pennylane_forest.ISWAP¶

class
ISWAP
(wires)[source]¶ Bases:
pennylane.operation.Operation
iSWAP gate.
\[\begin{split}ISWAP = \begin{bmatrix} 1 & 0 & 0 & 0 \\ 0 & 0 & i & 0\\ 0 & i & 0 & 0\\ 0 & 0 & 0 & 1 \end{bmatrix}.\end{split}\]Details:
 Number of wires: 3
 Number of parameters: 0
Parameters: wires (int) – the subsystem the gate acts on Attributes
base_name
Get base name of the operator. basis
control_wires
For operations that are controlled, returns the set of control wires. eigvals
Eigenvalues of an instantiated operator. generator
Generator of the operation. grad_method
Gradient computation method. grad_recipe
id
String for the ID of the operator. inverse
Boolean determining if the inverse of the operation was requested. is_composable_rotation
is_self_inverse
is_symmetric_over_all_wires
is_symmetric_over_control_wires
matrix
Matrix representation of an instantiated operator in the computational basis. name
Get and set the name of the operator. num_params
num_wires
par_domain
parameters
Current parameter values. single_qubit_rot_angles
The parameters required to implement a singlequbit gate as an equivalent Rot
gate, up to a global phase.string_for_inverse
wires
Wires of this operator. 
base_name
¶ Get base name of the operator.

basis
= None¶

control_wires
¶ For operations that are controlled, returns the set of control wires.
Returns: The set of control wires of the operation. Return type: Wires

eigvals
¶ Eigenvalues of an instantiated operator.
Note that the eigenvalues are not guaranteed to be in any particular order.
Example:
>>> U = qml.RZ(0.5, wires=1) >>> U.eigvals >>> array([0.968912420.24740396j, 0.96891242+0.24740396j])
Returns: eigvals representation Return type: array

generator
¶ Generator of the operation.
A length2 list
[generator, scaling_factor]
, wheregenerator
is an existing PennyLane operation class or \(2\times 2\) Hermitian array that acts as the generator of the current operationscaling_factor
represents a scaling factor applied to the generator operation
For example, if \(U(\theta)=e^{i0.7\theta \sigma_x}\), then \(\sigma_x\), with scaling factor \(s\), is the generator of operator \(U(\theta)\):
generator = [PauliX, 0.7]
Default is
[None, 1]
, indicating the operation has no generator.

grad_method
¶ Gradient computation method.
'A'
: analytic differentiation using the parametershift method.'F'
: finite difference numerical differentiation.None
: the operation may not be differentiated.
Default is
'F'
, orNone
if the Operation has zero parameters.

grad_recipe
= None¶

id
¶ String for the ID of the operator.

inverse
¶ Boolean determining if the inverse of the operation was requested.

is_composable_rotation
= None¶

is_self_inverse
= None¶

is_symmetric_over_all_wires
= None¶

is_symmetric_over_control_wires
= None¶

matrix
¶ Matrix representation of an instantiated operator in the computational basis.
Example:
>>> U = qml.RY(0.5, wires=1) >>> U.matrix >>> array([[ 0.96891242+0.j, 0.24740396+0.j], [ 0.24740396+0.j, 0.96891242+0.j]])
Returns: matrix representation Return type: array

name
¶ Get and set the name of the operator.

num_params
= 0¶

num_wires
= 2¶

par_domain
= None¶

parameters
¶ Current parameter values.

single_qubit_rot_angles
¶ The parameters required to implement a singlequbit gate as an equivalent
Rot
gate, up to a global phase.Returns: A list of values \([\phi, \theta, \omega]\) such that \(RZ(\omega) RY(\theta) RZ(\phi)\) is equivalent to the original operation. Return type: tuple[float, float, float]

string_for_inverse
= '.inv'¶

wires
¶ Wires of this operator.
Returns: wires Return type: Wires
Methods
adjoint
([do_queue])Create an operation that is the adjoint of this one. decomposition
()Returns a template decomposing the operation into other quantum operations. expand
()Returns a tape containing the decomposed operations, rather than a list. get_parameter_shift
(idx[, shift])Multiplier and shift for the given parameter, based on its gradient recipe. inv
()Inverts the operation, such that the inverse will be used for the computations by the specific device. queue
([context])Append the operator to the Operator queue. 
adjoint
(do_queue=False)¶ Create an operation that is the adjoint of this one.
Adjointed operations are the conjugated and transposed version of the original operation. Adjointed ops are equivalent to the inverted operation for unitary gates.
Parameters: do_queue – Whether to add the adjointed gate to the context queue. Returns: The adjointed operation.

decomposition
()[source]¶ Returns a template decomposing the operation into other quantum operations.

expand
()¶ Returns a tape containing the decomposed operations, rather than a list.
Returns: Returns a quantum tape that contains the operations decomposition, or if not implemented, simply the operation itself. Return type: JacobianTape

get_parameter_shift
(idx, shift=1.5707963267948966)¶ Multiplier and shift for the given parameter, based on its gradient recipe.
Parameters: idx (int) – parameter index Returns: list of multiplier, coefficient, shift for each term in the gradient recipe Return type: list[[float, float, float]]

inv
()¶ Inverts the operation, such that the inverse will be used for the computations by the specific device.
This method concatenates a string to the name of the operation, to indicate that the inverse will be used for computations.
Any subsequent call of this method will toggle between the original operation and the inverse of the operation.
Returns: operation to be inverted Return type: Operator

queue
(context=<class 'pennylane.queuing.QueuingContext'>)¶ Append the operator to the Operator queue.
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