operator (PrimitiveOp, ComposedOp, SummedOp, EvolvedOp, etc.), the result is a StateFn. If front is None, the matrix-representation of the operator is returned, which is a MatrixOp for the operators and a VectorStateFn for state-functions. If either self or front contain proper ListOps (not ListOp subclasses), the result is an n-dimensional list of complex or StateFn results, resulting from the recursive evaluation by each OperatorBase in the ListOps.
Return type
from_dict
static from_dict(density_dict)
Construct the CircuitStateFn from a dict mapping strings to probability densities.
Parameters
density_dict (dict) – The dict representing the desired state.
Returns
The CircuitStateFn created from the dict.
Return type
from_vector
static from_vector(statevector)
Construct the CircuitStateFn from a vector representing the statevector.
Parameters
statevector (ndarray) – The statevector representing the desired state.
Returns
The CircuitStateFn created from the vector.
Return type
permute
permute(permutation)
Permute the qubits of the circuit.
Parameters
permutation (List[int]) – A list defining where each qubit should be permuted. The qubit at index j of the circuit should be permuted to position permutation[j].
Returns
A new CircuitStateFn containing the permuted circuit.
Return type
primitive_strings
primitive_strings()
Return a set of strings describing the primitives contained in the Operator. For example, {'QuantumCircuit', 'Pauli'}. For hierarchical Operators, such as ListOps, this can help illuminate the primitives represented in the various recursive levels, and therefore which conversions can be applied.
Returns
A set of strings describing the primitives contained within the Operator.
Return type
reduce
reduce()
Try collapsing the Operator structure, usually after some type of conversion, e.g. trying to add Operators in a SummedOp or delete needless IGates in a CircuitOp. If no reduction is available, just returns self.
Returns
The reduced OperatorBase.
Return type
sample
sample(shots=1024, massive=False, reverse_endianness=False)
Sample the state function as a normalized probability distribution. Returns dict of bitstrings in order of probability, with values being probability.
Return type
tensor
tensor(other)
Return tensor product between self and other, overloaded by ^. Note: You must be conscious of Qiskit’s big-endian bit printing convention. Meaning, Plus.tensor(Zero) produces a |+⟩ on qubit 0 and a |0⟩ on qubit 1, or |+⟩⨂|0⟩, but would produce a QuantumCircuit like:
|0⟩– |+⟩–
Because Terra prints circuits and results with qubit 0 at the end of the string or circuit.
Parameters
other (OperatorBase) – The OperatorBase to tensor product with self.
Returns
An OperatorBase equivalent to the tensor product of self and other.
Return type
to_circuit
to_circuit_op
to_density_matrix
to_density_matrix(massive=False)
Return numpy matrix of density operator, warn if more than 16 qubits to force the user to set massive=True if they want such a large matrix. Generally big methods like this should require the use of a converter, but in this case a convenience method for quick hacking and access to classical tools is appropriate.
Return type
to_instruction
to_instruction()
Return Instruction corresponding to primitive.
to_matrix
to_matrix(massive=False)
Return NumPy representation of the Operator. Represents the evaluation of the Operator’s underlying function on every combination of basis binary strings. Warn if more than 16 qubits to force having to set massive=True if such a large vector is desired.
Returns
The NumPy ndarray equivalent to this Operator.
Return type