qp.labs.estimator_beta.templates.LabsQROM

class LabsQROM(num_bitstrings, size_bitstring, num_bit_flips=None, borrow_qubits=True, select_swap_depth=None, wires=None, **kwargs)

Bases: ResourceOperator

Resource class for the Quantum Read-Only Memory (QROM) template.

Parameters:

• num_bitstrings (int) – the number of bitstrings that are to be encoded

• size_bitstring (int) – the length of each bitstring

• num_bit_flips (int | None) – The total number of \(1\)’s in the dataset. Defaults to (num_bitstrings * size_bitstring) // 2, which is half the dataset.

• borrow_qubits (bool) – Determine whether the auxiliary qubits should be borrowed (higher gate cost) or freshly allocated (higher qubit cost). Defaults to True.

• select_swap_depth (int | None) – A parameter \(\lambda\) that determines if data will be loaded in parallel by adding more rows following Figure 1.C of Low et al. (2024). Can be None, 1 or a positive integer power of two. Defaults to None, which sets the depth that minimizes T-gate count.

• wires (WiresLike | None) – The wires the operation acts on (control and target), excluding any additional qubits allocated during the decomposition (e.g select-swap wires).

Resources:

The resources for QROM are derived from Appendix A, B from Berry et al. (2019).

• borrow_qubits=True: Uses the borrowed qubit decomposition from Figure 4 of Appendix A in Berry et al. (2019).

• borrow_qubits=False: Uses the clean qubit decomposition from Appendix B in Berry et al. (2019).

See also

The associated PennyLane operation QROM and the resource operator QROM.

Example

The resources for this operation are computed using:

>>> import pennylane.labs.estimator_beta as qre
>>> qrom = qre.LabsQROM(
...     num_bitstrings=10,
...     size_bitstring=4,
... )
>>> print(qre.estimate(qrom))
--- Resources: ---
Total wires: 11
    algorithmic wires: 8
    allocated wires: 3
    zero state: 3
    any state: 0
Total gates : 86
'Toffoli': 8,
'CNOT': 36,
'X': 18,
'Hadamard': 24

Attributes

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

num_wires = None

resource_keys = {'borrow_qubits', 'num_bit_flips', 'num_bitstrings', 'select_swap_depth', 'size_bitstring'}

resource_params

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

Returns:

A dictionary containing the resource parameters:

• num_bitstrings (int): the number of bitstrings that are to be encoded

• size_bitstring (int): the length of each bitstring

• num_bit_flips (int | None): The total number of \(1\)’s in the dataset. Defaults to (num_bitstrings * size_bitstring) // 2, which is half the dataset.

• borrow_qubits (bool): Determine whether the auxiliary qubits should be borrowed (higher gate cost) or freshly allocated (higher qubit cost). Defaults to True.

• select_swap_depth (int | None): A parameter \(\lambda\) that determines if data will be loaded in parallel by adding more rows following Figure 1.C of Low et al. (2024). Can be None, 1 or a positive integer power of two. Defaults to None, which sets the depth that minimizes T-gate count.

Return type:

dict

Methods

add_parallel(other)	Adds a ResourceOperator or Resources in parallel.
add_series(other)	Adds a ResourceOperator or Resources in series.
adjoint_resource_decomp([target_resource_params])	Returns a list representing the resources of 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.
qrom_clean_auxiliary_adjoint_resource_decomp(...)	Returns a list representing the resources of the adjoint of the operator.
qrom_dirty_auxiliary_adjoint_resource_decomp(...)	Returns a list representing the resources of the adjoint of the operator.
queue([context])	Append the operator to the Operator queue.
resource_decomp(num_bitstrings, size_bitstring)	Returns a list of GateCount objects representing the operator's resources.
resource_rep(num_bitstrings, size_bitstring)	Returns a compressed representation containing only the parameters of the Operator that are needed to compute the resources.
resource_rep_from_op()	Returns a compressed representation directly from the operator
single_controlled_res_decomp(num_bitstrings, ...)	The resource decomposition for LabsQROM controlled on a single wire.
tracking_name(num_bitstrings, size_bitstring)	Returns a name used to track the operator during resource estimation.

add_parallel(other)

Adds a ResourceOperator or Resources in parallel.

Parameters:

other (ResourceOperator) – The other object to combine with, it can be another ResourceOperator or a Resources object.

Returns:

added Resources

Return type:

Resources

add_series(other)

Adds a ResourceOperator or Resources in series.

Parameters:

other (ResourceOperator) – The other object to combine with, it can be another ResourceOperator or a Resources object.

Returns:

added Resources

Return type:

Resources

classmethod adjoint_resource_decomp(target_resource_params=None)

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

Parameters:

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

Resources:

This is an alternate decomposition for the adjoint of QROM which uses a measurement and phase fixup algorithm. This decomposition requires one clean auxiliary qubit. The resources are based on Figure 7 in Appendix C of Berry et al. (2019).

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=None)

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 for QROM are derived from Appendix A, B from Berry et al. (2019).

• borrow_qubits=True: Uses the borrowed qubit decomposition from Figure 4 of Appendix A in Berry et al. (2019).

• borrow_qubits=False: Uses the clean qubit decomposition from Appendix B in Berry et al. (2019).

Note: we use the single-controlled unary iterator trick to implement the Select. This implementation assumes we have access to \(n\) additional work qubits, where \(n = \lceil \log_{2}(N) \rceil\) 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 pow_resource_decomp(pow_z, target_resource_params=None)

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

For a ResourceOperator that doesn’t define a pow_resource_decomp method, this will be its pow_resource_decomp method.

Resources:

The resources for an operator raised to some power are obtained by taking the base resource decomposition of the operator and tracking each gate raised to the given power. For a power of zero, the identity operator is returned. For a power of one, the base operator is returned.

Parameters:

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

• target_resource_params (dict | None) – A dictionary containing the resource parameters of the target operator.

classmethod qrom_clean_auxiliary_adjoint_resource_decomp(target_resource_params)

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

Parameters:

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

Resources:

This is an alternate decomposition for the adjoint of QROM which uses a measurement and phase fixup algorithm. This decomposition requires one clean auxiliary qubit. The resources are based on Figure 7 in Appendix C of Berry et al. (2019).

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 qrom_dirty_auxiliary_adjoint_resource_decomp(target_resource_params)

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

Parameters:

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

Resources:

This is an alternate decomposition for the adjoint of QROM which uses a measurement and phase fixup algorithm. This decomposition requires one borrowed auxiliary qubit. The resources are based on Figure 7 in Appendix C of Berry et al. (2019).

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]

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

Append the operator to the Operator queue.

classmethod resource_decomp(num_bitstrings, size_bitstring, num_bit_flips=None, borrow_qubits=True, select_swap_depth=None)

Returns a list of GateCount objects representing the operator’s resources.

Parameters:

• num_bitstrings (int) – the number of bitstrings that are to be encoded

• size_bitstring (int) – the length of each bitstring

• num_bit_flips (int | None) – The total number of \(1\)’s in the dataset. Defaults to (num_bitstrings * size_bitstring) // 2, which is half the dataset.

• borrow_qubits (bool) – Determine whether the auxiliary qubits should be borrowed (higher gate cost) or freshly allocated (higher qubit cost). Defaults to True.

• select_swap_depth (int | None) –

  A parameter \(\lambda\) that determines if data will be loaded in parallel by adding more rows following Figure 1.C of Low et al. (2024). Can be None, 1 or a positive integer power of two. Defaults to None, which sets the depth that minimizes T-gate count.

Resources:

The resources for QROM are derived from Appendix A, B from Berry et al. (2019).

• borrow_qubits=True: Uses the borrowed qubit decomposition from Figure 4 of Appendix A in Berry et al. (2019).

• borrow_qubits=False: Uses the clean qubit decomposition from Appendix B in Berry et al. (2019).

Note: we use the unary iterator trick to implement the Select. 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(num_bitstrings, size_bitstring, num_bit_flips=None, borrow_qubits=True, select_swap_depth=None)

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

Parameters:

• num_bitstrings (int) – the number of bitstrings that are to be encoded

• size_bitstring (int) – the length of each bitstring

• num_bit_flips (int | None) – The total number of \(1\)’s in the dataset. Defaults to (num_bitstrings * size_bitstring) // 2, which is half the dataset.

• borrow_qubits (bool) – Determine whether the auxiliary qubits should be borrowed (higher gate cost) or freshly allocated (higher qubit cost). Defaults to True.

• select_swap_depth (int | None) –

  A parameter \(\lambda\) that determines if data will be loaded in parallel by adding more rows following Figure 1.C of Low et al. (2024). Can be None, 1 or a positive integer power of two. Defaults to None, which sets the depth that minimizes T-gate count.

Returns:

the operator in a compressed representation

Return type:

CompressedResourceOp

resource_rep_from_op()

Returns a compressed representation directly from the operator

classmethod single_controlled_res_decomp(num_bitstrings, size_bitstring, num_bit_flips=None, select_swap_depth=None, borrow_qubits=True)

The resource decomposition for LabsQROM controlled on a single wire.

Parameters:

• num_bitstrings (int) – the number of bitstrings that are to be encoded

• size_bitstring (int) – the length of each bitstring

• num_bit_flips (int | None) – The total number of \(1\)’s in the dataset. Defaults to (num_bitstrings * size_bitstring) // 2, which is half the dataset.

• borrow_qubits (bool) – Determine whether the auxiliary qubits should be borrowed (higher gate cost) or freshly allocated (higher qubit cost). Defaults to True.

• select_swap_depth (int | None) –

  A parameter \(\lambda\) that determines if data will be loaded in parallel by adding more rows following Figure 1.C of Low et al. (2024). Can be None, 1 or a positive integer power of two. Defaults to None, which sets the depth that minimizes T-gate count.

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]

static tracking_name(num_bitstrings, size_bitstring, num_bit_flips=None, borrow_qubits=True, select_swap_depth=None)

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

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