ScalarOp
class qiskit.quantum_info.ScalarOp(dims=None, coeff=1)
Bases: LinearOp
Scalar identity operator class.
This is a symbolic representation of an scalar identity operator on multiple subsystems. It may be used to initialize a symbolic scalar multiplication of an identity and then be implicitly converted to other kinds of operator subclasses by using the compose(), dot(), tensor(), expand() methods.
Initialize an operator object.
Parameters
- dims (int ortuple) – subsystem dimensions.
- coeff (Number) – scalar coefficient for the identity operator (Default: 1).
Raises
QiskitError – If the optional coefficient is invalid.
Attributes
atol
Default value: 1e-08
coeff
Return the coefficient
dim
Return tuple (input_shape, output_shape).
num_qubits
Return the number of qubits if a N-qubit operator or None otherwise.
qargs
Return the qargs for the operator.
rtol
Default value: 1e-05
Methods
adjoint
adjoint()
Return the adjoint of the Operator.
Return type
Self
compose
compose(other, qargs=None, front=False)
Return the operator composition with another ScalarOp.
Parameters
- other (ScalarOp) – a ScalarOp object.
- qargs (list or None) – Optional, a list of subsystem positions to apply other on. If None apply on all subsystems (default: None).
- front (bool) – If True compose using right operator multiplication, instead of left multiplication [default: False].
Returns
The composed ScalarOp.
Return type
Raises
QiskitError – if other cannot be converted to an operator, or has incompatible dimensions for specified subsystems.
Composition (&) by default is defined as left matrix multiplication for matrix operators, while @ (equivalent to dot()) is defined as right matrix multiplication. That is that A & B == A.compose(B) is equivalent to B @ A == B.dot(A) when A and B are of the same type.
Setting the front=True kwarg changes this to right matrix multiplication and is equivalent to the dot() method A.dot(B) == A.compose(B, front=True).
conjugate
conjugate()
Return the conjugate of the ScalarOp.
copy
copy()
Make a deep copy of current operator.
dot
dot(other, qargs=None)
Return the right multiplied operator self * other.
Parameters
- other (Operator) – an operator object.
- qargs (list or None) – Optional, a list of subsystem positions to apply other on. If None apply on all subsystems (default: None).
Returns
The right matrix multiplied Operator.
Return type
The dot product can be obtained using the @ binary operator. Hence a.dot(b) is equivalent to a @ b.
expand
expand(other)
Return the reverse-order tensor product with another ScalarOp.
Parameters
other (ScalarOp) – a ScalarOp object.
Returns
the tensor product , where
is the current ScalarOp, and is the other ScalarOp.
Return type
input_dims
input_dims(qargs=None)
Return tuple of input dimension for specified subsystems.
is_unitary
is_unitary(atol=None, rtol=None)
Return True if operator is a unitary matrix.
output_dims
output_dims(qargs=None)
Return tuple of output dimension for specified subsystems.
power
power(n)
Return the power of the ScalarOp.
Parameters
n (float) – the exponent for the scalar op.
Returns
the coeff ** n ScalarOp.
Return type
reshape
reshape(input_dims=None, output_dims=None, num_qubits=None)
Return a shallow copy with reshaped input and output subsystem dimensions.
Parameters
- input_dims (None or tuple) – new subsystem input dimensions. If None the original input dims will be preserved [Default: None].
- output_dims (None or tuple) – new subsystem output dimensions. If None the original output dims will be preserved [Default: None].
- num_qubits (None or int) – reshape to an N-qubit operator [Default: None].
Returns
returns self with reshaped input and output dimensions.
Return type
BaseOperator
Raises
QiskitError – if combined size of all subsystem input dimension or subsystem output dimensions is not constant.
tensor
tensor(other)
Return the tensor product with another ScalarOp.
Parameters
other (ScalarOp) – a ScalarOp object.
Returns
the tensor product , where
is the current ScalarOp, and is the other ScalarOp.
Return type
The tensor product can be obtained using the ^ binary operator. Hence a.tensor(b) is equivalent to a ^ b.
to_matrix
to_matrix()
Convert to a Numpy matrix.
to_operator
transpose
transpose()
Return the transpose of the ScalarOp.