qml.estimator.templates.HybridQRAM¶
- class HybridQRAM(data, num_wires, num_select_wires, num_control_wires, control_wires=None, target_wires=None, work_wires=None)[source]
Bases:
ResourceOperatorResource class for HybridQRAM.
- Parameters:
data (TensorLike | Sequence[str]) – The classical memory to retrieve values from.
num_wires (int) – The number of qubits the operation acts upon.
num_select_wires (int) – The number of “select” bits taken from
control_wires.num_control_wires (int) – The number of
control_wiresincluding select and tree control wires.control_wires (WiresLike) – The register that stores the index for the entry of the classical data we want to access.
target_wires (WiresLike) – The register in which the classical data gets loaded. The size of this register must equal each bitstring length in
bitstrings.work_wires (WiresLike) – The additional wires required to funnel the desired entry of
bitstringsinto thetarget_wiresregister. Thework_wiresregister includes the signal, bus, direction, left port and right port wires in that order for a tree of depth \((n-k)\). For more details, consult section 3 of arXiv:2306.03242.
- Raises:
ValueError – if the number of wires provided does not match
num_wires
- Resources:
The resources are obtained from the HybridQRAM implementation in PennyLane. Please find more details about the algorithm in Systems Architecture for Quantum Random Access Memory.
See also
Attributes
Returns a dictionary containing the minimal information needed to compute the resources.
- resource_keys = {'data', 'num_control_wires', 'num_select_wires', 'num_target_wires'}¶
- resource_params¶
Returns a dictionary containing the minimal information needed to compute the resources.
- Returns:
- A dictionary containing the resource parameters.
data (TensorLike | Sequence[str]): the classical memory to retrieve values from
num_wires (int): the number of qubits the operation acts upon
num_select_wires (int): the number of select wires
num_tree_control_wires (int): the number of
work_wiresminus the number of select wires
- Return type:
dict
Methods
resource_decomp(data, num_wires, ...)Returns a list representing the resources of the operator.
resource_rep(data, num_wires, ...)Returns a compressed representation containing only the parameters of the Operator that are needed to compute the resources.
tracking_name(data, num_wires, ...)Returns the tracking name built with the operator's parameters.
- classmethod resource_decomp(data, num_wires, num_select_wires, num_tree_control_wires)[source]¶
Returns a list representing the resources of the operator. Each object in the list represents a gate and the number of times it occurs in the circuit.
- Parameters:
data (TensorLike | Sequence[str]) – the classical memory to retrieve values from
num_wires (int) – the number of qubits the operation acts upon
num_select_wires (int) – the number of select wires
num_tree_control_wires (int) – the number of
work_wiresminus the number of select wires
- Resources:
The resources are obtained from the HybridQRAM implementation in PennyLane. Please find more details about the algorithm in Systems Architecture for Quantum Random Access Memory.
- 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(data, num_wires, num_select_wires, num_tree_control_wires)[source]¶
Returns a compressed representation containing only the parameters of the Operator that are needed to compute the resources.
- Parameters:
data (TensorLike | Sequence[str]) – the classical memory to retrieve values from
num_wires (int) – the number of qubits the operation acts upon
num_select_wires (int) – the number of select wires
num_tree_control_wires (int) – the number of
work_wiresminus the number of select wires
- Returns:
the operator in a compressed representation
- Return type: