DictStateFn

class qiskit.opflow.state_fns.DictStateFn(*args, **kwargs)

Bases: StateFn

Deprecated: A class for state functions and measurements which are defined by a lookup table, stored in a dict.

Deprecated since version 0.24.0: The class qiskit.opflow.state_fns.dict_state_fn.DictStateFn 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 dict, single bitstring (if defining a basis sate), or Qiskit Result, which defines the behavior of the underlying function.

• coeff -- A coefficient by which to multiply 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 -- invalid parameters.

Attributes

INDENTATION = '  '

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: Dict[str, complex]

The primitive which defines the behavior of the underlying State function.

settings

Return settings.

Methods

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:

OperatorBase

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:

DictStateFn

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:

OperatorBase | complex

permute(permutation)

Permute the qubits of the state function.

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 StateFn containing the permuted primitive.

Return type:

DictStateFn

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:

Set[str]

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.

Parameters:

• shots (int) -- The number of samples to take to approximate the State function.

• massive (bool) -- Whether to allow large conversions, e.g. creating a matrix representing over 16 qubits.

• reverse_endianness (bool) -- Whether to reverse the endianness of the bitstrings in the return dict to match Terra's big-endianness.

Returns:

A dict containing pairs sampled strings from the State function and sampling frequency divided by shots.

Return type:

Dict[str, float]

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:

OperatorBase

to_circuit_op()

Convert this state function to a CircuitStateFn.

Return type:

OperatorBase

to_density_matrix(massive=False)

Return matrix representing product of StateFn evaluated on pairs of basis states. Overridden by child classes.

Parameters:

massive (bool) -- Whether to allow large conversions, e.g. creating a matrix representing over 16 qubits.

Returns:

The NumPy array representing the density matrix of the State function.

Raises:

ValueError -- If massive is set to False, and exponentially large computation is needed.

Return type:

ndarray

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:

ndarray

to_spmatrix()

Same as to_matrix, but returns csr sparse matrix.

Returns:

CSR sparse matrix representation of the State function.

Raises:

ValueError -- invalid parameters.

Return type:

spmatrix

to_spmatrix_op()

Convert this state function to a SparseVectorStateFn.

Return type:

OperatorBase