TensoredOp

class qiskit.opflow.list_ops.TensoredOp(oplist, coeff=1.0, abelian=False)

Bases: ListOp

Deprecated: A class for lazily representing tensor products of Operators. Often Operators cannot be efficiently tensored to one another, but may be manipulated further so that they can be later. This class holds logic to indicate that the Operators in oplist are meant to be tensored together, and therefore if they reach a point in which they can be, such as after conversion to QuantumCircuits, they can be reduced by tensor product.

Deprecated since version 0.24.0: The class qiskit.opflow.list_ops.tensored_op.TensoredOp 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:

• oplist (List[OperatorBase]) – The Operators being tensored.

• coeff (complex | ParameterExpression) – A coefficient multiplying the operator

• abelian (bool) – Indicates whether the Operators in oplist are known to mutually commute.

Attributes

INDENTATION = '  '

abelian

Whether the Operators in oplist are known to commute with one another.

Returns:

A bool indicating whether the oplist is Abelian.

coeff

The scalar coefficient multiplying the Operator.

Returns:

The coefficient.

coeffs

Return a list of the coefficients of the operators listed. Raises exception for nested Listops.

combo_fn

The function defining how to combine oplist (or Numbers, or NumPy arrays) to produce the Operator’s underlying function. For example, SummedOp’s combination function is to add all of the Operators in oplist.

Returns:

The combination function.

distributive

grad_combo_fn

The gradient of combo_fn.

instance_id

Return the unique instance id.

num_qubits

oplist

The list of OperatorBases defining the underlying function of this Operator.

Returns:

The Operators defining the ListOp

parameters

settings

Return settings.

Methods

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).

ListOp’s eval recursively evaluates each Operator in oplist, and combines the results using the recombination function combo_fn.

Parameters:

front (str | dict | ndarray | OperatorBase | Statevector | None) – The bitstring, dict of bitstrings (with values being coefficients), or StateFn to evaluated by the Operator’s underlying function.

Returns:

The output of the oplist Operators’ evaluation function, combined with the combo_fn. 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.

Raises:

• NotImplementedError – Raised if called for a subclass which is not distributive.

• TypeError – Operators with mixed hierarchies, such as a ListOp containing both PrimitiveOps and ListOps, are not supported.

• NotImplementedError – Attempting to call ListOp’s eval from a non-distributive subclass.

Return type:

OperatorBase | complex

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:

OperatorBase

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, X.tensor(Y) produces an X on qubit 0 and an Y on qubit 1, or X⨂Y, but would produce a QuantumCircuit which looks like

-[Y]- -[X]-

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()

Returns the quantum circuit, representing the tensored operator.

Returns:

The circuit representation of the tensored operator.

Raises:

OpflowError – for operators where a single underlying circuit can not be produced.

Return type:

QuantumCircuit

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