qml.labs.resource_estimation.ResourceSelect

class ResourceSelect(select_ops, wires=None)

Bases: ResourceOperator

Resource class for the Select gate.

Parameters:

• select_ops (list[ResourceOperator]) – the set of operations to select over

• wires (Sequence[int], optional) – The wires the operation acts on. If select_ops provide wire labels, then this is just the set of control wire labels. Otherwise, it also includes the target wire labels of the selected operators.

Resources:

The resources are based on the analysis in Babbush et al. (2018) section III.A, ‘Unary Iteration and Indexed Operations’. See Figures 4, 6, and 7.

Note: This implementation assumes we have access to \(n - 1\) additional work qubits, where \(n = \left\lceil log_{2}(N) \right\rceil\) and \(N\) is the number of batches of unitaries to select.

See also

Select

Example

The resources for this operation are computed using:

>>> ops = [plre.ResourceX(), plre.ResourceY(), plre.ResourceZ()]
>>> select_op = plre.ResourceSelect(select_ops=ops)
>>> print(plre.estimate(select_op))
--- Resources: ---
Total qubits: 4
Total gates : 24
Qubit breakdown:
 clean qubits: 1, dirty qubits: 0, algorithmic qubits: 3
Gate breakdown:
 {'CNOT': 7, 'S': 2, 'Z': 1, 'Hadamard': 8, 'X': 4, 'Toffoli': 2}

Attributes

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

num_wires = 1

resource_keys = {'cmpr_ops', 'num_wires'}

resource_params

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

Returns:

A dictionary containing the resource parameters:

• cmpr_ops (list[CompressedResourceOp]): The list of operators, in the compressed representation, to be applied according to the selected qubits.

• num_wires (int): The number of wires the operation acts on. This is a sum of the control wires (\(\lceil(log_{2}(N))\rceil\)) required and the number wires targeted by the select_ops.

Return type:

dict

Methods

adjoint_resource_decomp(*args, **kwargs)	Returns a list representing the resources for the adjoint of the operator.
controlled_resource_decomp(...)	Returns a list representing the resources for a controlled version of the operator.
dequeue(op_to_remove[, context])	Remove the given resource operator(s) from the Operator queue.
pow_resource_decomp(pow_z, *args, **kwargs)	Returns a list representing the resources for an operator raised to a power.
queue([context])	Append the operator to the Operator queue.
resource_decomp(cmpr_ops, num_wires, **kwargs)	The resources for a select implementation taking advantage of the unary iterator trick.
resource_rep(cmpr_ops[, num_wires])	Returns a compressed representation containing only the parameters of the Operator that are needed to compute a resource estimation.
resource_rep_from_op()	Returns a compressed representation directly from the operator
textbook_resources(cmpr_ops, num_wires, **kwargs)	Returns a list representing the resources of the operator.
tracking_name(*args, **kwargs)	Returns a name used to track the operator during resource estimation.
tracking_name_from_op()	Returns the tracking name built with the operator's parameters.

classmethod adjoint_resource_decomp(*args, **kwargs)

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

classmethod controlled_resource_decomp(ctrl_num_ctrl_wires, ctrl_num_ctrl_values, *args, **kwargs)

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

Parameters:

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

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

static dequeue(op_to_remove, context=<class 'pennylane.queuing.QueuingManager'>)

Remove the given resource operator(s) from the Operator queue.

classmethod pow_resource_decomp(pow_z, *args, **kwargs)

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

Parameters:

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

queue(context=<class 'pennylane.queuing.QueuingManager'>)

Append the operator to the Operator queue.

classmethod resource_decomp(cmpr_ops, num_wires, **kwargs)

The resources for a select implementation taking advantage of the unary iterator trick.

Parameters:

• cmpr_ops (list[CompressedResourceOp]) – The list of operators, in the compressed representation, to be applied according to the selected qubits.

• num_wires (int) – The number of wires the operation acts on. This is a sum of the control wires (\(\lceil(log_{2}(N))\rceil\)) required and the number wires targeted by the select_ops.

Resources:

The resources are based on the analysis in Babbush et al. (2018) section III.A, ‘Unary Iteration and Indexed Operations’. See Figures 4, 6, and 7.

Note: This implementation assumes we have access to \(n - 1\) additional work qubits, where \(n = \left\lceil log_{2}(N) \right\rceil\) and \(N\) is the number of batches of unitaries to select.

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(cmpr_ops, num_wires=None)

Returns a compressed representation containing only the parameters of the Operator that are needed to compute a resource estimation.

Parameters:

• cmpr_ops (list[CompressedResourceOp]) – The list of operators, in the compressed representation, to be applied according to the selected qubits.

• num_wires (int) – An optional parameter representing the number of wires the operation acts on. This is a sum of the control wires (\(\lceil(log_{2}(N))\rceil\)) required and the number of wires targeted by the select_ops.

Returns:

the operator in a compressed representation

Return type:

CompressedResourceOp

resource_rep_from_op()

Returns a compressed representation directly from the operator

static textbook_resources(cmpr_ops, num_wires, **kwargs)

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:

• cmpr_ops (list[CompressedResourceOp]) – The list of operators, in the compressed representation, to be applied according to the selected qubits.

• num_wires (int) – The number of wires the operation acts on. This is a sum of the control wires (\(\lceil(log_{2}(N))\rceil\)) required and the number wires targeted by the select_ops.

Resources:

The resources correspond directly to the definition of the operation. Specifically, for each operator in cmpr_ops, the cost is given as a controlled version of the operator controlled on the associated bitstring.

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 tracking_name(*args, **kwargs)

Returns a name used to track the operator during resource estimation.

tracking_name_from_op()

Returns the tracking name built with the operator’s parameters.

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