SuperOp

class SuperOp(data, input_dims=None, output_dims=None)[source]

Superoperator representation of a quantum channel.

The Superoperator representation of a quantum channel \(\mathcal{E}\) is a matrix \(S\) such that the evolution of a DensityMatrix \(\rho\) is given by

\[|\mathcal{E}(\rho)\rangle\!\rangle = S |\rho\rangle\!\rangle\]

where the double-ket notation \(|A\rangle\!\rangle\) denotes a vector formed by stacking the columns of the matrix \(A\) (column-vectorization).

See reference [1] for further details.

References

  1. C.J. Wood, J.D. Biamonte, D.G. Cory, Tensor networks and graphical calculus for open quantum systems, Quant. Inf. Comp. 15, 0579-0811 (2015). arXiv:1111.6950 [quant-ph]

Initialize a quantum channel Superoperator operator.

Parameters
  • (QuantumCircuit or (data) – Instruction or BaseOperator or matrix): data to initialize superoperator.

  • input_dims (tuple) – the input subsystem dimensions. [Default: None]

  • output_dims (tuple) – the output subsystem dimensions. [Default: None]

Raises

QiskitError – if input data cannot be initialized as a superoperator.

Additional Information:

If the input or output dimensions are None, they will be automatically determined from the input data. If the input data is a Numpy array of shape (4**N, 4**N) qubit systems will be used. If the input operator is not an N-qubit operator, it will assign a single subsystem with dimension specified by the shape of the input.

Attributes

SuperOp.atol

The default absolute tolerance parameter for float comparisons.

SuperOp.data

Return data.

SuperOp.dim

Return tuple (input_shape, output_shape).

SuperOp.num_qubits

Return the number of qubits if a N-qubit operator or None otherwise.

SuperOp.qargs

Return the qargs for the operator.

SuperOp.rtol

The relative tolerance parameter for float comparisons.

Methods

SuperOp.__call__(qargs)

Return a clone with qargs set

SuperOp.__mul__(other)

SuperOp.add(other)

Return the linear operator self + other.

SuperOp.adjoint()

Return the adjoint of the operator.

SuperOp.compose(other[, qargs, front])

Return the composed quantum channel self @ other.

SuperOp.conjugate()

Return the conjugate of the QuantumChannel.

SuperOp.copy()

Make a deep copy of current operator.

SuperOp.dot(other[, qargs])

Return the right multiplied operator self * other.

SuperOp.expand(other)

Return the tensor product channel other ⊗ self.

SuperOp.input_dims([qargs])

Return tuple of input dimension for specified subsystems.

SuperOp.is_cp([atol, rtol])

Test if Choi-matrix is completely-positive (CP)

SuperOp.is_cptp([atol, rtol])

Return True if completely-positive trace-preserving (CPTP).

SuperOp.is_tp([atol, rtol])

Test if a channel is completely-positive (CP)

SuperOp.is_unitary([atol, rtol])

Return True if QuantumChannel is a unitary channel.

SuperOp.multiply(other)

Return the linear operator other * self.

SuperOp.output_dims([qargs])

Return tuple of output dimension for specified subsystems.

SuperOp.power(n)

Return the compose of a QuantumChannel with itself n times.

SuperOp.reshape([input_dims, output_dims])

Return a shallow copy with reshaped input and output subsystem dimensions.

SuperOp.set_atol(value)

Set the class default absolute tolerance parameter for float comparisons.

SuperOp.set_rtol(value)

Set the class default relative tolerance parameter for float comparisons.

SuperOp.subtract(other)

Return the linear operator self - other.

SuperOp.tensor(other)

Return the tensor product channel self ⊗ other.

SuperOp.to_instruction()

Convert to a Kraus or UnitaryGate circuit instruction.

SuperOp.to_operator()

Try to convert channel to a unitary representation Operator.

SuperOp.transpose()

Return the transpose of the QuantumChannel.

SuperOp.__mul__(other)

SuperOp.__call__(qargs)

Return a clone with qargs set