Stinespring#
- class qiskit.quantum_info.Stinespring(data, input_dims=None, output_dims=None)[fuente]#
Bases:
QuantumChannel
Stinespring representation of a quantum channel.
The Stinespring representation of a quantum channel \(\mathcal{E}\) is a rectangular matrix \(A\) such that the evolution of a
DensityMatrix
\(\rho\) is given by\[\mathcal{E}(ρ) = \mbox{Tr}_2\left[A ρ A^\dagger\right]\]where \(\mbox{Tr}_2\) is the
partial_trace()
over subsystem 2.A general operator map \(\mathcal{G}\) can also be written using the generalized Stinespring representation which is given by two matrices \(A\), \(B\) such that
\[\mathcal{G}(ρ) = \mbox{Tr}_2\left[A ρ B^\dagger\right]\]See reference [1] for further details.
Referencias
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 Stinespring operator.
- Parámetros:
or (data (QuantumCircuit) – 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]
- Muestra:
QiskitError – if input data cannot be initialized as a a list of Kraus matrices.
- Additional Information:
If the input or output dimensions are None, they will be automatically determined from the input data. This can fail for the Stinespring operator if the output dimension cannot be automatically determined.
Attributes
- atol = 1e-08#
- data#
- 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 = 1e-05#
- settings#
Return settings.
Methods
- adjoint()#
Return the adjoint quantum channel.
Nota
This is equivalent to the matrix Hermitian conjugate in the
SuperOp
representation ie. for a channel \(\mathcal{E}\), the SuperOp of the adjoint channel \(\mathcal{{E}}^\dagger\) is \(S_{\mathcal{E}^\dagger} = S_{\mathcal{E}}^\dagger\).- Tipo del valor devuelto:
Self
- compose(other, qargs=None, front=False)[fuente]#
Return the operator composition with another Stinespring.
- Parámetros:
other (Stinespring) – a Stinespring 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].
- Devuelve:
The composed Stinespring.
- Tipo del valor devuelto:
- Muestra:
QiskitError – if other cannot be converted to an operator, or has incompatible dimensions for specified subsystems.
Nota
Composition (
&
) by default is defined as left matrix multiplication for matrix operators, while@
(equivalent todot()
) is defined as right matrix multiplication. That is thatA & B == A.compose(B)
is equivalent toB @ A == B.dot(A)
whenA
andB
are of the same type.Setting the
front=True
kwarg changes this to right matrix multiplication and is equivalent to thedot()
methodA.dot(B) == A.compose(B, front=True)
.
- conjugate()[fuente]#
Return the conjugate quantum channel.
Nota
This is equivalent to the matrix complex conjugate in the
SuperOp
representation ie. for a channel \(\mathcal{E}\), the SuperOp of the conjugate channel \(\overline{{\mathcal{{E}}}}\) is \(S_{\overline{\mathcal{E}^\dagger}} = \overline{S_{\mathcal{E}}}\).
- copy()#
Make a deep copy of current operator.
- dot(other, qargs=None)#
Return the right multiplied operator self * other.
- Parámetros:
- Devuelve:
The right matrix multiplied Operator.
- Tipo del valor devuelto:
Nota
The dot product can be obtained using the
@
binary operator. Hencea.dot(b)
is equivalent toa @ b
.
- expand(other)[fuente]#
Return the reverse-order tensor product with another Stinespring.
- Parámetros:
other (Stinespring) – a Stinespring object.
- Devuelve:
- the tensor product \(b \otimes a\), where \(a\)
is the current Stinespring, and \(b\) is the other Stinespring.
- Tipo del valor devuelto:
- input_dims(qargs=None)#
Return tuple of input dimension for specified subsystems.
- is_cp(atol=None, rtol=None)#
Test if Choi-matrix is completely-positive (CP)
- Tipo del valor devuelto:
- is_tp(atol=None, rtol=None)#
Test if a channel is trace-preserving (TP)
- Tipo del valor devuelto:
- is_unitary(atol=None, rtol=None)#
Return True if QuantumChannel is a unitary channel.
- Tipo del valor devuelto:
- output_dims(qargs=None)#
Return tuple of output dimension for specified subsystems.
- power(n)#
Return the power of the quantum channel.
- Parámetros:
n (float) – the power exponent.
- Devuelve:
the channel \(\mathcal{{E}} ^n\).
- Tipo del valor devuelto:
- Muestra:
QiskitError – if the input and output dimensions of the SuperOp are not equal.
Nota
For non-positive or non-integer exponents the power is defined as the matrix power of the
SuperOp
representation ie. for a channel \(\mathcal{{E}}\), the SuperOp of the powered channel \(\mathcal{{E}}^\n\) is \(S_{{\mathcal{{E}}^n}} = S_{{\mathcal{{E}}}}^n\).
- reshape(input_dims=None, output_dims=None, num_qubits=None)#
Return a shallow copy with reshaped input and output subsystem dimensions.
- Parámetros:
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].
- Devuelve:
returns self with reshaped input and output dimensions.
- Tipo del valor devuelto:
BaseOperator
- Muestra:
QiskitError – if combined size of all subsystem input dimension or subsystem output dimensions is not constant.
- tensor(other)[fuente]#
Return the tensor product with another Stinespring.
- Parámetros:
other (Stinespring) – a Stinespring object.
- Devuelve:
- the tensor product \(a \otimes b\), where \(a\)
is the current Stinespring, and \(b\) is the other Stinespring.
- Tipo del valor devuelto:
Nota
The tensor product can be obtained using the
^
binary operator. Hencea.tensor(b)
is equivalent toa ^ b
.
- to_instruction()#
Convert to a Kraus or UnitaryGate circuit instruction.
If the channel is unitary it will be added as a unitary gate, otherwise it will be added as a kraus simulator instruction.
- Devuelve:
A kraus instruction for the channel.
- Tipo del valor devuelto:
- Muestra:
QiskitError – if input data is not an N-qubit CPTP quantum channel.
- to_operator()#
Try to convert channel to a unitary representation Operator.
- Tipo del valor devuelto: