qml.estimator.ops.CRY

class CRY(precision=None, wires=None)

Bases: ResourceOperator

Resource class for the CRY gate.

Parameters:

• wires (Sequence[int] | None) – the wire the operation acts on

• precision (float | None) – The error threshold for clifford plus T decomposition of the rotation gate. The default value is None which corresponds to using the epsilon stated in the config.

Resources:

The resources are taken from Figure 1b of arXiv:2110.10292. In combination with the following identity:

\[\hat{RY}(\theta) = \hat{X} \cdot \hat{RY}(- \theta) \cdot \hat{X}.\]

By replacing the X gates with CNOT gates, we obtain a controlled-version of this identity. Thus we are able to constructively or destructively interfere the gates based on the value of the control qubit. Specifically, the resources are defined as two CNOT gates and two RY gates.

See also

The corresponding PennyLane operation CRY.

Example

The resources for this operation are computed using:

>>> qml.estimator.CRY.resource_decomp()
[(2 x CNOT), (2 x RY)]

Attributes

num_wires
resource_keys
resource_params	Returns a dictionary containing the minimal information needed to compute the resources.

num_wires = 2

resource_keys = {'precision'}

resource_params

Returns a dictionary containing the minimal information needed to compute the resources.

Returns:

A dictionary containing the resource parameters:

• precision (float | None): the number of qubits the operation is controlled on

Return type:

dict

Methods

adjoint_resource_decomp(target_resource_params)	Returns a list representing the resources for the adjoint of the operator.
controlled_resource_decomp(num_ctrl_wires, ...)	Returns a list representing the resources for a controlled version of the operator.
pow_resource_decomp(pow_z, ...)	Returns a list representing the resources for an operator raised to a power.
resource_decomp([precision])	Returns a list representing the resources of the operator.
resource_rep([precision])	Returns a compressed representation containing only the parameters of the operator that are needed to compute the resources.

classmethod adjoint_resource_decomp(target_resource_params)

Returns a list representing the resources for the adjoint of the operator.

Parameters:

target_resource_params (dict) – A dictionary containing the resource parameters of the target operator.

Resources:

The adjoint of a single qubit rotation changes the sign of the rotation angle, thus the resources of the adjoint operation result are same as the originial operation.

Returns:

A list of GateCount objects, where each object represents a specific quantum gate and the number of times it appears in the decomposition.

Return type:

list[GateCount]

classmethod controlled_resource_decomp(num_ctrl_wires, num_zero_ctrl, target_resource_params)

Returns a list representing the resources for a controlled version of the operator.

Parameters:

• num_ctrl_wires (int) – the number of qubits the operation is controlled on

• num_zero_ctrl (int) – the number of control qubits, that are controlled when in the \(|0\rangle\) state

• target_resource_params (dict) – A dictionary containing the resource parameters of the target operator.

Resources:

The resources are expressed using the symbolic Controlled. The resources are computed according to the controlled_resource_decomp() of the base RY class.

Returns:

A list of GateCount objects, where each object represents a specific quantum gate and the number of times it appears in the decomposition.

Return type:

list[GateCount]

classmethod pow_resource_decomp(pow_z, target_resource_params)

Returns a list representing the resources for an operator raised to a power.

Parameters:

• pow_z (int) – the power that the operator is being raised to

• target_resource_params (dict) – A dictionary containing the resource parameters of the target operator.

Resources:

Taking arbitrary powers of a single qubit rotation produces a sum of rotations. The resources simplify to just one total single qubit rotation.

Returns:

A list of GateCount objects, where each object represents a specific quantum gate and the number of times it appears in the decomposition.

Return type:

list[GateCount]

classmethod resource_decomp(precision=None)

Returns a list representing the resources of the operator.

Parameters:

precision (float | None) – The error threshold for clifford plus T decomposition of the rotation gate. The default value is None which corresponds to using the epsilon stated in the config.

Resources:

The resources are taken from Figure 1b of arXiv:2110.10292. In combination with the following identity:

\[\hat{RY}(\theta) = \hat{X} \cdot \hat{RY}(- \theta) \cdot \hat{X}.\]

By replacing the X gates with CNOT gates, we obtain a controlled-version of this identity. Thus we are able to constructively or destructively interfere the gates based on the value of the control qubit. Specifically, the resources are defined as two CNOT gates and two RY gates.

Returns:

A list of GateCount objects, where each object represents a specific quantum gate and the number of times it appears in the decomposition.

Return type:

list[GateCount]

classmethod resource_rep(precision=None)

Returns a compressed representation containing only the parameters of the operator that are needed to compute the resources.

Parameters:

precision (float | None) – The error threshold for the Clifford + T decomposition of this operation.

Returns:

A compressed representation of the operator.

Return type:

CompressedResourceOp

code/api/pennylane.estimator.ops.CRY

 

Download Python script

 

Download Notebook

 

View on GitHub